{"found":53989,"hits":[{"document":{"authors":[{"affiliation":[{"name":"Imperial College London, Chemstry"}],"contributor_roles":[],"family":"Rzepa","given":"Henry","url":"https://orcid.org/0000-0002-8635-8390"}],"blog":{"authors":[{"name":"Henry Rzepa","url":"https://orcid.org/0000-0002-8635-8390"}],"community_id":"8fb94c86-e95f-41cf-aac2-a2877ffc1b5f","created":1693094400,"current_feed_url":null,"description":"Chemistry with a twist","doi":"https://doi.org/10.59350/rzepa","favicon":"https://rogue-scholar.org/api/communities/8fb94c86-e95f-41cf-aac2-a2877ffc1b5f/logo","feed_format":"application/atom+xml","feed_url":"https://www.ch.ic.ac.uk/rzepa/blog/?feed=atom","filter":null,"generator":"WordPress","home_page_url":"https://www.ch.ic.ac.uk/rzepa/blog","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"rzepa","status":"active","subfield":"1606","title":"Henry Rzepa's Blog","updated":1787733932,"use_api":true},"blog_name":"Henry Rzepa's Blog","blog_slug":"rzepa","content_html":"
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I have in the past (around 2012 to be specific) taken an interest in a particular type of [3,3]sigmatropic pericyclic reaction called the semibullvalene rearrangement.[1],[2],[3]. This system can apparently exhibit very long C-C bonds in the region of 2.1\u00c5, in which form it would be called a “frozen” transition state, also referred to a bis-homoaromatic molecule, which in this form is NOT regarded as a [3,3]sigmatropic pericyclic transition state. Time for an update I thought, starting with a crystal structure search (Figure 1) for these types of species.

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Figure 1. Search query.

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Figure 2. C-C bond lengths, showing publication date.

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Figure 3. C-C bond lengths showing measurement temperature.

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The bottom right region of these maps (Figures 2 and 3) contains examples for which both DIST and DIST2 are more or less equal with values of ~2.1A. Note that all but one have been measured at room temperatures, which means that the structure is measured with a lot of thermal motions for the atoms. Some molecules have been singled out from the map above and two of those have been selected for DFT calculations – ICILAI which is characterised by dispersion attractions between ethyl groups on the bulvallene unit and CASFUE which instead has polar cyano groups.

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CSD EntryC-C 1C-C 2TempDOI
ICILAI1.9312.084RT[4]
ICILAI011.6902.325140[5]
ICIKUB1.9722.017RT[4]
CAZFUE011.9901.996RT[6]
LAGHOG031.6712.20615[7]
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Note that ICILAI, which has more or less equal bonds when measured at RT, shows very unequal bonds at\u00a0140K. The question we are asking here is whether there are any examples where the equal and long C-C bonds genuinely persist down to low temperatures and which therefore constitute especially “long” C-C bonds as part of a bis-homoaromatic molecule. The “bond” here would not be an abnormally long conventional \u03c3-bond but instead what is called a “suspended \u03c0-bond”\u00a0and considered a “normal” length for such an interaction.

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Entry\u03bdC-C
\nMN15L[8]/Def2-TZVPP		DOI MN15L\u03bdC-C
\nr2SCAN-3c/Def2-mTZVPPL[9]		\u03bdC-C
\n\u03c9B97XD[10]/Def2-TZVPP		DOI \u03c9B97XD
CAZFUE01+214.7[11],[12]+234.1 (+291.6)\u2021-281.3[13],[14]
ICILAI-38.6[15]-155.8-356.0[16]
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What emerges from the calculations is that the characterisation as either a [3,3]-sigmatropic pericyclic transition state or as a bis-homoaromatic ground state is very dependent on the DFT functional being used.

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  1. For CAZFUE the conventional \u03c9B97XD/Def2-TZVPP method gives results belonging to the classical camp of predicting both examples above as being [3,3] sigmatropic transition states, with a characteristic strong calculated negative force constant and an IRC that shows the equal bond length position only as an energy maximum along the transition coordinate, albeit with a relatively modest barrier of ~5 kcal/mol. Such a value is higher than the energy of thermal vibrations, and so at low temperatures the structure will be frozen to either end of the IRC and show unequal C-C bonds of 1.614\u00c5 and 2.338\u00c5, typical of those found in the table above.
    \n\"\"
    \nFigure 4. \u03c9B97XD/Def2-TZVPP IRC for CAZFUE.
    2. \n
  2. The MN15L DFT method[8] (which is optimised specifically for transition metal elements) predicts a symmetrical long bond bis-homoaromatic structure\u00a0(C-C 2.135\u00c5) for CAZFUE, with a positive antisymmetric C-C stretch of +215 cm-1, almost equal in magnitude to \u03c9B97XD but opposite in sign for the force constant (Figure 5).
    \n\"\"
    \nFigure 5. MN15L normal vibrational C-C mode for CAZFUI.
    3. \n
  3. The newer r2SCAN-3c/Def2-mTZVPP functional is very similar in behaviour to MN15L.
    4. \n
  4. With MN15L, ICILAI however weakly retains the classical transition state mode, but now the C-C antisymmetric stretch is small with a negative FC (Figure 6). One wonders whether the difference is due to the dispersion attractions vs the electronic effect of a cyano group? The \u00a0r2SCAN-3c/Def2-mTZVPP method predicts a larger -ve FC (\u0394\u0394G\u2021 3.2 kcal/mol) but not as large as using \u03c9B97XD.
    \n\"\"
    \nFigure 6. MN15L normal vibrational C-C mode for ICILAI.
    5. \n
  5. In contrast to both MN15L and to a lesser extent \u00a0r2SCAN-3c/Def2-mTZVPP, using \u03c9B97XD for ICILAI reveals it is now strongly characterised as a [3,3] transition state.
    6. \n
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I note from Figure 2 that many of these crystal structures are quite old – clearly this area of research is no longer highly active. But such structures are proving invaluable tests of how density functional procedures perform for these molecules. Thus r2SCAN-3c/Def2-mTZVPP as a recent new method[17] is giving significantly different results from the much older \u03c9B97XD functional. But is it correct? More accurate and reliable crystal structures might help provide an answer – perhaps obtained using quantum crystallography? Or repeating the structure CAZFUI at say 15K.

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\u2021 Value for C2v symmetric tetra-cyano derivative.

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This post has DOI: 10.59350/sjyby-4yw41

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References

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  1. H. Rzepa, \"Predicted properties of a candidate for a frozen semibullvalene.\", 2012. https://doi.org/10.59350/cq2a3-g2g35\n\n
    2. \n
  2. H. Rzepa, \"Frozen Semibullvalene: a holy grail (and a bis-homoaromatic molecule).\", 2012. https://doi.org/10.59350/585c3-dpy86\n\n
    3. \n
  3. H. Rzepa, \"The ten-electron homologue of semibullvalene.\", 2012. https://doi.org/10.59350/8nkna-ycy23\n\n
    4. \n
  4. C. Wang, J. Yuan, G. Li, Z. Wang, S. Zhang, and Z. Xi, \"Metal-Mediated Efficient Synthesis, Structural Characterization, and Skeletal Rearrangement of Octasubstituted Semibullvalenes\", Journal of the American Chemical Society, vol. 128, pp. 4564-4565, 2006. https://doi.org/10.1021/ja0579208\n\n
    5. \n
  5. S. Zhang, M. Zhan, Q. Wang, C. Wang, W. Zhang, and Z. Xi, \"Synthesis of semibullvalene derivatives via Co\n <sub>2</sub>\n (CO)\n <sub>8</sub>\n -mediated cyclodimerization of 1,4-dilithio-1,3-butadienes\", Org. Chem. Front., vol. 1, pp. 130-134, 2014. https://doi.org/10.1039/c3qo00019b\n\n
    6. \n
  6. L.M. Jackman, A. Benesi, A. Mayer, H. Quast, E.M. Peters, K. Peters, and H.G. Von Schnering, \"The Cope rearrangement of 1,5-dimethylsemibullvalene-2,6- and 3,7-dicarbonitriles in the solid state\", Journal of the American Chemical Society, vol. 111, pp. 1512-1513, 1989. https://doi.org/10.1021/ja00186a064\n\n
    7. \n
  7. R.V. Williams, V.R. Gadgil, P. Luger, T. Koritsanszky, and M. Weber, \"The Search for Homoaromatic Semibullvalenes. 6.<sup>1</sup>X-ray Structure and Charge Density Studies of 1,5-Dimethyl-2,4,6,8-semibullvalenetetracarboxylic Dianhydride in the Temperature Range 123\u221215 K\", The Journal of Organic Chemistry, vol. 64, pp. 1180-1190, 1999. https://doi.org/10.1021/jo981703q\n\n
    8. \n
  8. H.S. Yu, X. He, and D.G. Truhlar, \"MN15-L: A New Local Exchange-Correlation Functional for Kohn\u2013Sham Density Functional Theory with Broad Accuracy for Atoms, Molecules, and Solids\", Journal of Chemical Theory and Computation, vol. 12, pp. 1280-1293, 2016. https://doi.org/10.1021/acs.jctc.5b01082\n\n
    9. \n
  9. S. Grimme, A. Hansen, S. Ehlert, and J. Mewes, \"r2SCAN-3c: A \"Swiss army knife\" composite electronic-structure method\", The Journal of Chemical Physics, vol. 154, 2021. https://doi.org/10.1063/5.0040021\n\n
    10. \n
  10. J. Chai, and M. Head-Gordon, \"Long-range corrected hybrid density functionals with damped atom\u2013atom dispersion corrections\", Physical Chemistry Chemical Physics, vol. 10, pp. 6615, 2008. https://doi.org/10.1039/b810189b\n\n
    11. \n
  11. H. Rzepa, \"CAZFUE01 MN15L/Def2-TZVPP => C2 symmetry => bis(homoaromatic) ? Gas phase\", 2026. https://doi.org/10.5281/zenodo.22009539\n\n
    12. \n
  12. H. Rzepa, \"CAZFUE01 => C2 symmetry => bis(homoaromatic) ? STABLE wavefunction? Gas phase\", 2026. https://doi.org/10.5281/zenodo.22009550\n\n
    13. \n
  13. H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state\", 2026. https://doi.org/10.5281/zenodo.22012011\n\n
    14. \n
  14. H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state Gas phase IRC\", 2026. https://doi.org/10.5281/zenodo.22012031\n\n
    15. \n
  15. H. Rzepa, \"ICILAI MN15L /Def2-TZVPP = TS (nu -31 cm-1). Gas phase\", 2026. https://doi.org/10.5281/zenodo.22009559\n\n
    16. \n
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Head-Gordon, \"Long-range corrected hybrid density functionals with damped atom\u2013atom dispersion corrections\", Physical Chemistry Chemical Physics, vol. 10, pp. 6615, 2008."},{"id":"https://doi.org/10.5281/zenodo.22009539","unstructured":"H. Rzepa, \"CAZFUE01 MN15L/Def2-TZVPP => C2 symmetry => bis(homoaromatic) ? Gas phase\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22009550","unstructured":"H. Rzepa, \"CAZFUE01 => C2 symmetry => bis(homoaromatic) ? STABLE wavefunction? Gas phase\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22012011","unstructured":"H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22012031","unstructured":"H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state Gas phase IRC\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22009559","unstructured":"H. Rzepa, \"ICILAI MN15L /Def2-TZVPP = TS (nu -31 cm-1). Gas phase\", 2026."}],"rid":"gtbbg-j6r70","summary":"I have in the past (around 2012 to be specific) taken an interest in a particular type of [3,3]sigmatropic pericyclic reaction called the semibullvalene rearrangement.,,. This system can apparently exhibit very long C-C bonds in the region of 2.1\u00c5, in which form it would be called a \"frozen\" transition state, also referred to a bis-homoaromatic [\u2026]","tags":["Crystal_structure_mining","Pericyclic","Reaction Mechanism"],"title":"How long can a C-C bond get? Semibullvalenes \u2013 genuine bis-homoaromatic molecules or are they [3,3] sigmatropic transition states.","updated_at":1787734490,"url":"https://www.ch.ic.ac.uk/rzepa/blog/?p=31787","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"family":"Crueger","given":"Jens"}],"blog":{"authors":[{"name":"Redaktion iRights.info"}],"community_id":"7d3b25fd-a4a8-4155-8e76-99d6be06706a","created":1694736000,"current_feed_url":null,"description":"Urheberrecht und kreatives Schaffen in der digitalen Welt","doi":"https://doi.org/10.59350/irights","favicon":"https://rogue-scholar.org/api/communities/7d3b25fd-a4a8-4155-8e76-99d6be06706a/logo","feed_format":"application/atom+xml","feed_url":"https://irights.info/feed/atom","filter":null,"generator":"Other","home_page_url":"https://irights.info/","issn":null,"language":"deu","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"irights","status":"active","subfield":"3308","title":"iRights.info","updated":1787730867,"use_api":false},"blog_name":"iRights.info","blog_slug":"irights","content_html":"

Im Bereich der Offenen Bildungsmaterialien sind Fragen rund um das Urheberrecht und K\u00fcnstliche Intelligenz ein Dauerbrenner. iRights.info hat als Kooperationspartnerin von OERinfo in den vergangenen Jahren zahlreiche Blogbeitr\u00e4ge hierzu beigesteuert. Der folgende Artikel gibt einen thematischen \u00dcberblick und soll als Orientierungshilfe dienen.\u00a0

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M\u00f6glichkeiten zur urheberrechtsfreien Nutzung von Bildungsinhalten

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KI und OER

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Creative-Commons-Lizenzen f\u00fcr OER-Materialien

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Creative-Commons-Module

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\u00c4nderungen und R\u00fccknahmen

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Besonderheiten und Herausforderungen

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Wo findet man Material?

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Ausblick f\u00fcr OER und das Urheberrecht

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Die K\u00fcnstliche Intelligenz fordert das Urheberrecht aktuell sehr heraus, und schafft damit auch im Kontext der Freien Bildungsmaterialien viele neue Fragen. Die Kooperation zwischen OERinfo und iRights.info wird daher auch in Zukunft spannende Themen bieten.

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Hinweis: Dieser Beitrag ist Teil einer Kooperation von\u00a0iRights.info, dem\u00a0Deutschen Bildungsserver\u00a0und\u00a0OERinfo. Der Text stammt von Jens Crueger, steht unter der Lizenz CC BY 4.0\u00a0und wurde zun\u00e4chst bei\u00a0OERinfo\u00a0ver\u00f6ffentlicht.

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Sie m\u00f6chten iRights.info unterst\u00fctzen?

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iRights.info\u00a0informiert und erkl\u00e4rt rund um das Thema \"Urheberrecht und Kreativit\u00e4t in der digitalen Welt\". Alle Texte erscheinen kostenlos und offen lizenziert.

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Wenn Sie m\u00f6gen, k\u00f6nnen Sie uns \u00fcber die\u00a0gemeinn\u00fctzige\u00a0Spendenplattform Betterplace\u00a0unterst\u00fctzen und daf\u00fcr eine Spendenbescheinigung erhalten. Betterplace akzeptiert PayPal, Bankeinzug, Kreditkarte, paydirekt oder \u00dcberweisung.

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Besonders freuen wir uns \u00fcber einen regelm\u00e4\u00dfigen Beitrag, beispielsweise als monatlicher Dauerauftrag.\u00a0F\u00fcr Ihre Unterst\u00fctzung dankt Ihnen herzlich der\u00a0gemeinn\u00fctzige iRights e.V.!

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DOI f\u00fcr diesen Text: \u00a0\u00b7 automatische DOI-Vergabe f\u00fcr Blogs \u00fcber The Rogue Scholar

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The post OER und das Urheberrecht \u2013 ein \u00dcberblick der Beitr\u00e4ge von iRights.info appeared first on iRights.info.

","doi":"https://doi.org/10.59350/cry6m-afz94","guid":"https://irights.info/?post_type=custom_artikel&p=32896","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787702400,"rid":"0xssx-9tw81","summary":"Im Bereich der Offenen Bildungsmaterialien sind Fragen rund um das Urheberrecht und K\u00fcnstliche Intelligenz ein Dauerbrenner. iRights.info hat als Kooperationspartnerin von OERinfo in den vergangenen Jahren zahlreiche Blogbeitr\u00e4ge hierzu beigesteuert. Der folgende Artikel gibt einen thematischen \u00dcberblick und soll als Orientierungshilfe dienen.","tags":["Allgemein","Bildung + OER","Generative KI","In Eigener Sache","K\u00fcnstliche Intelligenz"],"title":"OER und das Urheberrecht \u2013 ein \u00dcberblick der Beitr\u00e4ge von iRights.info","updated_at":1787731843,"url":"https://irights.info/artikel/urheberrecht-ueberblick-der-beitraege/32896","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"family":"Neylon","given":"Cameron","url":"https://orcid.org/0000-0002-0068-716X"}],"blog":{"authors":[{"name":"Cameron Neylon","url":"https://orcid.org/0000-0002-0068-716X"}],"community_id":"57bf5fb9-8f97-4a80-83d7-c6a1910c7e8e","created":1707696000,"current_feed_url":null,"description":"The online home of Cameron Neylon","doi":"https://doi.org/10.59350/cameronneylon","favicon":"https://rogue-scholar.org/api/communities/57bf5fb9-8f97-4a80-83d7-c6a1910c7e8e/logo","feed_format":"application/atom+xml","feed_url":"https://cameronneylon.net/feed/atom/","filter":null,"generator":"WordPress","home_page_url":"https://cameronneylon.net","issn":null,"language":"eng","license":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"cameronneylon","status":"active","subfield":"1802","title":"Science in the Open","updated":1787726875,"use_api":true},"blog_name":"Science in the Open","blog_slug":"cameronneylon","content_html":"

This was originally a script for a video I recorded for a meeting of the Australian Deans and Directors of Creative Arts (DDCA) group. It is addressed to those who are in institutional positions who need to make judgements about the qualities of research outputs in Humanities and Social Sciences with a particular focus on outputs that are “non-traditional” (actually often very “traditional” in their field!) or otherwise “not easily measurable by a STEM audience”.

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In my view there are two key roles for those specifically engaged in supporting those doing HSS research. The first is to advocate for financial systems that can support small and numerous research projects and the funders who want to support them. The second key role is to defend the diversity of research practices, outputs and impacts in HSS and to create a meaningful narrative around their qualities for institutional audiences.

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I'm going to focus on the second here, but I wanted to link both to underline the point that what is of value in HSS research is precisely its diversity, and its difference from the homogeneity and scale of conventional STEM research and its outputs. There is not infrequently a greater diversity of research outputs from single HSS groups, centres and departments than there is from entire faculties of science, engineering and medicine.

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That diversity is at the core of the value that HSS research and scholarship brings to the table. 

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Every social epistemology of knowledge from Latour to Longino via Merton, Ravetz, Kuhn and Fleck have at their heart the idea that the core is the negotiation of knowledge across boundaries, or between groups. This places diversity, of all kinds, at the heart of this process, and linked to it the institutional systems that keep it alive. Arguably it is the purpose of a university to support and bring into contact diverse approaches, experiences and ways of knowing.

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The issue of course is that managing that diversity is a challenge. At the scale of a university, systems are a necessity. Consistency is needed and economies of scale are real. Particularly in HSS but across other disciplines as well, it is impossible for any leader to be across the detail of how good every specific body of work is. If you believe in the argument for diversity then this as it should be – anything else would be a sign of insufficient diversity. That doesn't mean that leaders can't be effective at telling the stories about why diverse research matters. Nor does it mean that they can't make judgement calls on the distribution of resources. But it means those decisions are subjective and contextual. And that the evidence that supports them will be specific to each case.

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But that doesn't solve the problem either. So what are the pragmatic and principled approaches available to addressing this complexity? In my view the key lies in separating out the challenge into two parts, one relatively straightforward and immediately useful, the other more complex but I would argue ultimately tractable.

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An important, but oddly overlooked distinction in research evaluation and particularly technology discussions is the distinction between tracking outputs and evaluating them. There is often a tendency to lump these together and to imagine for example, that if scholarly books were better tracked then that would necessarily mean there would be improved citation data for them. The homogeneity of STEM research outputs means that issues with data coverage and completeness are often conflated to the question \"is it indexed\" using the presence of a specific journal in a specific database both as a reliable marker of quality itself but also of confidence in the quality and relevance of generally accepted performance data.

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So, although this is an oversimplification, in STEM the tracking of outputs is standardised and homogenous. You look it up in an index like Web of Science.

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In HSS, and particularly for creative works, the situation is far more complex. Institutions generally have very poor data on the scope and volume of creative outputs, or other forms of (so-called) \"non-traditional\" outputs. Work done by Niamh Quigley, within the COKI team (Quigley, 2022) showed generally used recording systems (systems like Symplectic, Pure and the like) tended to be poor at capturing aspects of research outputs important to creative researchers. Further, there was a tendency for the information that was manually inputted by researchers (that they care enough to type in!) to be stripped away as it made its way through institutional systems to the data warehouses used for high level analysis.

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From a systems perspective what is needed is systems that make it easy for creative practice researchers to register outputs, to flexibly record the evidence that they consider important about the qualities of these works, and to also make it easy for institutions in turn to gather that information up. Recent technical developments provide improved paths to making this happen.

\n\n\n\n

The Open Research Contributor and ID (ORCID) system provides a mechanism for researchers to authoritatively identify themselves, and to record outputs they have contributed to. In 2025 ORCID have increased the number of work types (Petro, 2025) to include a range relevant in humanities (including images, video, designs, sound and other creative works) as well as improving the mapping of some other relevant work types including reports. A researcher can choose what works they make visible, and thereby designate as \"research\". This is an important distinction for some creative workers. Institutions can then harvest those outputs without requiring further work from researchers.\u00a0

\n\n\n\n

ORCID doesn't solve all the problems though. Badly implemented as an institutional system it is yet another place creative researchers have to battle through manually adding their work while colleagues in STEM subjects have it all done for them by journal publishers. Critical to making this work is a commitment from you and your teams that ORCID be the only place researchers have to make sure their work is available and pulling that information from ORCID is an institutional responsibility.

\n\n\n\n

But that still leaves the manual input issue. There isn't – currently – a complete solution for that (although one – or several – could be built) but there is at least a solution that offers some additional value for creative researchers. Zenodo is a large scale repository, managed by CERN (yes the particle accelerator in Switzerland CERN) that offers a place for anyone to deposit research outputs. It provides a safe, publicly accessible platform from which researchers can showcase their work. It even allows for dark deposit for those creative researchers who need to restrict access to the core of their work for artistic, ethical or commercial reasons.

\n\n\n\n

Most importantly Zenodo provides DataCite DOIs and this means that – while you do have to manually put information into Zenodo – that information can automatically flow through to ORCID. One place to input the information and then it can flow to the other places it needs to be.

\n\n\n\n

This flow of information should be the case for any repository that integrates with DataCite (or Crossref) to provide DOIs. Zenodo is large scale and flexible, but there can be an argument for specialist repositories. I am generally sceptical of the value of creating new local repositories, whether at institutions or nationally, but the key questions to ask of any repository are \"does it integrate with DOI providers\" and \"does it provide the recording functionality creative research practitioners need\"? That flexibility is key and Zenodo has some strengths here that can also help us to address, if not yet fully solve, the second problem.\u00a0

\n\n\n\n

Creative practice researchers know the reasons that their work is important, and can help provide evidence of that. But that evidence is highly diverse. 

\n\n\n\n

I know the pressures that institutional leaders face to articulate a comparative quantitative value of research outputs to the rest of the university. And I would argue that we nonetheless need to collectively hold the line that this makes no sense. If you value a diversity of research and researchers, you can't protect that diversity by homogenising the way that value is measured. 

\n\n\n\n

But that doesn't mean we can't articulate value. It doesn't mean we can't compare how disparate research projects and outputs achieve specific goals. It just means, in the best tradition of HSS scholarship, that the evidence that we use is contextual. That it is diverse.

\n\n\n\n

And here is how repositories like Zenodo can help. Where they support the creation of packages of work, researchers can bundle up the work itself with evidence of its value and impact. This will start unstructured, but over time, and in collaboration with research communities it will be possible to develop some standards. For specific cases. Where appropriate. This might mean giving some background on the gallery that invited an exhibition, the footfall or an audience survey. It might be details of the film festival that selected a documentary for screening, or audience numbers when it was syndicated or broadcast. It might be structured in a particular way to make it easier to process (or even generate). But the key is to build on systems that always allow for the flexibility of a narrative statement that allows for the flexibility that research statements already provide. 

\n\n\n\n

This workflow places researchers in control, gives them flexibility they need to provide access and to evidence the value of their work. It provides a single point of entry from which communities, institutions, and others can draw in the data to help track those outputs and collate the evidence of their value. It is not controlled by corporate interests but by academic communities. It is not subject to the funding whims of one national government but an international set of consortia.

\n\n\n\n

Perhaps best of all, this is an area where the humanities and social sciences can lead. It solves a problem by putting researchers in control while supporting institutional needs. It helps and simplifies monitoring while offering a path to gathering more sophisticated evidence to tell better stories. These are not problems that are restricted to HSS, but you could argue that much of STEM evaluation has lost its way, focusing on numbers instead of substance, journal lists instead of journal content, impact factors instead of actual impact. This recontextualisation, and re-situation is where humanities and social sciences scholars, and leadership can show a way to better forms of evaluation.

\n\n\n\n

References

\n\n\n\n

","doi":"https://doi.org/10.59350/gtm23-qy713","guid":"https://cameronneylon.net/?p=20122","language":"en","license":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","published_at":1787702400,"reference":[{"id":"https://info.orcid.org/new-work-types/","unstructured":"Petro, J. 2025. ORCID and Humanities: Celebrating the New Year with New Work Types. ORCID Blog. ORCID. ."},{"id":"https://doi.org/10.5281/zenodo.6501506","unstructured":"Quigley, N. 2022. Increasing the visibility of grey literature: Project report (Version 1). Zenodo. ."}],"rid":"h59g6-h3b89","summary":"This was originally a script for a video I recorded for a meeting of the Australian Deans and Directors of Creative Arts (DDCA) group.","tags":["Institution","Peer Review","Research-evaluation"],"title":"Tracking, Valuing and Evaluating the Diversity of HSS Research Outputs","updated_at":1787731729,"url":"https://cameronneylon.net/blog/tracking-valuing-and-evaluating-the-diversity-of-hss-research-outputs/","version":"v1"}},{"document":{"authors":[{"affiliation":[{"id":"https://ror.org/05a28rw58","name":"ETH Zurich"}],"contributor_roles":[],"family":"Rutz","given":"Adriano","url":"https://orcid.org/0000-0003-0443-9902"}],"blog":{"authors":[{"name":"Adriano Rutz","url":"https://orcid.org/0000-0003-0443-9902"}],"community_id":"9d85a476-b411-4d80-89d5-500bb0f3750d","created":1780876800,"current_feed_url":null,"description":"Personal website of Adriano Rutz","doi":"https://doi.org/10.59350/adafede","favicon":"https://rogue-scholar.org/api/communities/9d85a476-b411-4d80-89d5-500bb0f3750d/logo","feed_format":"application/feed+json","feed_url":"https://adafede.github.io/posts.json","filter":null,"generator":"Other","home_page_url":"https://adafede.github.io","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":null,"slug":"adafede","status":"active","subfield":"1312","title":"Adriano Rutz","updated":1787700179,"use_api":null},"blog_name":"Adriano Rutz","blog_slug":"adafede","content_html":"

I have finally opened a Posts section on my website! Every post should now automatically get a DOI.

\n

This is something I have wanted to do for a long time, largely inspired by the tireless and consistent example set by Egon Willighagen (Willighagen 2024b, 2024a, 2025).

\n

It was today's post of (Fenner 2025) that finally motivated me to look into it again. That led me down a productive rabbit hole to set up Rogue Scholar: first landing on (Csefalvay 2023)'s excellent guide, and then (Fruehwald 2025)'s clear write-up, both of which made the process of integrating Rogue Scholar into a Quarto-based site surprisingly smooth.

\n

All the changes are documented in the following commit:

\n

https://github.com/Adafede/adafede.github.io/commit/bc2dfe6f

\n

If you care about attribution, long-term archiving, DOIs and metadata, I highly recommend looking into Rogue Scholar.

\n

Edit (1): I realized that integrating CiTO could be a significant enhancement. With some effort (and thanks again to Egon), I managed to implement a working solution for the HTML and PDF outputs, see (Willighagen 2023). However, the solution for the XML feed still feels suboptimal.

\n

Edit (2): After some help from Egon and Martin, I could improve my feed with correct CiTO annotations and their cool custom json feed, see: https://adafede.github.io/posts.json!

\n
\n

References

\n
\n
\nCsefalvay, Chris von. 2023. Auto-DOI for Quarto Posts via Rogue Scholar. http://dx.doi.org/10.59350/5hxdg-fz574.\n [cito:obtainsBackgroundFrom]
\n
\nFenner, Martin. 2025. Rogue Scholar Citation Tracking Launches to Production. http://dx.doi.org/10.53731/zyg15-qv911.\n [cito:obtainsBackgroundFrom]
\n
\nFruehwald, Josef. 2025. Setting up Rogue Scholar. http://dx.doi.org/10.59350/3fp6d-e6z90.\n [cito:usesMethodIn]
\n
\nWillighagen, Egon. 2023. \"Two Years of Explicit CiTO Annotations.\" Journal of Cheminformatics 15 (1). https://doi.org/10.1186/s13321-023-00683-2.\n [cito:usesMethodIn]
\n
\nWillighagen, Egon. 2024a. FAIR Blog-to-Blog Citations. http://dx.doi.org/10.59350/er1mn-m5q69.\n [cito:cites]
\n
\nWillighagen, Egon. 2024b. GoatCounter, Rogue Scholar and More New Things. http://dx.doi.org/10.59350/8x2f1-h6d21.\n [cito:cites]
\n
\nWillighagen, Egon. 2025. Blog Updates. http://dx.doi.org/10.59350/cf885-kee54.\n [cito:cites]
\n
\n
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Citation

BibTeX citation:
@online{rutz2025,\n  author = {{Adriano Rutz}},\n  title = {Open {Science} {Upgrade:} {Adding} {Blog} {Posts} to My\n    {Website} and {Linking} to {Rogue} {Scholar}},\n  date = {2025-08-04},\n  url = {https://adafede.github.io/posts/2025-08-04_rogue_scholar.html},\n  doi = {10.59350/yckwd-9vm79},\n  langid = {en}\n}\n
For attribution, please cite this work as:
\nAdriano Rutz. 2025. \"Open Science Upgrade: Adding Blog Posts to My\nWebsite and Linking to Rogue Scholar.\" August 4. https://doi.org/10.59350/yckwd-9vm79.\n
","doi":"https://doi.org/10.59350/yckwd-9vm79","guid":"https://doi.org/10.59350/yckwd-9vm79","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1754265600,"reference":[{"id":"https://doi.org/10.59350/5hxdg-fz574","unstructured":"[cito:obtainsBackgroundFrom]"},{"id":"https://doi.org/10.53731/zyg15-qv911","unstructured":"[cito:obtainsBackgroundFrom]"},{"id":"https://doi.org/10.59350/3fp6d-e6z90","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.1186/s13321-023-00683-2","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.59350/er1mn-m5q69","unstructured":"[cito:cites]"},{"id":"https://doi.org/10.59350/8x2f1-h6d21","unstructured":"[cito:cites]"},{"id":"https://doi.org/10.59350/cf885-kee54","unstructured":"[cito:cites]"}],"rid":"9hzx0-g6543","summary":"I have finally opened a Posts section on my website! Every post should now automatically get a DOI.","tags":["Open Science"],"title":"Open Science Upgrade: Adding Blog Posts to my Website and Linking to Rogue Scholar","updated_at":1787720776,"url":"https://adafede.github.io/posts/2025-08-04_rogue_scholar.html","version":"v1"}},{"document":{"authors":[{"affiliation":[{"id":"https://ror.org/05a28rw58","name":"ETH Zurich"}],"contributor_roles":[],"family":"Rutz","given":"Adriano","url":"https://orcid.org/0000-0003-0443-9902"}],"blog":{"authors":[{"name":"Adriano Rutz","url":"https://orcid.org/0000-0003-0443-9902"}],"community_id":"9d85a476-b411-4d80-89d5-500bb0f3750d","created":1780876800,"current_feed_url":null,"description":"Personal website of Adriano Rutz","doi":"https://doi.org/10.59350/adafede","favicon":"https://rogue-scholar.org/api/communities/9d85a476-b411-4d80-89d5-500bb0f3750d/logo","feed_format":"application/feed+json","feed_url":"https://adafede.github.io/posts.json","filter":null,"generator":"Other","home_page_url":"https://adafede.github.io","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":null,"slug":"adafede","status":"active","subfield":"1312","title":"Adriano Rutz","updated":1787700179,"use_api":null},"blog_name":"Adriano Rutz","blog_slug":"adafede","content_html":"

Five years ago, LOTUS (Rutz et al. 2022) started as a small attempt to cultivate the flow of chemical knowledge, in the same way we study how metabolites flow through living systems, rather than to build yet another database.

\n

The idea was simple. Natural products data should be open, structured, reusable, and belong to everyone.

\n

Like many community-driven efforts, LOTUS had bursts of activity, long pauses, and years of invisible maintenance. From the outside, silence can look like disappearance. From the inside, it usually means people are still doing the work; slowly, carefully, and often without announcements.

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\n

From isolated datasets to global outreach

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The early focus of LOTUS was necessarily inward: assembling data, cleaning records, releasing versions. We built a website, curated entries, and archived releases.

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But we slowly realized something uncomfortable: data stored in a repository, even a good one, does not automatically live.

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Archiving on Zenodo (https://zenodo.org/communities/the-lotus-initiative) was the right thing to do, but archived data is mostly silent data. It waits to be discovered, and versioning remains labor-intensive.

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What we really needed were entry points where people already were.

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Wikipedia , Wikidata , and Scholia building on top of it are not dissemination platforms in the classical sense. They are circulatory systems. They persist because communities maintain them.

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The Scholia Chemistry preprint (Willighagen et al. 2025) co-authored with Egon , Denise , Daniel , and Finn belongs to this continuity. It does not introduce a new platform. It offers a lens for communities to see what they already collectively know.

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Making knowledge visible: the Wikipedia P703 module

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\n

Knowledge needs channels, not just reservoirs.

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\n

One important step was enabling Wikipedia articles and infoboxes to directly access found in taxon (P703) relationships from Wikidata in an efficient way.

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This sounds like a small technical detail. It is not.

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The idea had circulated quietly for years, in hallway conversations, chats, and conferences. I also mentioned it during the WikiCite 2025 conference last August, but it took time before conditions were right. Infrastructure work rarely happens on schedule. It almost never happens on stage. It happens in version histories, talk pages, and tiny edits that fix one Lua bug, enabling thousands of articles to improve forever.

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Once data is in Wikidata, it can flow into thousands of chemical articles, in dozens of languages, without duplication or translation overhead. It becomes visible to non-experts, students, and readers who will never see a database interface. This is how open data becomes public knowledge.

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These modules are now available on multiple Wikipedias:

\n\n

If you speak another language, feel free to copy them and increase their use.

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Initially, I tried to reuse existing modules, and quickly learned why module reuse across Wikipedias is famously difficult. Each wiki evolves its own ecosystem of dependencies, conventions, and technical debt. So the modules were written fully contained, independent of language-specific infrastructure. Only lines that need to be changed are the language-specific translations at the top of the module, trying to follow 18n.

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These modules are not a new website or a new interface. They are simply better plumbing.

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\n
\n

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Screenshot of the P703 module on English Wikipedia
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\n
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By default, only 5 organisms are shown, keeping the text clean and readable. But the magic is in how the module handles the rest: each taxon links to its Wikipedia article, and if no article exists in the current language, the module gracefully redirects to an equivalent page in another wiki. A beautiful example of this is war for Quassia africana.

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Reaching non-experts

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Not everyone wants to learn SPARQL.

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\n

I have heard this sentiment countless times. Regardless of personal preferences, if we want the data to truly live, it must reach as many people as possible.

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Small tools like the LOTUS Wikidata Explorer help lower that barrier. It is imperfect. It is still growing. But it already allows chemists, curators, and students to access and export data in formats they can actually use.

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The principle is simple: knowledge only flows when it reaches people. The data must be seen, explored, and reused. Only then does it fulfill its purpose.

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\n
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Screenshot of the LOTUS Wikidata Explorer interface
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On a more technical note, the LOTUS Wikidata Explorer leverages the powerful IDSM endpoint (Galgonek and Vondr\u00e1\u0161ek 2021), which allows for chemical similarity searches thanks to Sachem (Kratochv\u00edl et al. 2018). Its speed for large-scale queries could never have been reached without QLever (Bast and Buchhold 2017), and chemical depictions come from CDK Depict.

\n

It returns structured metadata for traceability and reproducibility, together with hashes that uniquely identify the query and its results. It can be queried programmatically via simple API calls, for example ?taxon=Gentianaceae or ?smiles=c1ccccc1&formula_filter=true&f_state=required. It works directly in the browser without requiring heavy dependencies, almost everything works out of the box.

\n

Alternatively, users can take advantage of a local version, for example to extract a small, personal knowledge graph in TTL format, or to export all or selected LOTUS data in more chemistry-friendly formats such as JSON or CSV, ready for analysis, visualization, or integration into other workflows.

\n

For example, to export a complete or filtered snapshot locally:

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uvx \\\n  --from \\\n  git+https://github.com/adafede/marimo \\\n  lotus_wikidata_explorer \\\n  export \\\n  --taxon \"*\" \\   # to get all taxa, else \"Gentianaceae\", for example\n  --format csv \\  # also supports json, ttl\n  --output 20260119_lotus.csv.gz \\\n  --compress \\\n  --verbose
\n
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And if you are curious where halogenated compounds appear most often, you can simply ask:

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xan dedup 20260119_lotus.csv.gz \\\n  --select compound_inchikey,molecular_formula,taxon_name | \\\n  xan select compound_inchikey,molecular_formula,taxon_name | \\\n  xan filter \"contains(molecular_formula, 'Br') or\n              contains(molecular_formula, 'Cl') or\n              contains(molecular_formula, 'F') or\n              contains(molecular_formula, 'I')\" | \\\n  xan filter '!contains(molecular_formula, \"Fe\")' | \\\n  xan freq -s taxon_name | \\\n  xan hist -l value -R
\n
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Histogram for taxon_name (bars: 11, sum: 11,604, max: 10,060):\n\nStreptomyces            |   374   3.22%|\u25a0\u25a0\u25a0\u25a0                                                                                                   |\nLaurencia dendroidea    |   314   2.71%|\u25a0\u25a0\u25a0\u25a0                                                                                                   |\nLaurencia obtusa        |   184   1.59%|\u25a0\u25a0                                                                                                     |\nPseudoceratina purpurea |   112   0.97%|\u25a0\u25a0                                                                                                     |\nAplysia dactylomela     |    99   0.85%|\u25a0\u25a0                                                                                                     |\nNostoc                  |    99   0.85%|\u25a0\u25a0                                                                                                     |\nLaurencia nipponica     |    95   0.82%|\u25a0                                                                                                      |\nPortieria hornemannii   |    94   0.81%|\u25a0                                                                                                      |\nLyngbya majuscula       |    88   0.76%|\u25a0                                                                                                      |\nChaetomium globosum     |    85   0.73%|\u25a0                                                                                                      |\n<rest>                  |10,060  86.69%|\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0|
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Making flow reliable: curation and standards

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At some point, flow only runs if it is maintained.

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As I do not post as often as I probably should, here are some other pointers to related work and discussions from the past months, for those who want to follow the flow a bit further:

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Blue Obelisk

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Reactions flow

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Recently, I also contributed to improving how chemical reactions are modeled in Wikidata.

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Previously, many reactions were modeled as instances of \"chemical reaction\", which violated disjointness, see (Do\u01e7an and Patel-Schneider 2025).

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The introduction of type of chemical reaction now allows reactions to be classified more precisely, while preserving their hierarchy using subclass of.

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Wikifunctions

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Out of curiosity, I also made a small contribution to chemistry-related functions in Wikifunctions: Z30950. It validates CAS Registry Numbers. It does one thing, and it does it reliably.

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It is tiny. But it is a seed.

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Looking forward: flowing knowledge, flowing metabolites

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Projects like Wikifunctions and Abstract Wikipedia point to the next phase of open knowledge: knowledge that is not only stored, but executed, reused, and recombined.

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A global, open metabolomics knowledge graph is slowly taking shape, one where chemical structures, organisms, reactions, and evidence can finally be traced together.

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LOTUS is no longer an initiative. It is one contributor among many in that graph.

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If you edit Wikipedia, curate Wikidata, maintain a SPARQL endpoint, write a template, review a module, or fix a tiny detail no one will notice, thank you. This work only matters because you are here.

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References

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\nBast, Hannah, and Bj\u00f6rn Buchhold. 2017. \"QLever: A Query Engine for Efficient SPARQL+text Search.\" Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17, November, 647\u201356. https://doi.org/10.1145/3132847.3132921.\n [cito:usesMethodIn]
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\nDo\u01e7an, Ege Atacan, and Peter F. Patel-Schneider. 2025. \"Disjointness Violations in Wikidata.\" In Knowledge Graphs and Semantic Web. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-81221-7_18.\n [cito:citesAsRecommendedReading]
\n
\nGalgonek, Jakub, and Ji\u0159\u00ed Vondr\u00e1\u0161ek. 2021. \"IDSM ChemWebRDF: SPARQLing Small-Molecule Datasets.\" Journal of Cheminformatics 13 (1). https://doi.org/10.1186/s13321-021-00515-1.\n [cito:usesMethodIn]
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\nKratochv\u00edl, Miroslav, Ji\u0159\u00ed Vondr\u00e1\u0161ek, and Jakub Galgonek. 2018. \"Sachem: A Chemical Cartridge for High-Performance Substructure Search.\" Journal of Cheminformatics 10 (1). https://doi.org/10.1186/s13321-018-0282-y.\n [cito:usesMethodIn]
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\nRutz, Adriano, Maria Sorokina, Jakub Galgonek, et al. 2022. \"The LOTUS Initiative for Open Knowledge Management in Natural Products Research.\" eLife 11 (May). https://doi.org/10.7554/elife.70780.\n [cito:cites]
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\nWillighagen, Egon. 2025. August. https://doi.org/10.59350/krw9n-dv417.\n [cito:citesAsRecommendedReading]
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\nWillighagen, Egon, Denise Slenter, Adriano Rutz, Daniel Mietchen, and Finn Nielsen. 2025. Scholia Chemistry: Access to Chemistry in Wikidata. May. https://doi.org/10.26434/chemrxiv-2025-53n0w.\n [cito:cites]
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Citation

BibTeX citation:
@online{rutz2026,\n  author = {{Adriano Rutz}},\n  title = {Cultivating {Knowledge} {Flow} in {Open} {Chemistry}},\n  date = {2026-01-20},\n  url = {https://adafede.github.io/posts/2026-01-20_chem_flow.html},\n  doi = {10.59350/sk00y-3gh44},\n  langid = {en}\n}\n
For attribution, please cite this work as:
\nAdriano Rutz. 2026. \"Cultivating Knowledge Flow in Open\nChemistry.\" January 20. https://doi.org/10.59350/sk00y-3gh44.\n
","doi":"https://doi.org/10.59350/sk00y-3gh44","guid":"https://doi.org/10.59350/sk00y-3gh44","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1768867200,"reference":[{"id":"https://doi.org/10.1145/3132847.3132921","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.1007/978-3-031-81221-7_18","unstructured":"[cito:citesAsRecommendedReading]"},{"id":"https://doi.org/10.1186/s13321-021-00515-1","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.1186/s13321-018-0282-y","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.7554/elife.70780","unstructured":"[cito:cites]"},{"id":"https://doi.org/10.59350/krw9n-dv417","unstructured":"[cito:citesAsRecommendedReading]"},{"id":"https://doi.org/10.26434/chemrxiv-2025-53n0w","unstructured":"[cito:cites]"}],"rid":"80nkb-cq953","summary":"Five years ago, LOTUS (Rutz et al. 2022) started as a small attempt to cultivate the flow of chemical knowledge, in the same way we study how metabolites flow through living systems, rather than to build yet another database.","tags":["Chemistry","LOTUS","Open Science","Wikidata"],"title":"Cultivating Knowledge Flow in Open Chemistry","updated_at":1787701339,"url":"https://adafede.github.io/posts/2026-01-20_chem_flow.html","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"family":"Richardson","given":"Reese"}],"blog":{"authors":null,"community_id":"40570e0b-b289-4145-9c60-6fb881efaa45","created":1721779200,"current_feed_url":null,"description":"Case studies in scientific reproducibility","doi":"https://doi.org/10.59350/reeserichardson","favicon":"https://rogue-scholar.org/api/communities/40570e0b-b289-4145-9c60-6fb881efaa45/logo","feed_format":"application/atom+xml","feed_url":"https://reeserichardson.blog/feed/atom","filter":null,"generator":"WordPress.com","home_page_url":"https://reeserichardson.blog","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"reeserichardson","status":"active","subfield":"1802","title":"Reese Richardson","updated":1787662200,"use_api":false},"blog_name":"Reese Richardson","blog_slug":"reeserichardson","content_html":"

On May 17, 2026, Sholto David identified one fabricated image presented as validation data in Thermo Fisher's antibody catalog. By May 28, we had identified more than 100 fabricated images, which expanded to more than 450 images in Thermo Fisher's catalog and one in Abcam's catalog by June 3 (see my previous blog post). We set up a Zenodo repository to collect all these instances of apparent manipulation of antibody validation data and a form for others to report suspicious images in vendor's antibody validation data that they had found themselves.

\n

Understandably, this revelation prompted considerable outrage among biomedical scientists, as reported by Nature, Chemistry World, The Scientist, GenomeWeb and others. Phillip Broadwith, Business editor for Chemistry World, summarizes: \"The discovery of extensive manipulation in Western blot images used by laboratory supply giant Thermo Fisher Scientific as verification data for antibody reagents has led to a serious breakdown of trust between the company and its customers.\"

\n

This update is to say that this newfound distrust should probably extend to a good fraction of the research antibody industry at large. Our repository now contains 18,943 images presented as validation data for 17,495 unique antibody products sold by 15 different vendors1. In order of discovery, these vendors are:

\n\n

Below, I summarize the findings for each company and provide a short postscript detailing my own opinion about what should happen from here. Note that while I have tried to document as many instances of apparent manipulation as possible, the figures shown here do not represent a complete audit of each company's catalog. Moreover, many images I've reviewed look as though they may have been manipulated, but are too low-resolution for me to offer a confident opinion. I've elected not to include these images in the repository. For all of these images, the best way to know if falsification has occurred is to inspect the original, high-resolution images, which may or may not be available, even to the vendors themselves.

\n

For these reasons, a vendor having a larger or smaller number of manipulated images documented here should not be interpreted as an indication that it has a larger or smaller manipulation problem than the other companies listed here. All of these companies have some level of manipulated images in their catalogs and they should each comprehensively and transparently audit the images in their respective catalogs. Finally, if a vendor is not present here, it is not an indication that their catalog is free of manipulation.

\n

Hundreds of these problematic images were first identified by others, including Sholto David, Elisabeth Bik, Javeria Nishtar, Maxwell Marley, Marvin Bader, HKADolan, Bryan Heit and several community members that prefer to remain anonymous. Many other community members submitted images that they found suspicious, but were too low-resolution for me to make a confident determination and include them in the repository. I want to thank all these people for taking the time to document and report their findings. I encourage readers to report any suspicious validation data they notice in vendor catalogs here.

\n

Vendors frequently use the same validation images as one another, probably reflecting private labeling

\n

It is clear that many of these vendors are using the same images as one another for their own versions of the same product. For instance, this HAS1 antibody from Thermo Fisher uses the same Western blot image as similar products from Millipore Sigma, Novus (R&D Systems) and Boster Bio. I only noticed this because the image used for the HAS1 antibody has the exact same pattern of background noise as a different Western blot image used for a different antibody also sold by Thermo Fisher, implying that at least one of these images is fabricated.

\n
\"\"
My annotation of the problematic images described above.
\n

At least six companies (Thermo Fisher, Abcam, LSBio, Antibodies.com, G-Biosciences and GeneTex) present a Western blot using the exact same \"background pattern A\" as thousands of other antibody products. I described background pattern A in my previous blog post.

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Thermo Fisher's catalog all featuring \"background pattern A\".
\n

If they aren't using the exact same images as one another, different companies will often use images that are so stylistically similar that it is clear that they originated from the same art studio laboratory.

\n
\"\"
Three Western blot validation images from LSBio, Origene and Thermo Fisher, all of which feature a background that has apparently been painted in. Note that the images all feature a two-lane Western blot without lane labels and feature the same molecular weight markers written in the same italic font at the same molecular weights. These images are among hundreds from multiple vendors featuring the same style, many of which also feature signs of apparent painting.
\n

Identical images across multiple vendors probably reflect the industry practicing private labeling, where one manufacturer produces a product that they then sell to other companies to market and sell under their own branding. It appears that the original manufacturer of these antibodies also passed along their validation data to the final vendor, who then placed them on their website.

\n

Thermo Fisher Scientific (5,580 images across 4,819 products)

\n

Thermo Fisher Scientific, headquartered in Waltham, Massachusetts, is probably the world's largest supplier of laboratory equipment and reagents and was the first company that was noted to have presented fabricated images as validation data. In response to the public outrage, Thermo Fisher released a baffling 15-point FAQ wherein they promise an investigation, but repeatedly state that \"antibody images may have been optimized for presentation and clarity on the website\". Shortly after, they revised their FAQ to just seven points. To the carefully-worded question \"Did Thermo Fisher manipulate or fabricate antibody data?\", they emphatically respond:

\n
\n

No. The Company fully stands by the data and underlying science.\u00a0 We are confident in the quality of the products within our antibody catalog and our performance guarantee is valid for products purchased directly from Thermo Fisher Scientific or any of our authorized distributors. For further information, please refer to the Invitrogen\"\u2122\" antibody performance guarantee.

\n
\n

Note that this answer only claims that Thermo Fisher itself did not manipulate or fabricate antibody data, which leaves the company room to offer a clean mea culpa if their review finds that the images were manipulated by a third party. Regardless of which party is responsible for the manipulation, Thermo Fisher used these images to market their products to scientists hungry for antibodies that actually perform as advertised.\u00a0

\n

Around the same time that their FAQ was revised, Thermo Fisher and added a disclaimer to all antibody product pages in small gray type:

\n
\n

Please note: We are reviewing Western blot images included in the antibody testing data in our catalog, including those provided by third parties. Unless expressly labeled or annotated as \"raw-unedited\", Western blot images included in the antibody testing data in our catalog may have been edited, optimized or otherwise adjusted for presentation.

\n
\n

Thus far, I have not seen any images in Thermo Fisher's catalog that are labeled as \"raw-unedited\". Note that Thermo Fisher has not committed to making the findings of their investigation public.

\n

More than a thousand newly-documented images from Thermo Fisher's catalog contain artefacts of \"painting\", where someone presumably has brushed over some undesirable image features in Photoshop or a similar program (some highlights below).

\n
\"\"
A Western blot image presented as validation data for a Thermo Fisher alpha-II spectrin antibody.\u00a0
\n
\"\"
An immunocytochemistry image presented as validation data for a Thermo Fisher XBP1 antibody.
\n
\"\"
A Western blot image presented as validation data for a Thermo Fisher PCMT1 antibody.
\n
\"\"
An immunofluorescence image presented as validation data for a Thermo Fisher APC2 antibody.
\n

Dozens of other images feature duplicated regions of background noise.

\n
\"\"
A Western blot image presented as \"Advanced Verification\" data for a Thermo Fisher CRMP2 antibody.
\n

Thousands of other images feature the same background patterns with the bands repositioned to correspond to the expected molecular weight, as in the previously-documented \"background pattern A\" and \"background pattern B\".

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Thermo Fisher's catalog all featuring \"background pattern C\"
\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Thermo Fisher's catalog all featuring \"background pattern D\", which appears to be a two-lane version of \"background pattern C\".
\n

If 450 images was not enough to convince Thermo Fisher that this is not data they should \"fully stand behind\", maybe 5,000 images will be.

\n
An aside about Thermo Fisher's \"quotations\"
\n

Another way to stoke confidence in buyers that an antibody works as advertised is to show them that other scientists have successfully used it. To that end, most antibody vendors show \"citations\" and \"references\" on product pages, listing published articles wherein the authors state that they used the antibody in their experiments. These product citations are compiled by services like CiteAb, the Antibody Registry and BenchSci. Thermo Fisher's product pages collect citations to the product and provide a short quotation from each describing how the reagent was used.

\n
\"\"
The References section on Thermo Fisher's product page for a XBP1 antibody.
\n

I was alerted to a problem with these citations by a post by Sander Kersten, who complained that:

\n
\n

[Thermo Fisher] is quoting a sentence from our manuscript, written 25 years ago, indicating that we used their antibody. However, we didn't, and the quote is a total fabrication.

\n
\n
\"\"
The reference to Kersten's publication shown on Thermo Fisher's product page for an ANGPTL4 antibody. Note the quotation marks around the apparent excerpt. This reference has since been removed.
\n

The product page makes it appear as if it is quoting directly from Kersten et al. (2000): \"PA1-1053 was used in western blot to investigate the function of PPAR alpha and characterize FIAF during fasting\". The actual relevant quotation from Kersten et al. is \"[t]he polyclonal antibody used was directed against the epitope CQGPKGKDAPFKDSE in the N-terminal region of FIAF. The peptide affinity-purified antibody was generated in rabbit and ordered via Eurogentec's customized antibody production service.\" In other words, Kersten et al. never claim to use the Thermo Fisher product in question. The antibody they used binds the same epitope (amino acid sequence) as PA1-1053 claims, but the authors explicitly state that it came from a different manufacturer.\u00a0

\n

In fact, every single apparent quotation from a product reference on Thermo Fisher's site is not actually from the reference manuscript. For instance, the same product page that misquoted Kersten et al. also makes it appear as if it is quoting directly from Choudhuri et al. (2021): \"PA1-1053 was used in Western Blotting to gain insight into the mechanisms that result in such changes by Tempol in female C3H mice\". The actual relevant quotation from Choudhuri et al. reads \"[f]ollowing transfer to nitrocellulose, samples were probed with primary antibodies ALDH1A1 (ab52492) from Abcam (Waltham, MA), ANGPTL4/FIAF (PA1-1053) from Thermo Fisher Scientific (Waltham, MA) followed by rabbit secondary antibody from Santa Cruz Biotechnology (Dallas, TX), and were visualized by chemiluminescence (PerkinElmer; Billerica, MA)\".

\n

I believe these summaries are AI-generated, but they are clearly presented (in quotation marks, no less) as if they are direct quotations from the manuscript. While product pages on Thermo Fisher are littered with buttons prompting users to \"Ask AI about this product\", users are given no indication that these quotations are AI-generated nor that they are not actually quotations. Every Reference section does have an \"AI-generated summary\" at the top, however, this part is not presented in quotation marks and is clearly disclaimed as being AI-generated, unlike the references themselves.

\n

Moreover, many of these summaries are inaccurate, such as the reference to Kersten et al.! I ran spot-checks of 15 references from another antibody (MA5-14520, Ki-67 Recombinant Rabbit Monoclonal Antibody clone SP6) and found 4 listed references (1, 2, 3, 4) that state that they used a rabbit antibody from Thermo Fisher (or one of the brands acquired by Thermo Fisher) but don't actually specify that it was MA5-14520. Thermo Fisher currently sells 54 antibodies targeting Ki-67 with rabbits as the host organism.

\n

Abcam (185 images across 115 products)

\n

Abcam is based in Cambridge, UK and was acquired by the Danaher Corporation, headquartered in Washington, DC, in 2023. We previously found just one instance of image manipulation in Abcam's catalog (an appearance by \"background pattern A\"). After making this public, Abcam issued a short statement to The Scientist and wordlessly removed the image from the antibody's product page. The product remains for sale.

\n

The newly-documented manipulations contain a lot of patchwork painting of background noise in Western blots, as well as several dozen appearances of background patterns C and D.

\n
\"\"
A Western blot image presented as validation data for an Abcam HSP90 alpha/beta antibody.
\n
\"\"
A Western blot image presented as validation data for an Abcam ADSS2 antibody.
\n

Novus Biologicals / R&D Systems (263 images across 171 products)

\n

Novus Biologicals is a brand owned by R&D Systems, a brand of Bio-Techne, based in Minneapolis, Minnesota. Bio-Techne announced in June that they would be acquired by Merck KGaA, headquartered in Darmstadt, Germany (not to be confused with the American company Merck & Co., Inc.). The images flagged in our repository mostly feature background pattern C and background pattern D.

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from R&D System's catalog all featuring \"background pattern D\". Although the images are heavily compressed, the pattern is distinguishable by a unique set of \"freckles\" in the gel (for instance, see the three dots on the left edge of the image just above the 55 kDa marker).
\n

Proteogenix (362 images across 362 products)

\n

Proteogenix is headquartered in Schiltigheim, France. An anonymous community member noticed that several images in Proteogenix's catalog use the exact same background pattern (which I've called \"background pattern E\"). According to this person, they alerted Proteogenix to the first handful of problematic images that they noticed. Proteogenix apparently answered this courtesy by silently removing the offending images from the catalog (note that since the catalog pages were not previously archived, I cannot independently verify if Proteogenix did indeed remove these images after the community report). This person went on to document 200 additional occurrences of the background pattern in Proteogenix's catalog, after which I found more than 150 more.

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Proteogenix's catalog all featuring \"background pattern E\". Notice that the single band in the \"R\" lane also appears to be repeatedly reused.
\n

Origene (2,236 images across 1,959 products)

\n

Origene is headquartered in Rockville, Maryland. Most of their newly-documented image manipulations contain evidence of background painting.\u00a0

\n
\"\"
A Western blot image presented as validation data for an Origene SMAD1 antibody.
\n
\"\"
A Western blot image presented as validation data for an Origene SERPINB1 antibody.
\n
\"\"
An immunofluorescence image presented as validation data for an Origene HRASLS3 antibody.
\n
\"\"
Three Western blot images used by Origene that share the same repetitive background. One image was also used by R&D Systems for a Novus Biologicals antibody.
\n

Even one of the images shown as \"Example Data\" for \"Specificity Validation\" on Origene's \"Antibodies\" landing page appears to have been manipulated.

\n
\"\"
An image shown as example validation data on Origene's \"Antibodies\" landing page. The same image appears in a promotional video about Origene's \"rigorous process\" for knockout-based validation.
\n

(As it turns out, some of the images I had previously annotated as belonging to Thermo Fisher products actually belonged to Origene products and only appeared on Thermo Fisher's website as part of a partnership with Origene to also include their catalog in Thermo Fisher's search interface. This error has been corrected in the updated version of the repository.)

\n

Millipore Sigma (39 images across 31 products)

\n

Millipore Sigma is a subsidiary of Merck KGaA, headquartered in Darmstadt, Germany. Most of these image manipulations involve reuse of background patterns C and D.

\n
\"\"
A Western blot image presented as validation data for a Millipore Sigma CEACAM5 antibody.
\n

LSBio (2,695 images across 2,536 products)

\n

LSBio is a subsidiary of Vector Laboratories, based in Newark, California. Their catalog features more than 1,000 repetitions each of background pattern A and background pattern B and hundreds of instances of apparent painting in Western blot and immunofluorescence images.

\n
\"\"
A Western blot image presented as validation data for a LSBio CD79 antibody.
\n
\"\"
A Western blot image presented as validation data for a LSBio ESRRA antibody.
\n
\"\"
An immunofluorescence image presented as validation data for an LSBio MTCH2 antibody.
\n

Bioss (305 images across 292 products)

\n

Bioss is headquartered in Woburn, Massachusetts. Hundreds of images in its catalog feature apparent painting or stitching-together of background noise.

\n
\"\"
An immunofluorescence image presented as validation data for a Bioss ALAS1 antibody.
\n
\"\"
A Western blot image presented as validation data for a Bioss Caspase-8 antibody.
\n
\"\"
An immunofluorescence image presented as validation data for a Bioss E2F4 antibody.
\n
\"\"
A Western blot image presented as validation data for a Bioss SCM1 alpha antibody.
\n

Boster Bio (120 images across 96 products)

\n

Boster Bio is headquartered in Pleasanton, California. Many images in Boster's catalog feature signs of apparent painting.

\n
\"\"
A Western blot image presented as validation data for a Boster AKT1 antibody.
\n
\"\"
A Western blot image presented as validation data for a Boster IKB epsilon antibody.
\n

G-Biosciences (6,388 images across 6,373 products)

\n

G-Biosciences is headquartered in St. Louis, Missouri. A stunning volume of images presented as validation data in G-Biosciences' catalog feature either background pattern A (4,278 images) or background pattern B (2,110 images).

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from G-Biosciences' catalog all featuring \"background pattern B\".
\n

GeneTex (38 images across 38 products)

\n

GeneTex is headquartered in Irvine, California. Problematic images in GeneTex's catalog include repetitions of background patterns A and B and at least one instance of copy-pasted background noise.

\n
\"\"
A Western blot image presented as validation data for a GeneTex TET3 antibody.
\n

HUABIO (209 images across 203 products)

\n

HUABIO is headquartered in Hangzhou, China. HUABIO's catalog features many instances of apparent painting and repetitive patterns in background noise.\u00a0

\n
\"\"
A Western blot image presented as validation data for a HUABIO GPC1 antibody.
\n
\"\"
A Western blot image presented as validation data for a HUABIO RBBP5 antibody.
\n

Some of the repetitive regions of background noise also inexplicably contain numerals. I do not have a satisfactory explanation for what happened here.

\n
\"\"
A Western blot image haunted by the number 15, presented as validation data for a HUABIO CLIC2 antibody.
\n

Antibodies.com (242 images across 242 products)

\n

Antibodies.com is headquartered in Cambridge, UK. At least 242 validation images in their catalog feature background pattern A. On August 21, I was alerted that several of these products had been discontinued from the Antibodies.com online catalog since I downloaded these images on August 12 and can no longer be found by search.

\n
\"\"
The product page for a CREB (pSer111) antibody that was discontinued by Antibodies.com sometime between 12 August and 21 August. The validation image displayed features background pattern A.
\n

Abnova (154 images across 145 products)

\n

Abnova is headquartered in Taipei, Taiwan. Many validation images in their catalog feature background pattern C or D, signs of apparent painting or compositing, or other common background patterns (\"background pattern G\" and \"background pattern H\") that I have not observed in other vendors' catalogs.

\n
\"\"
A collage of contrast-adjusted Western blots from Abnova's catalog all featuring \"background pattern G\", distinguishable by a patch of apparent painting around 34 kDa on the left side of the frame.
\n
\"\"
A collage of contrast-adjusted Western blots from Abnova's catalog all featuring \"background pattern H\", distinguishable by a patch of apparent painting around 20 kDa in the lower left corner of the frame.
\n
\"\"
A Western blot image presented as validation data for an Abnova FXR1 antibody (sold through Thermo Fisher's online catalog).
\n

Santa Cruz Biotechnology (125 images across 111 products)

\n

Santa Cruz Biotechnology is headquartered in Dallas, Texas. In 2016, the company paid a historically high 3.5 million USD fine to the United States Department of Agriculture to settle numerous allegations of violating the Animal Welfare Act in its treatment of animals used to produce antibodies. Problematic images in Santa Cruz's catalog feature background painting and apparent cloning of background noise.

\n
\"\"
A Western blot image presented as validation data for a Santa Cruz Biotechnology 14-3-3 eta antibody.
\n
\"\"
A Western blot image presented as validation data for a Santa Cruz Biotechnology G alpha 13 antibody.
\n

Postscript

\n

It cannot be overstated how much biomedical research rides on antibodies performing as intended and how much time researchers lose to working with antibodies that do not perform. Increased recognition of the importance of antibody validation has led to vendors near-universally embedding validation data in their catalogs. However, to many vendors, selling validated antibodies apparently matters less than the semblance of selling validated antibodies.\u00a0

\n

If an antibody fails internal validation testing by its manufacturer, a responsible vendor would elect not to sell it. However, a large fraction of research antibodies currently for sale do not perform as advertised, as detailed by Ayoubi et al. (2024). Thus, either manufacturers and vendors are willfully ignoring the results of their validation testing or are not performing validation testing in the first place. When a vendor sells an antibody with validation data that has been painted over or otherwise altered, it suggests the former possibility. The many wholly-fabricated Western blots using a common background pattern suggest the latter. Many companies are clearly attaching their quality guarantees to private-label products that they had no part in testing, if testing occurred at all.

\n

Skirting validation makes perfect business sense; running validation tests is expensive and it is more profitable to sell a large catalog of untested antibodies than a small catalog of properly-validated products. Ayoubi et al. address this:

\n
\n

Commercial antibody suppliers support a large and diverse catalogue of products, with most antibody products generating <$5000 in total sales, far less than the costs of [knockout]-based validation, estimated at $25,000. While leading companies are increasingly assessing antibody performance, it is exceedingly difficult, and cost restrained, to properly characterize all their products. Even when available, high-performing antibodies may remain hidden within the millions of reagents of unknown quality.\u00a0

\n
\n

An inconvenient result in validation testing could also mean that the cost of developing an antibody goes unrecouped. I wonder, then, why we feel comfortable outsourcing the critical task of antibody production and distribution to entities whose profit motive encourages them to market products that have not been tested.

\n

I do think that readers should direct their ire towards the companies that have been marketing antibodies with faked data. A simple way to do this is for scientists to request the original, unedited validation data images for antibodies they have purchased (Thermo Fisher has already promised that such images will be provided to customers \"where available\"). However, even the most protracted opprobrium will bounce off of large companies like Thermo Fisher or Merck KGaA. Regulation of how research antibodies are produced and marketed will induce longer-term change (and I believe regulation is a minimum necessary step), but there still remains a fundamental mismatch between the needs of the biomedical research community and the interests of the for-profit enterprises producing their crucial reagents. In the long term, I think that the biomedical research community would be better served by the creation of publicly-funded antibody vendors whose interest is in producing antibodies that work, not in producing antibodies that sell.

\n

Footnotes

\n
  1. The repository also contains two images from NeoBiotechnologies (based in Union City, California) which represent a re-used image of an SDS PAGE gel on the product pages for two different TP53 antibodies. Since these were the only potentially problematic images identified in their catalog, I did not profile NeoBiotechnologies here. These products were previously annotated as Thermo Fisher products. This error has been corrected in the latest version of the repository. \"\u21a9\"\ufe0e
\n

","doi":"https://doi.org/10.59350/txnbb-prj57","guid":"http://reeserichardson.blog/?p=4960","image":"https://reeserichardson.blog/wp-content/uploads/2026/08/ma5-15569_ma5-15671_annotated.png?w=1024","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787616000,"rid":"an620-j7872","summary":"On May 17, 2026, Sholto David identified one fabricated image presented as validation data in Thermo Fisher's antibody catalog.","tags":["Research Integrity"],"title":"At least 15 companies are selling antibodies using faked validation data","updated_at":1787662567,"url":"https://reeserichardson.blog/2026/08/25/at-least-15-companies-are-selling-antibodies-using-faked-validation-data/","version":"v1"}},{"document":{"authors":[{"affiliation":[{"id":"https://ror.org/046ak2485","name":"Freie Universit\u00e4t Berlin"}],"contributor_roles":[],"family":"Fischer","given":"Georg","url":"https://orcid.org/0000-0001-5620-5759"},{"affiliation":[{"id":"https://ror.org/0546hnb39","name":"University of Konstanz"}],"contributor_roles":[],"family":"Flaig","given":"Sebastian","url":"https://orcid.org/0009-0001-1247-6976"},{"affiliation":[{"name":"Freie Universit\u00e4t Berlin, Open Research Office Berlin"}],"contributor_roles":[],"family":"Neufend","given":"Maike","url":"https://orcid.org/0000-0002-1484-0516"}],"blog":{"authors":[{"name":"Open Access Network"}],"community_id":"969d397b-49b9-4c53-9220-607ef85409e5","created":1780876800,"current_feed_url":null,"description":"Neueste Beitr\u00e4ge","doi":"https://doi.org/10.64395/oa_network","favicon":"https://rogue-scholar.org/api/communities/969d397b-49b9-4c53-9220-607ef85409e5/logo","feed_format":"application/rss+xml","feed_url":"https://open-access.network/rss-feed?type=200","filter":null,"generator":"Other","home_page_url":"https://open-access.network/rss-feed?type=200","issn":null,"language":"deu","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.64395","relative_url":null,"secure":null,"slug":"oa_network","status":"active","subfield":"1802","title":"OA Network","updated":1787646360,"use_api":null},"blog_name":"OA Network","blog_slug":"oa_network","content_html":"\"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin\n\n\nAnfang Juli 2026 hat die Landesinitiative Open Research Berlin ein Positionspapier zur Entwicklung von Open Research in Berlin ver\u00f6ffentlicht. Unter dem Titel \"Offenheit als Grundsatz\" enth\u00e4lt das neue Papier diverse Vorschl\u00e4ge und Ideen f\u00fcr Ma\u00dfnahmen, um Open Access auf Open Research strategisch f\u00fcr Wissenschaft und Kulturerbe auszuweiten und im Berliner Forschungsraum zu verankern. Im Interview mit dem oa.blog erz\u00e4hlen Georg Fischer und Maike Neufend vom Open Research Office Berlin (OROB), das den Prozess koordiniert hat, von den Hintergr\u00fcnden, der Motivation und den Kernpunkten des Positionspapiers.\n\n\noa.blog: Wie kam es zur Erarbeitung des neuen \"Positionspapiers zur Entwicklung von Open Research in Berlin\"?\nOROB: Dazu ist es wichtig, einen Schritt zur\u00fcck zu gehen: 2015 erschien die \"Open-Access-Strategie Berlin\", die vom Berliner Abgeordnetenhaus verabschiedet worden war. Das Dokument legte den Grundstein f\u00fcr die kooperative Entwicklung von Open-Access-Aktivit\u00e4ten f\u00fcr den Standort Berlin. Als Ziel wurde damals unter anderem ausgegeben, bis 2020 den Anteil der wissenschaftlichen Open-Access-Publikationen f\u00fcr Zeitschriftenartikel aus allen wissenschaftlichen Einrichtungen in der Zust\u00e4ndigkeit des Landes Berlin auf mindestens 60% zu erh\u00f6hen. Daneben sollten Open Access in den Berliner Hochschulvertr\u00e4gen verankert und die Diskussion \u00fcber die Einbeziehung von Open Access als Indikator f\u00fcr die leistungsorientierte Mittelvergabe gef\u00f6rdert werden. Die Open-Access-Strategie sah au\u00dferdem vor, neben Text-Publikationen auch Forschungsdaten und Kulturdaten bzw. kulturelles Erbe als Handlungsfelder zu entwickeln. Das Open Research Office Berlin ist ebenfalls als Ma\u00dfnahme aus der Berliner Open-Access-Strategie von 2015 hervorgegangen (2016 als \"Open-Access-B\u00fcro Berlin\" gegr\u00fcndet, umbenannt 2025).\n\nNun sind gut zehn Jahre vergangen und die Wissenschaftswelt hat sich weitergedreht. Open Research wurde etwa in das Berliner Hochschulgesetz (BerlHG) aufgenommen: In Paragraph 41 werden Open Access und Open Science definiert und der Auftrag der Hochschulen beschrieben. Auch in der Praxis hat sich Open Access in vielen Bereichen als genereller Standard etabliert; Forschungsdaten zu teilen wird zunehmend beliebter und auch im Kulturbereich tut sich allerhand bei der digitalen \u00d6ffnung und Nutzung der Best\u00e4nde, wie wir 2024 im Open-Access-Bericht Berlin festgehalten haben. Um den Entwicklungen Rechnung zu tragen und die Bedingungen \u2013 z. B. auf infrastruktureller oder rechtlicher Ebene \u2013 aktiv zu gestalten, wurde die \"Landesinitiative Open Research Berlin\" ins Leben gerufen. Damit werden die Erfolge aus der Open-Access-Strategie von 2015 weitergef\u00fchrt, mit Open Research wird aber nun der gesamte Forschungszyklus ins Auge genommen und neben der Wissenschaft werden weitere Wissenssysteme einbezogen. Die Landesinitiative legt nun nach einem partizipativen Prozess das \"Positionspapier zur Entwicklung von Open Research in Berlin\" vor, das zahlreiche Vorschl\u00e4ge und gangbare Wege konturiert, um die Vorreiterrolle Berlins in Sachen Offenheit zu festigen.\n\n\noa.blog: In einem Satz zusammengefasst: Was versteht ihr unter \"Open Research\" konkret?\nOROB: In der Landesinitiative haben wir uns auf folgenden Konsens verst\u00e4ndigt: Mit Open Research meinen wir einen gemeinsamen Bezugsrahmen, in dem verschiedene Praktiken und Prinzipien offener Forschung zusammengef\u00fchrt werden, um Offenheit, Nachvollziehbarkeit und Teilhabe in Wissenschaft und Kultur zu erh\u00f6hen und den Dialog mit anderen Wissenssystemen zu verbessern.\n\n\noa.blog: Was versprecht ihr euch vom Positionspapier?\nOROB: Berlin hat aufgrund der zahlreichen wissenschaftlichen und kulturellen Einrichtungen, die bereits jetzt vielfach miteinander vernetzt sind, einige Standortvorteile. Es gibt hier diverse gut eingespielte Verb\u00fcnde und Kooperationen, die zu verschiedenen Themen gemeinsam arbeiten und L\u00f6sungen f\u00fcr geteilte Herausforderungen suchen. Dennoch k\u00f6nnen mit Open Research neue Potentiale gehoben und \u00fcber Wissenschaft und Kultur hinaus verankert werden: etwa um die gegenseitige Durchdringung der Bereiche zu st\u00e4rken oder die demokratische Aushandlungsf\u00e4higkeit \u2013 und damit auch das Gemeinwohl der Stadtgesellschaft \u2013 zu verbessern.\n\nDie Landesinitiative kn\u00fcpft hier mit ihrem Positionspapier zu Open Research an. Open Research kann folgende drei Standortvorteile f\u00fcr Berlin st\u00e4rken: erstens Wissenstransfer und Vermittlung von Kunst und Kulturerbe, zweitens digitale Souver\u00e4nit\u00e4t und Resilienz sowie drittens Kooperation und gemeinsame Infrastruktur. Offene Forschung und offene Kultur leisten einen elementaren Beitrag zur St\u00e4rkung von demokratischen Prozessen, Vielfalt und Wissensgerechtigkeit. Informationsinfrastrukturen stellen auf der anderen Seite, insbesondere wenn sie offen und kooperativ getragen sind, eine wesentliche Voraussetzung f\u00fcr die digitale Handlungsf\u00e4higkeit und Unabh\u00e4ngigkeit der Wissenschafts- und Kulturerbe-Einrichtungen dar. Kooperationen innerhalb Berlins schlie\u00dflich schaffen Synergien, k\u00f6nnen die Effizienz erh\u00f6hen und st\u00e4rken die Widerstandsf\u00e4higkeit des Wissenschafts- und Kulturstandorts. In dem Positionspapier skizziert die Landesinitiative entsprechende Ma\u00dfnahmen und legt dar, wie diese ineinandergreifen.\n\n\noa.blog: Was sind die wichtigsten Eckpunkte und Themen?\nOROB: Das Papier formuliert insgesamt vier gro\u00dfe Themen: Kulturen der Offenheit, Souver\u00e4ne Wissens\u00f6kosysteme, Faire Finanzierung und Open Research Monitoring.\n\nKulturen der Offenheit f\u00f6rdern Transparenz, Zusammenarbeit und den Austausch von Wissen in Fachdom\u00e4nen und \u00d6ffentlichkeit. Erst in und mit Kulturen der Offenheit lassen sich souver\u00e4ne Wissens\u00f6kosysteme entwickeln, die es den Akteur*innen erm\u00f6glichen, ihre Publikationen, Informationen und Daten selbstbestimmt zu verwalten, ihre Forschungsprozesse offen zu gestalten und im Rahmen offener Praktiken langfristig zu etablieren und zu pflegen.\n\nGleichzeitig ist eine den Kosten angemessene, also faire Finanzierung notwendig, um die genannten Kulturen der Offenheit zu st\u00e4rken und die Entwicklung souver\u00e4ner Wissens\u00f6kosysteme institutionell und langfristig zu verankern. Hier sieht es die Landesinitiative als unabdingbar an, die Berliner Einrichtungen mit angemessenen finanziellen Mitteln auszustatten. Zugleich m\u00fcssen die Einrichtungen die Finanzentscheidungen so diversifizieren, dass die Finanzierung von Forschung inklusive Publikationen gerechter wird, d.h. nicht-gewinnorientiertes Open Research gef\u00f6rdert wird. Erst dann lassen sich die oben genannten Ziele erreichen.\n\nAu\u00dferdem sehen wir ein intelligentes, kontextsensitives Monitoring von Open Research vor, das die Entwicklung in den vorherigen Themenbereichen dokumentiert und damit nachvollziehbar macht, ob die Prinzipien der Offenheit, Souver\u00e4nit\u00e4t und Fairness gelebt werden und wo ein Nachsteuern ggfls. notwendig ist. Ein solches Monitoring erm\u00f6glicht also eine kontinuierliche Verbesserung und Anpassung der Ma\u00dfnahmen.\n\n\noa.blog: Und welche konkreten Ziele adressiert das Papier?\nOROB: Konkret sollen innerhalb der vier Themen folgende neun Ziele erreicht werden: Anerkennung, Kompetenzen und Rechtssicherheit in Bezug auf Open Research st\u00e4rken; robuste Informationsinfrastrukturen kooperativ entwickeln und pflegen sowie das Engagement zur Unterst\u00fctzung von Open Research verbessern; transparente Finanzierungsmodelle entwickeln und mit Leben f\u00fcllen sowie eine koordinierte Transformation und Diversifizierung des Investitionsverhaltens einleiten; geeignete Methoden zur Beobachtung, Dokumentation und Monitoring von Open Research entwickeln und umsetzen.\n\n\noa.blog: Was habt ihr speziell f\u00fcr Open Access festgehalten? Welche Rolle sieht das Papier f\u00fcr Open Access im gr\u00f6\u00dferen Kontext von Open Research vor?\nOROB: Die Definition von Open Research basiert auf den vorhergehenden Initiativen und Empfehlungen, wie die Budapest Open Access Initiative (2002), das Bethesda Statement on Open Access Publishing (2003) und die Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003). Wenn es um die Ver\u00f6ffentlichung von wissenschaftlicher Information und Forschung durch die Mitglieder der Hochschulen geht, soll diese unter freien Lizenzen mit dem Ziel der Nachnutzbarkeit erfolgen (Open Access). Da Open Access sich in den vergangenen Jahren zu einem sehr lukrativen Gesch\u00e4ftsmodell f\u00fcr gewinnorientierte Verlage entwickelt hat, liegt ein Fokus aktuell auf einer Diversifizierung der Finanzentscheidungen von Hochschulen (faire Finanzierung) und entsprechend einer F\u00f6rderung von Open Access als nicht-gewinnorientiertes Publizieren. Darunter verstehen wir nicht, dass faires Open-Access-Publizieren zwingend weniger kostet, aber die Investition in nachhaltige und wissenschaftsgeleitete Publikationsinitiativen und -Modelle erlaubt, Kosten und Preise nachvollziehbar und damit die Finanzierung durch die \u00f6ffentliche Hand gerechter zu machen. Zugleich k\u00f6nnen die technologischen Investitionen und das Engagement der Wissenschaft f\u00fcr innovative Verfahren der Wissenschaftskommunikation an den Hochschulen besser verankert werden.\n\n\noa.blog: Wieso ist das Positionspapier auch f\u00fcr andere Einrichtungen und OA-Professionals interessant, obwohl es sich auf Berlin bezieht?\nOROB: Bei der Erarbeitung des Papiers hat sich die Landesinitiative von zahlreichen existierenden Initiativen, Strategien und anderen Papieren inspirieren lassen, etwa von der UNESCO, der DFG und nat\u00fcrlich von Entwicklungen im Berliner Raum. Damit bilden wir den Status Quo in Sachen Open Research im Jahre 2026 ab, was f\u00fcr Einrichtungen und OA-Professionals, aber auch f\u00fcr interessierte Forschende insgesamt von Interesse sein d\u00fcrfte. Die von uns adressierten neun Ziele enthalten kulturelle, rechtliche, infrastrukturelle, technische und finanzielle Aspekte in Sachen Open Research und sollen Impulse setzen, offene Wissenschaft und Kultur gemeinsam weiterzuentwickeln, also etwa die Arbeit von Bibliotheken, Archiven und Kulturerbe-Einrichtungen zusammen mit wissenschaftlicher Forschung und Lehre zu verzahnen und damit Synergien zu heben. Interessierte d\u00fcrften daher Denkanst\u00f6\u00dfe f\u00fcr einzelne Problemstellungen erhalten wie auch f\u00fcr das Gesamtpaket, das die Landesinitiative f\u00fcr Berlin nun anbietet. Schlie\u00dflich unterst\u00fctzt das Papier auch die \u00fcberregionale Zusammenarbeit, z. B. mit Landesinitiativen aus anderen Bundesl\u00e4ndern oder lokalen Akteur*innen. Wir haben hier gute Erfahrungen und eine enge Zusammenarbeit etwa mit den Kolleg*innen aus Nordrhein-Westfalen, dem Saarland oder Brandenburg.\n\n\noa.blog: Habt ihr im Strategieprozess Erfahrungen gemacht, von denen andere Akteure lernen k\u00f6nnen, die \u00e4hnliche Vorhaben verfolgen?\nOROB: Es braucht einen langen Atem, um die verschiedenen Interessen der einzelnen Stakeholder zu diskutieren und unter dem Dach eines gemeinsamen Papiers zusammenzubringen. Das war im Berliner Fall nicht innerhalb von ein paar Monaten zu bewerkstelligen. Gleichzeitig war uns von Anfang an ein transparenter und partizipativer Konsultationsprozess zur gemeinsamen Erarbeitung des Papiers wichtig. Dies haben wir in einem Addendum dokumentiert, das vergleichbaren Initiativen hoffentlich Anregungen bietet.\n\nMan muss darauf vorbereitet sein, dass sich externe Rahmenbedingungen \u00e4ndern k\u00f6nnen, auf die man selbst keinen Einfluss hat. In unserem Fall etwa die Wiederholungswahl zum 19. Abgeordnetenhaus von Berlin am 12. Februar 2023, aber auch der \u00dcberfall Russlands auf das gesamte Staatsgebiet der Ukraine oder der Erfolg von KI-Technologien, der nun weite Teile des Forschungsprozesses ber\u00fchrt. In diesem Zuge wurden etwa Themen wie digitale Souver\u00e4nit\u00e4t und Resilienz von technischen Systemen im Kontext Offenheit wichtiger, so dass wir in der Landesinitiative darauf reagierten. \n\nLast but not least ist das Positionspapier die Frucht des regelm\u00e4\u00dfigen Austauschs: nicht nur in der Landesinitiative sondern auch etwa vier Mal im Jahr mit den Open-Access-Beauftragten der Berliner Universit\u00e4ten und Hochschulen. In diesen Runden sind \u00fcber die Jahre zahlreiche Herausforderungen, L\u00f6sungswege und strategische Ans\u00e4tze diskutiert worden, die in das Positionspapier gem\u00fcndet sind.\n\n\noa.blog: Wie geht es nun mit dem Positionspapier weiter? Habt ihr bereits konkrete n\u00e4chste Schritte f\u00fcr die praktische Umsetzung der Ziele vorgesehen?\nOROB: Der Konsultationsprozess ist mit der Ver\u00f6ffentlichung des Papiers nicht abgeschlossen, sondern nun f\u00fcr die interessierte \u00d6ffentlichkeit ge\u00f6ffnet. Auf PubPub k\u00f6nnen alle, die m\u00f6gen und sich einen Account anlegen, im Rahmen eines Public Review-Verfahrens das Papier kommentieren, Vorschl\u00e4ge, Ideen, Anregungen eingeben und sich so in den Prozess einbringen. Aktuell wird das Papier in den Gremien der betroffenen Berliner Einrichtungen diskutiert und weitere Schritte werden in den kommenden Sitzungen der Landesinitiative er\u00f6rtert. Mit Spannung blicken wir auf die Wahl zum Abgeordnetenhaus von Berlin am 20. September, nach der sich f\u00fcr die gro\u00dfen wissenschaftspolitischen Vorhaben in Berlin die Weichen stellen werden.\n\n\noa.blog: Vielen Dank!\n\n\nDas Interview f\u00fchrte f\u00fcr den oa.blog Sebastian Flaig. F\u00fcr das OROB beantworteten die Fragen Georg Fischer und Maike Neufend.\n\n\nZitiervorschlag\nFlaig, S., Fischer, G., Neufend, M. (2026): \"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin. open-access.network. DOI: \n\n\n\nDieser Beitrag ist lizenziert unter der Creative Commons Namensnennung 4.0 International Lizenz (CC BY 4.0)","doi":"https://doi.org/10.64395/3zj8s-kxd10","guid":"https://open-access.network/blog/interview-zum-strategiepapier-open-research-berlin","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787616000,"rid":"vw51w-tc197","summary":"\"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin Anfang Juli 2026 hat die Landesinitiative Open Research Berlin ein Positionspapier zur Entwicklung von Open Research in Berlin ver\u00f6ffentlicht.","tags":["Open Access Transformation"],"title":"\"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin","updated_at":1787658400,"url":"https://open-access.network/blog/interview-zum-strategiepapier-open-research-berlin","version":"v1"}},{"document":{"authors":[{"contributor_roles":[],"family":"Neylon","given":"Cameron","url":"https://orcid.org/0000-0002-0068-716X"},{"affiliation":[{"name":"Sesame Open Science"}],"contributor_roles":[],"family":"Kramer","given":"Bianca","url":"https://orcid.org/0000-0002-5965-6560"},{"contributor_roles":[],"family":"Mazoni","given":"Alysson","url":"https://orcid.org/0000-0001-5265-6894"},{"affiliation":[{"id":"https://ror.org/027bh9e22","name":"Leiden University"}],"contributor_roles":[],"family":"Costas","given":"Rodrigo","url":"https://orcid.org/0000-0002-7465-6462"},{"contributor_roles":[],"family":"Jahn","given":"Najko","url":"https://orcid.org/0000-0001-5105-1463"},{"affiliation":[{"name":"Leiden University, Centre for Science and Technology Studies"}],"contributor_roles":[],"family":"van Eck","given":"Nees Jan","url":"https://orcid.org/0000-0001-8448-4521"}],"blog":{"authors":null,"community_id":"b56ef314-34f7-4c7f-b0e2-d0bf13bfe83b","created":1673568000,"current_feed_url":"https://upstream.force11.org/atom/","description":"The community blog for all things Open Research.","doi":"https://doi.org/10.54900/upstream","favicon":"https://rogue-scholar.org/api/communities/b56ef314-34f7-4c7f-b0e2-d0bf13bfe83b/logo","feed_format":"application/atom+xml","feed_url":"https://upstream.force11.org/atom-complete/","filter":null,"generator":"Ghost","home_page_url":"https://upstream.force11.org","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.54900","relative_url":null,"secure":true,"slug":"upstream","status":"active","subfield":"1802","title":"Upstream","updated":1785846998,"use_api":true},"blog_name":"Upstream","blog_slug":"upstream","content_html":"

The rise of open research information resources is transforming the way we track, analyse and study research systems. Increasingly, sources like OpenAIRE, OpenAlex, Crossref, DataCite, ORCID, ROR and others are being used as the basis for making decisions, designing interventions and understanding progress in the science system. This operates both at the small scale, where access to data and evidence is easier than it has ever been, to the very large scale analysis of whole systems.

Traditionally, the capacity to do large-scale analyses was restricted to a very small set of players, like specialised research centres or companies. This kind of large scale analysis usually requires access to an actionable version of the whole dataset, particularly if the goal is combining data resources. The set of sites with access to complete copies of proprietary databases is tiny. 

Modern open data sources provide access, including access to full copies of the data, but there has been less focus on providing this access in a way that allows large scale complex querying and connecting of whole data archives - for example to compare the coverage of research outputs by OpenAlex and OpenAIRE or analyse global information on clinical trials using affiliation data from OpenAlex and clinical trials information from Pubmed. Another valuable possibility is the ability to incorporate local data enrichments from national or regional data sources to support local data needs, or improve the overall pool of data.

Google BigQuery has emerged as one powerful tool for combining and working on these large datasets at scale. Multiple groups (including the MultiObs team - continuing the work of the InSySPo team at Campinas, SUB G\u00f6ttingen, Sesame Open Science and CWTS amongst others), have created 'public' versions of specific open datasets in the BigQuery system, which anyone can access and run their own analyses. Through these public versions, the 'provider' (i.e. the teams mentioned above) pays for storage, and the user freely accesses the 'public' versions taking responsibility for covering the costs of data querying and processing.  

Having worked independently so far, this small group came together last year to ask whether we could coordinate actions. Could it be possible to build a comprehensive open research information resource where the load of providing specific core and relevant open data sources was distributed? Rather than each separately trying to tackle the whole, potentially duplicating efforts, could we collectively create a resource that was more than the sum of its parts? 

We met with a series of key questions:

  1. Can we share resources and burdens to make available key open research information resources in actionable and connectable form in the cloud?
  2. Through sharing processes and systems, is it possible, over time, to build a standard for how these data sources should be made available?
  3. What are the challenges that we can usefully approach collectively?
  4. What are the benefits and risks of Google BigQuery as an environment and do we agree it is the best place to start?
  5. What are the blockers for engagement with such an effort? What is needed for different stakeholders to make it attractive both as users and (for some) as providers?

User and use case driven

Core to our shared interest in working together was the idea of making it easier for more people to undertake large scale analysis. There are many kinds of analysis for which access to APIs is sufficient. We share a belief that large scale analysis will be useful in multiple settings, but that it has been relatively inaccessible. This inaccessibility is a hurdle to realising the promise of democratization and broader adoption of open research information in all decision making processes around science and scholarship, as proposed by the Barcelona Declaration. APIs are also expensive to run, by taking some of the heavy load use-cases away from APIs we can support providers by reducing their costs, centralising distribution, and allowing APIs to focus on the use cases they are best suited for.

There is a growing set of research projects that are exploiting this capacity for large scale and combined analysis in a range of ways. Two recent pieces of work provide examples of what is possible. One by Camilla Lindelow and Eline Vandewalle, used the combination of ORCID and OpenAlex provided by InSySPo (now MultiObs) to analyse researchers without a formal affiliation from around the world. The second example, from Cespedes and colleagues associated with the UNESCO Chair in Open Science, used a global analysis of language in OpenAlex to examine affiliation. This combines with other efforts, including comparisons of metadata coverage across sources, and combinations of data sets that exploit the capacity to do analysis at scale.

These use cases have a few things in common. They tend to be global in scope (or at least aspire to be) so they require analysis across the whole of a datasource (or a combination of datasources). They generally involve a complex form of query, requiring filtering or analysis on multiple database elements, or a combination of multiple data sources, that is difficult or impossible using the API for any given datasource. And the generated dataset is often very large in its own right - perhaps involving hundreds of millions of rows of data - and requires further reduction and analysis.

Overall, the common theme here is analyses that require entire data sources to be combinable and actionable at scale. We believe if we focus on that set of use cases we can add something valuable to the overall Open Research Information ecosystem.

Opportunities for shared systems

If people are already doing this what is the value of coordination? The first and most obvious is that with a shared cloud system we only need to pay for online storage of each dataset once and then anyone can use it (backups and versions over time are a separate issue, which we aim to address, but not as the first priority). Cloud storage costs are generally larger than the usage costs involved in running queries so sharing this load is valuable in its own right.

The second advantage is the ability to share capacities. One example of this is data preprocessing. These datasets are not \"clean\" in the sense that they change over time, have some internal inconsistencies, and often contain elements that raise compatibility issues with database systems. Processing hundreds of millions of lines of JSON to convert hyphens to underscores in variable names takes time and computing power (and money!). 

Systems developed within the Curtin Open Knowledge Initiative (COKI) use cloud VMs to do this on demand which scales but adds costs. The team at G\u00f6ttingen are using code derived from this on their own HPC resources. The team at CWTS uses their own code to process datasource dumps on local servers so that relational databases can be integrated into their internal database system, while also exporting the results to Google BigQuery. Within the Sesame Open Science system a further evolution of the COKI code is used to process dumps on local computers. There is a clear benefit to be gained by using a common code base for necessary transformations. But also in having a community discussion on what pathways and transformations are necessary. The MultiObs team uses a quite different approach -- creating relational structures from datasource dumps -- with advantages (reduced costs, timestamps, etc.) but also disadvantages (lack of live data, need for updates, etc.) we can learn from. Different approaches and experiences, but also different sets of resources like HPC could be shared amongst an effective collaboration.

This leads to the third advantage. If we use common systems we help to develop quasi-standards that can be adopted by others. That creates an opportunity to spread the load further, as well as to increase the diversity of datasets available (again, thinking of those highly curated national datasets that are used locally but not always recombined into the global data ecosystem). If we have a clear shared approach to the data and how it is managed it makes it easier for others to contribute, and makes the whole set of resources more valuable and sustainable. In essence, the more we share the load, the less we pay for the costs of our contributions. 

A final benefit of a shared approach would be a virtuous loop in which shared systems encourage shared approaches to analysis. Common approaches can form the basis for training resources that give end-users an easy point of entry to using these data sources at scale. They will also encourage the sharing of analysis scripts and protocols creating advanced and transparent resources to support developing users.

Key to this is understanding both what has value to keep in common, but also what needs to be different to serve a diversity of use cases. We can see value in technical standards (where they are useful) and in agreements around archiving and preservation. Documentation, where it can reach common standards, will be helpful not just for users of the data, but potentially for upstream producers in understanding how the data is being used and how to optimize the provision of their data snapshots to facilitate downstream usage.

The Google-shaped elephant in the room 

A big question is why Google BigQuery? It is certainly not an open system in any meaningful sense and Google is not an organisation many of us feel able to trust. The short answer is pragmatism. There are reasons why we independently arrived at GBQ as a useful tool. Google solves a bunch of the hard problems, including authentication without the need for institutional affiliation, systems provisioning and a highly performant database system. In practice, this means datasets can be made publicly available, without the need for specific hard-or software on the side of the user, and, from a user perspective, access to datasets hosted by different providers is possible using a single system. Standing up an independent infrastructure to do this is a big job and not one we're equipped to tackle at the moment.

That said, none of us believe that reliance on Google is a desirable long term solution, nor that it is fully equitable. There are some emerging alternatives both in the cloud and for local computing. These aren't fully mature but they show promise. In the meantime we believe it is important to ensure we have an exit strategy. One such strategy could be a commitment to creating backups in the form of parquet files. Parquet is an interesting interoperability format for databases and can be read in by an increasing number of tools. It holds schema information and allows for database partitioning. 

Perhaps the most important argument is that with Google BigQuery and external archiving, there is at least one plausible option to explore that can provide value immediately, but also provide a potential escape route. We can save the arguments for frozen duck lakes, glaciers, torrents and MySQL for later and for those who will want to have them! But we need to think seriously about how we will work towards more independence and resilience early on in the process. 

Next steps and a call for interest

We have made a small start. Small, but useful for us.  After all, we are already using these shared data resources. We have demonstrated that without much effort or technical hassle it is possible to share the load, reduce costs and maximize benefits and accessibility. We hope by engaging a wider community we can make this more useful for more people and move us all closer to ideals of democratization of open research information, supporting adoption. How far this goes and how big a community we can create is an open question.

We have made a small start under the label of ORION-DBs, standing for Open Research Information Online Databases. There is now a website that details the datasets available, where they can be accessed and when the most recent update was. We hope this will be a useful resource for people doing ad hoc analyses, occasional use, or just one-off interest in taking a look, as well as those with bigger use cases and ongoing needs for data access. We hope a community of users and also of providers will be interested to coordinate through this platform to aid discovery, adoption and democratization of open research information.

Looking forward, we're interested in how we can build on this base. We want to coordinate and build a shared capacity. If you have an interest in how this could be shaped, demonstrating specific use cases, or contributing additional hosted datasets, we'd love to hear from you. Coordination takes time, time requires resources. If there is sufficient interest, we will look at how we could coordinate resources and build something as lightweight as possible and as formalised as necessary.

Above all, we want to hear from those who share the vision for creating data resources that can be combined and used together and to make them as useful as possible. You can contact us through info@orion-dbs.community and depending on interest, we will set up other forums. It is through using these data sources that we identify their issues and can correct and improve them. When we do that work together, we increase the quality of all data resources faster, more sustainably and more effectively.

","doi":"https://doi.org/10.54900/2pnyq-nhx95","guid":"https://doi.org/10.54900/2pnyq-nhx95","image":"https://upstream.force11.org/content/images/2026/02/antique-orion.webp","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1771200000,"rid":"9xdwc-j6753","summary":"The rise of open research information resources is transforming the way we track, analyse and study research systems. Increasingly, sources like OpenAIRE, OpenAlex, Crossref, DataCite, ORCID, ROR and others are being used as the basis for making decisions, designing interventions and understanding progress in the science system.","tags":["Thought Pieces"],"title":"Sharing the load: Building a collective to support open research information online","updated_at":1787651919,"url":"https://upstream.force11.org/sharing-the-load-building-a-collective-to-support-open-research-information-online/","version":"v1"}},{"document":{"authors":[{"affiliation":[{"id":"https://ror.org/008zgvp64","name":"Public Library of Science"}],"contributor_roles":[],"family":"Fenner","given":"Martin","url":"https://orcid.org/0000-0003-1419-2405"}],"blog":{"authors":[{"name":"Martin Fenner","url":"https://orcid.org/0000-0003-1419-2405"}],"community_id":"15a362ea-8138-42b8-917f-1840a92addf8","created":1672531200,"current_feed_url":null,"description":"The Front Matter Blog covers the intersection of science and technology since 2007.","doi":"https://doi.org/10.53731/front_matter","favicon":"https://rogue-scholar.org/api/communities/15a362ea-8138-42b8-917f-1840a92addf8/logo","feed_format":"application/atom+xml","feed_url":"https://blog.front-matter.de/atom","filter":null,"generator":"Ghost","home_page_url":"https://blog.front-matter.de/","issn":"2749-9952","language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.53731","relative_url":null,"secure":true,"slug":"front_matter","status":"active","subfield":"1710","title":"Front Matter","updated":1787642045,"use_api":true},"blog_name":"Front Matter","blog_slug":"front_matter","content_html":"

In October I published an essay on Article-Level Metrics (ALM) in PLOS Biology (Fenner, 2013). The essay is a good introduction into Article-Level Metrics, and I am proud that it is part of the Tenth Anniversary PLOS Biology Collection. Like all PLOS content, the article was published with a Creative Commons attribution license, allowing me to republish the article on this blog. I have now done so and the article is available here.

Of course I didn't want to simply republish the article, but I wanted to publish an improved version. The article has five figures, four of them show visualizations of ALM data that were generated using R (the fifth figure is a table reproduced from another article). The PLOS article includes the ALM dataset and the R scripts used to generate the figures as supplementary information. What I have done now is to recreate the article as a single markdown file (available here) that has all R code embedded. Using R and knitr - and the CSV file with the ALM data - everyone can now reproduce the figures from the paper by simply running the embedded code, and can dig deeper into the data.

\"Figure
Figure 3. Views vs. citations for PLOS Biology articles published in 2010.

This was a good opportunity to improve the accessibility of the article in other ways. Instead of the raster image formats PNG, JPEG and TIFF used by PLOS and almost every other publisher, I generated the figures in the vector format SVG. Not only does SVG produce images independent of device resolution and screen size (try to zoom in on the figure above), but SVG can also easily be manipulated in the browser since it is XML. This is beyond the scope of this blog post, but look at the d3.js Javascript library for great examples of how SVG can be dynamically generated and changed in the browser. Figure 3 above could for example be enhanced so that the article title is displayed when you hover over one of the bubbles, or we could enable zooming to show more detail.

Like all content on this blog, the article was created using Pandoc, and the bibliography was dynamically generated. This makes it easy to change the citation style, and I decided to use the APA Style that shows the citations in the text as author-date rather than numbered as with the PLOS style (see the example citation in the first paragraph). The combined bibliography for all blog posts including the article can be downloaded in bibtex format here.

Lastly, I wanted to generate nicer HTML for a better online reading experience. I haven't done anything fancy, but most publishers seem to focus on navigation around an article, so that very little screen real estate is left for the actual content of the article. I've tried to improve readability by reducing the navigation areas to a minimum, by using readable fonts in larger sizes: Adobe Minion Pro for the body text and Adobe Myriad Pro for headings, tables and figure legends.

References

Fenner, M. (2013). What can article-level metrics do for you? PLoS Biol, 11(10), e1001687. doi:10.1371/journal.pbio.1001687

","doi":"https://doi.org/10.53731/r294649-6f79289-8cw0n","guid":"https://doi.org/10.53731/r294649-6f79289-8cw0n","image":"https://storage.ghost.io/c/c5/33/c533c955-b5f3-4ff1-ae2d-6b52a212e602/content/images/2025/01/pbio.1001687.g003.png","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1386720000,"reference":[{"id":"https://doi.org/10.1371/journal.pbio.1001687","unstructured":"Unknown title"}],"rid":"5dqtd-94222","summary":"In October I published an essay on Article-Level Metrics (ALM) in PLOS Biology (Fenner, 2013). The essay is a good introduction into Article-Level Metrics, and I am proud that it is part of the Tenth Anniversary PLOS Biology Collection. Like all PLOS content, the article was published with a Creative Commons attribution license, allowing me to republish the article on this blog. I have now done so and the article is available here.","tags":["Feature"],"title":"Example article with embedded code and data","updated_at":1787651654,"url":"https://blog.front-matter.de/posts/example-article-with-embedded-code-and-data/","version":"v1"}},{"document":{"authors":[{"affiliation":[{"name":"Front Matter"}],"contributor_roles":[],"family":"Fenner","given":"Martin","url":"https://orcid.org/0000-0003-1419-2405"}],"blog":{"authors":[{"name":"Martin Fenner","url":"https://orcid.org/0000-0003-1419-2405"}],"community_id":"15a362ea-8138-42b8-917f-1840a92addf8","created":1672531200,"current_feed_url":null,"description":"The Front Matter Blog covers the intersection of science and technology since 2007.","doi":"https://doi.org/10.53731/front_matter","favicon":"https://rogue-scholar.org/api/communities/15a362ea-8138-42b8-917f-1840a92addf8/logo","feed_format":"application/atom+xml","feed_url":"https://blog.front-matter.de/atom","filter":null,"generator":"Ghost","home_page_url":"https://blog.front-matter.de/","issn":"2749-9952","language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.53731","relative_url":null,"secure":true,"slug":"front_matter","status":"active","subfield":"1710","title":"Front Matter","updated":1787642045,"use_api":true},"blog_name":"Front Matter","blog_slug":"front_matter","content_html":"

Starting this week blog posts are archived in the Rogue Scholar science blog archive using a dedicated invenio module instead of an external service. This simplifies the maintenance of the service and is critical for the long-term future of the archived content.

Rogue Scholar started out as a bespoke service written in Javascript in early 2023. In September 2024 Rogue Scholar started the migration to the InvenioRDM repository platform. This migration is now complete with the release of the invenio-feeds module that provides functionality to automatically parse blog feeds and archive the metadata and content in a digital repository. This extends functionality already available in InvenioRDM, or added in previous work \u2013 DOI registration with Crossref, full-text search, and automated subject classification with the OpenAlex vocabulary falls in the later category.

Until the release of invenio-feeds, automatic parsing of newly published or updated science blog posts was done by a dedicated Javascript and later Python service hosted at api.rogue-scholar.org. This service is no longer needed and will be retired on November 1st, reducing the complexity and cost of Rogue Scholar infrastructure. One example is the use of GitHub Actions to trigger the parsing of all blog feeds every 10 min which is now handled by InvenioRDM background workers.

The switch from dedicated external service to Python module has been fairly smooth so far, but I absolutely expect issues to come up in the coming weeks and months.

The migration to invenio module not only simplifies Rogue Scholar infrastructure, but comes with new functionality: archiving of blog posts as PDF files in the PDF/A format as InvenioRDM file attachments.

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One fundamental archiving principle is LOCKSS (Lots of Copies Keep Stuff Safe), and these PDF files nicely complement archiving activities by the blog itself, archiving of metadata and full-text in Rogue Scholar, and archiving of participating science blogs in the Internet Archive Archive-It service.

These PDF files are generated the moment content is added or updated to Rogue Scholar, and it will take a few months to address issues with the PDF files (e.g. pagination, image sizing), and archiving the more than 50K science blog posts in Rogue Scholar.

The PDF files use the same layout as the PDF files generated by Rogue Scholar since January 2024, but are generated with every submission to Rogue Scholar instead of dynamically on demand (using the commonmeta-py library). The PDF files are again generated with the WeasyPrint and pikepdf Python libraries, but no longer use Pandoc and the markdown format as an intermediary step. Other formats (markdown, ePub or JATS XML) are no longer supported, and this simplification makes the PDF generation workflow simpler and faster \u2013 allowing me to generate more than 3000 PDF attachments this week.

I have a painful relationship with PDF and scholarly publishing, and have long thought the proper archiving format for Rogue Scholar. WARC is a widely used archiving format developed and used by the Internet Archive \u2013 supported in InvenioRDM since the recent v14 release. Markdown and ePub are open formats closer to the technologies used by blogging platforms. PDF is fine for reading and archiving, but very painful to work with to extract content out again. The decision for PDF/A (and not WARC or ePub) was mainly for two reasons:

The PDF/A that Rogue Scholar generates has two important features that overcome critical PDF shortcomings:

Over the coming months I will not only work on any issues that come up with the new invenio-feeds module and PDF generation, but reach out to participating science blogs about archiving the PDF/A files in associated repositories, starting with the Invenio blog and Zenodo.

Please reach out via Slack, email, Mastodon, or Bluesky if you have any questions or comments.

Rogue Scholar is a scholarly infrastructure that is free for all authors and readers. You can support Rogue Scholar with a one-time or recurring donation or by becoming a sponsor.

References

  1. Fenner, M. (2022, December 12). Building an archive for scholarly blog posts. Front Matter. https://doi.org/10.53731/br9f5xa-a556w2t
  2. Fenner, M. (2024, September 2). Rogue Scholar migrates to InvenioRDM. Front Matter. https://doi.org/10.53731/sdazp-kzn55
  3. Fenner, M. (2023, October 30). Starting November, all Rogue Scholar blog posts will be archived by the Internet Archive. Front Matter. https://doi.org/10.53731/hhtx0-wb293
  4. Fenner, M. (2024, January 8). Every Rogue Scholar blog post now available in Markdown, ePub, and PDF formats. Front Matter. https://doi.org/10.53731/1dfxr-hs665
  5. Fenner, M. (2010, October 6). Beyond the PDF \u2013 it is time for a workshop. Front Matter. https://doi.org/10.53731/r294649-6f79289-8cw7z
","doi":"https://doi.org/10.53731/kv08z-vhj21","guid":"https://doi.org/10.53731/kv08z-vhj21","image":"https://images.unsplash.com/photo-1576670158645-ef7b03134e32?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=M3wxMTc3M3wwfDF8c2VhcmNofDM4fHxhcmNoaXZlfGVufDB8fHx8MTc4NzYzNTYyOXww&ixlib=rb-4.1.0&q=80&w=2000","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787616000,"reference":[{"id":"https://doi.org/10.53731/br9f5xa-a556w2t","unstructured":"Fenner, M. (2022, December 12). Building an archive for scholarly blog posts. Front Matter."},{"id":"https://doi.org/10.53731/sdazp-kzn55","unstructured":"Fenner, M. (2024, September 2). Rogue Scholar migrates to InvenioRDM. Front Matter."},{"id":"https://doi.org/10.53731/hhtx0-wb293","unstructured":"Fenner, M. (2023, October 30). Starting November, all Rogue Scholar blog posts will be archived by the Internet Archive. Front Matter."},{"id":"https://doi.org/10.53731/1dfxr-hs665","unstructured":"Fenner, M. (2024, January 8). Every Rogue Scholar blog post now available in Markdown, ePub, and PDF formats. Front Matter."},{"id":"https://doi.org/10.53731/r294649-6f79289-8cw7z","unstructured":"Fenner, M. (2010, October 6). Beyond the PDF \u2013 it is time for a workshop. Front Matter."}],"rid":"avg2p-eww74","summary":"Starting this week blog posts are archived in the Rogue Scholar science blog archive using a dedicated invenio module instead of an external service. This simplifies the maintenance of the service and is critical for the long-term future of the archived content. Rogue Scholar started out as a bespoke service written in Javascript in early 2023. In September 2024 Rogue Scholar started the migration to the InvenioRDM repository platform.","tags":["Rogue Scholar","InvenioRDM","Commonmeta"],"title":"Rogue Scholar blog post archiving becomes an InvenioRDM module","updated_at":1787651546,"url":"https://blog.front-matter.de/posts/rogue-scholar-blog-post-archiving-becomes-an-inveniordm-module/","version":"v1"}}],"items":[{"authors":[{"affiliation":[{"name":"Imperial College London, Chemstry"}],"contributor_roles":[],"family":"Rzepa","given":"Henry","url":"https://orcid.org/0000-0002-8635-8390"}],"blog":{"authors":[{"name":"Henry Rzepa","url":"https://orcid.org/0000-0002-8635-8390"}],"community_id":"8fb94c86-e95f-41cf-aac2-a2877ffc1b5f","created":1693094400,"current_feed_url":null,"description":"Chemistry with a twist","doi":"https://doi.org/10.59350/rzepa","favicon":"https://rogue-scholar.org/api/communities/8fb94c86-e95f-41cf-aac2-a2877ffc1b5f/logo","feed_format":"application/atom+xml","feed_url":"https://www.ch.ic.ac.uk/rzepa/blog/?feed=atom","filter":null,"generator":"WordPress","home_page_url":"https://www.ch.ic.ac.uk/rzepa/blog","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"rzepa","status":"active","subfield":"1606","title":"Henry Rzepa's Blog","updated":1787733932,"use_api":true},"blog_name":"Henry Rzepa's Blog","blog_slug":"rzepa","content_html":"
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I have in the past (around 2012 to be specific) taken an interest in a particular type of [3,3]sigmatropic pericyclic reaction called the semibullvalene rearrangement.[1],[2],[3]. This system can apparently exhibit very long C-C bonds in the region of 2.1\u00c5, in which form it would be called a “frozen” transition state, also referred to a bis-homoaromatic molecule, which in this form is NOT regarded as a [3,3]sigmatropic pericyclic transition state. Time for an update I thought, starting with a crystal structure search (Figure 1) for these types of species.

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Figure 1. Search query.

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Figure 2. C-C bond lengths, showing publication date.

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Figure 3. C-C bond lengths showing measurement temperature.

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The bottom right region of these maps (Figures 2 and 3) contains examples for which both DIST and DIST2 are more or less equal with values of ~2.1A. Note that all but one have been measured at room temperatures, which means that the structure is measured with a lot of thermal motions for the atoms. Some molecules have been singled out from the map above and two of those have been selected for DFT calculations – ICILAI which is characterised by dispersion attractions between ethyl groups on the bulvallene unit and CASFUE which instead has polar cyano groups.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
CSD EntryC-C 1C-C 2TempDOI
ICILAI1.9312.084RT[4]
ICILAI011.6902.325140[5]
ICIKUB1.9722.017RT[4]
CAZFUE011.9901.996RT[6]
LAGHOG031.6712.20615[7]
\n

Note that ICILAI, which has more or less equal bonds when measured at RT, shows very unequal bonds at\u00a0140K. The question we are asking here is whether there are any examples where the equal and long C-C bonds genuinely persist down to low temperatures and which therefore constitute especially “long” C-C bonds as part of a bis-homoaromatic molecule. The “bond” here would not be an abnormally long conventional \u03c3-bond but instead what is called a “suspended \u03c0-bond”\u00a0and considered a “normal” length for such an interaction.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Entry\u03bdC-C
\nMN15L[8]/Def2-TZVPP		DOI MN15L\u03bdC-C
\nr2SCAN-3c/Def2-mTZVPPL[9]		\u03bdC-C
\n\u03c9B97XD[10]/Def2-TZVPP		DOI \u03c9B97XD
CAZFUE01+214.7[11],[12]+234.1 (+291.6)\u2021-281.3[13],[14]
ICILAI-38.6[15]-155.8-356.0[16]
\n

What emerges from the calculations is that the characterisation as either a [3,3]-sigmatropic pericyclic transition state or as a bis-homoaromatic ground state is very dependent on the DFT functional being used.

\n
    \n
  1. For CAZFUE the conventional \u03c9B97XD/Def2-TZVPP method gives results belonging to the classical camp of predicting both examples above as being [3,3] sigmatropic transition states, with a characteristic strong calculated negative force constant and an IRC that shows the equal bond length position only as an energy maximum along the transition coordinate, albeit with a relatively modest barrier of ~5 kcal/mol. Such a value is higher than the energy of thermal vibrations, and so at low temperatures the structure will be frozen to either end of the IRC and show unequal C-C bonds of 1.614\u00c5 and 2.338\u00c5, typical of those found in the table above.
    \n\"\"
    \nFigure 4. \u03c9B97XD/Def2-TZVPP IRC for CAZFUE.
    2. \n
  2. The MN15L DFT method[8] (which is optimised specifically for transition metal elements) predicts a symmetrical long bond bis-homoaromatic structure\u00a0(C-C 2.135\u00c5) for CAZFUE, with a positive antisymmetric C-C stretch of +215 cm-1, almost equal in magnitude to \u03c9B97XD but opposite in sign for the force constant (Figure 5).
    \n\"\"
    \nFigure 5. MN15L normal vibrational C-C mode for CAZFUI.
    3. \n
  3. The newer r2SCAN-3c/Def2-mTZVPP functional is very similar in behaviour to MN15L.
    4. \n
  4. With MN15L, ICILAI however weakly retains the classical transition state mode, but now the C-C antisymmetric stretch is small with a negative FC (Figure 6). One wonders whether the difference is due to the dispersion attractions vs the electronic effect of a cyano group? The \u00a0r2SCAN-3c/Def2-mTZVPP method predicts a larger -ve FC (\u0394\u0394G\u2021 3.2 kcal/mol) but not as large as using \u03c9B97XD.
    \n\"\"
    \nFigure 6. MN15L normal vibrational C-C mode for ICILAI.
    5. \n
  5. In contrast to both MN15L and to a lesser extent \u00a0r2SCAN-3c/Def2-mTZVPP, using \u03c9B97XD for ICILAI reveals it is now strongly characterised as a [3,3] transition state.
    6. \n
\n

I note from Figure 2 that many of these crystal structures are quite old – clearly this area of research is no longer highly active. But such structures are proving invaluable tests of how density functional procedures perform for these molecules. Thus r2SCAN-3c/Def2-mTZVPP as a recent new method[17] is giving significantly different results from the much older \u03c9B97XD functional. But is it correct? More accurate and reliable crystal structures might help provide an answer – perhaps obtained using quantum crystallography? Or repeating the structure CAZFUI at say 15K.

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\u2021 Value for C2v symmetric tetra-cyano derivative.

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This post has DOI: 10.59350/sjyby-4yw41

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References

\n
  1. H. Rzepa, \"Predicted properties of a candidate for a frozen semibullvalene.\", 2012. https://doi.org/10.59350/cq2a3-g2g35\n\n
    2. \n
  2. H. Rzepa, \"Frozen Semibullvalene: a holy grail (and a bis-homoaromatic molecule).\", 2012. https://doi.org/10.59350/585c3-dpy86\n\n
    3. \n
  3. H. Rzepa, \"The ten-electron homologue of semibullvalene.\", 2012. https://doi.org/10.59350/8nkna-ycy23\n\n
    4. \n
  4. C. Wang, J. Yuan, G. Li, Z. Wang, S. Zhang, and Z. Xi, \"Metal-Mediated Efficient Synthesis, Structural Characterization, and Skeletal Rearrangement of Octasubstituted Semibullvalenes\", Journal of the American Chemical Society, vol. 128, pp. 4564-4565, 2006. https://doi.org/10.1021/ja0579208\n\n
    5. \n
  5. S. Zhang, M. Zhan, Q. Wang, C. Wang, W. Zhang, and Z. Xi, \"Synthesis of semibullvalene derivatives via Co\n <sub>2</sub>\n (CO)\n <sub>8</sub>\n -mediated cyclodimerization of 1,4-dilithio-1,3-butadienes\", Org. Chem. Front., vol. 1, pp. 130-134, 2014. https://doi.org/10.1039/c3qo00019b\n\n
    6. \n
  6. L.M. Jackman, A. Benesi, A. Mayer, H. Quast, E.M. Peters, K. Peters, and H.G. Von Schnering, \"The Cope rearrangement of 1,5-dimethylsemibullvalene-2,6- and 3,7-dicarbonitriles in the solid state\", Journal of the American Chemical Society, vol. 111, pp. 1512-1513, 1989. https://doi.org/10.1021/ja00186a064\n\n
    7. \n
  7. R.V. Williams, V.R. Gadgil, P. Luger, T. Koritsanszky, and M. Weber, \"The Search for Homoaromatic Semibullvalenes. 6.<sup>1</sup>X-ray Structure and Charge Density Studies of 1,5-Dimethyl-2,4,6,8-semibullvalenetetracarboxylic Dianhydride in the Temperature Range 123\u221215 K\", The Journal of Organic Chemistry, vol. 64, pp. 1180-1190, 1999. https://doi.org/10.1021/jo981703q\n\n
    8. \n
  8. H.S. Yu, X. He, and D.G. Truhlar, \"MN15-L: A New Local Exchange-Correlation Functional for Kohn\u2013Sham Density Functional Theory with Broad Accuracy for Atoms, Molecules, and Solids\", Journal of Chemical Theory and Computation, vol. 12, pp. 1280-1293, 2016. https://doi.org/10.1021/acs.jctc.5b01082\n\n
    9. \n
  9. S. Grimme, A. Hansen, S. Ehlert, and J. Mewes, \"r2SCAN-3c: A \"Swiss army knife\" composite electronic-structure method\", The Journal of Chemical Physics, vol. 154, 2021. https://doi.org/10.1063/5.0040021\n\n
    10. \n
  10. J. Chai, and M. Head-Gordon, \"Long-range corrected hybrid density functionals with damped atom\u2013atom dispersion corrections\", Physical Chemistry Chemical Physics, vol. 10, pp. 6615, 2008. https://doi.org/10.1039/b810189b\n\n
    11. \n
  11. H. Rzepa, \"CAZFUE01 MN15L/Def2-TZVPP => C2 symmetry => bis(homoaromatic) ? Gas phase\", 2026. https://doi.org/10.5281/zenodo.22009539\n\n
    12. \n
  12. H. Rzepa, \"CAZFUE01 => C2 symmetry => bis(homoaromatic) ? STABLE wavefunction? Gas phase\", 2026. https://doi.org/10.5281/zenodo.22009550\n\n
    13. \n
  13. H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state\", 2026. https://doi.org/10.5281/zenodo.22012011\n\n
    14. \n
  14. H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state Gas phase IRC\", 2026. https://doi.org/10.5281/zenodo.22012031\n\n
    15. \n
  15. H. Rzepa, \"ICILAI MN15L /Def2-TZVPP = TS (nu -31 cm-1). Gas phase\", 2026. https://doi.org/10.5281/zenodo.22009559\n\n
    16. \n
\n\n
","doi":"https://doi.org/10.59350/sjyby-4yw41","guid":"https://www.ch.ic.ac.uk/rzepa/blog/?p=31787","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787184000,"reference":[{"id":"https://doi.org/10.59350/cq2a3-g2g35","unstructured":"H. Rzepa, \"Predicted properties of a candidate for a frozen semibullvalene.\", 2012."},{"id":"https://doi.org/10.59350/585c3-dpy86","unstructured":"H. Rzepa, \"Frozen Semibullvalene: a holy grail (and a bis-homoaromatic molecule).\", 2012."},{"id":"https://doi.org/10.59350/8nkna-ycy23","unstructured":"H. Rzepa, \"The ten-electron homologue of semibullvalene.\", 2012."},{"id":"https://doi.org/10.1021/ja0579208","unstructured":"C. Wang, J. Yuan, G. Li, Z. Wang, S. Zhang, and Z. Xi, \"Metal-Mediated Efficient Synthesis, Structural Characterization, and Skeletal Rearrangement of Octasubstituted Semibullvalenes\", Journal of the American Chemical Society, vol. 128, pp. 4564-4565, 2006."},{"id":"https://doi.org/10.1039/c3qo00019b","unstructured":"S. Zhang, M. Zhan, Q. Wang, C. Wang, W. Zhang, and Z. Xi, \"Synthesis of semibullvalene derivatives via Co 2 (CO) 8 -mediated cyclodimerization of 1,4-dilithio-1,3-butadienes\", Org. Chem. Front., vol. 1, pp. 130-134, 2014."},{"id":"https://doi.org/10.1021/ja00186a064","unstructured":"L.M. Jackman, A. Benesi, A. Mayer, H. Quast, E.M. Peters, K. Peters, and H.G. Von Schnering, \"The Cope rearrangement of 1,5-dimethylsemibullvalene-2,6- and 3,7-dicarbonitriles in the solid state\", Journal of the American Chemical Society, vol. 111, pp. 1512-1513, 1989."},{"id":"https://doi.org/10.1021/jo981703q","unstructured":"R.V. Williams, V.R. Gadgil, P. Luger, T. Koritsanszky, and M. Weber, \"The Search for Homoaromatic Semibullvalenes. 6.1X-ray Structure and Charge Density Studies of 1,5-Dimethyl-2,4,6,8-semibullvalenetetracarboxylic Dianhydride in the Temperature Range 123\u221215 K\", The Journal of Organic Chemistry, vol. 64, pp. 1180-1190, 1999."},{"id":"https://doi.org/10.1021/acs.jctc.5b01082","unstructured":"H.S. Yu, X. He, and D.G. Truhlar, \"MN15-L: A New Local Exchange-Correlation Functional for Kohn\u2013Sham Density Functional Theory with Broad Accuracy for Atoms, Molecules, and Solids\", Journal of Chemical Theory and Computation, vol. 12, pp. 1280-1293, 2016."},{"id":"https://doi.org/10.1063/5.0040021","unstructured":"S. Grimme, A. Hansen, S. Ehlert, and J. Mewes, \"r2SCAN-3c: A \"Swiss army knife\" composite electronic-structure method\", The Journal of Chemical Physics, vol. 154, 2021."},{"id":"https://doi.org/10.1039/b810189b","unstructured":"J. Chai, and M. Head-Gordon, \"Long-range corrected hybrid density functionals with damped atom\u2013atom dispersion corrections\", Physical Chemistry Chemical Physics, vol. 10, pp. 6615, 2008."},{"id":"https://doi.org/10.5281/zenodo.22009539","unstructured":"H. Rzepa, \"CAZFUE01 MN15L/Def2-TZVPP => C2 symmetry => bis(homoaromatic) ? Gas phase\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22009550","unstructured":"H. Rzepa, \"CAZFUE01 => C2 symmetry => bis(homoaromatic) ? STABLE wavefunction? Gas phase\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22012011","unstructured":"H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22012031","unstructured":"H. Rzepa, \"CAZFUE01 wB97XD/Def2-TZVPP => C2 symmetry => bis(homoaromatic) transition state Gas phase IRC\", 2026."},{"id":"https://doi.org/10.5281/zenodo.22009559","unstructured":"H. Rzepa, \"ICILAI MN15L /Def2-TZVPP = TS (nu -31 cm-1). Gas phase\", 2026."}],"rid":"gtbbg-j6r70","summary":"I have in the past (around 2012 to be specific) taken an interest in a particular type of [3,3]sigmatropic pericyclic reaction called the semibullvalene rearrangement.,,. This system can apparently exhibit very long C-C bonds in the region of 2.1\u00c5, in which form it would be called a \"frozen\" transition state, also referred to a bis-homoaromatic [\u2026]","tags":["Crystal_structure_mining","Pericyclic","Reaction Mechanism"],"title":"How long can a C-C bond get? Semibullvalenes \u2013 genuine bis-homoaromatic molecules or are they [3,3] sigmatropic transition states.","updated_at":1787734490,"url":"https://www.ch.ic.ac.uk/rzepa/blog/?p=31787","version":"v1"},{"authors":[{"contributor_roles":[],"family":"Crueger","given":"Jens"}],"blog":{"authors":[{"name":"Redaktion iRights.info"}],"community_id":"7d3b25fd-a4a8-4155-8e76-99d6be06706a","created":1694736000,"current_feed_url":null,"description":"Urheberrecht und kreatives Schaffen in der digitalen Welt","doi":"https://doi.org/10.59350/irights","favicon":"https://rogue-scholar.org/api/communities/7d3b25fd-a4a8-4155-8e76-99d6be06706a/logo","feed_format":"application/atom+xml","feed_url":"https://irights.info/feed/atom","filter":null,"generator":"Other","home_page_url":"https://irights.info/","issn":null,"language":"deu","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"irights","status":"active","subfield":"3308","title":"iRights.info","updated":1787730867,"use_api":false},"blog_name":"iRights.info","blog_slug":"irights","content_html":"

Im Bereich der Offenen Bildungsmaterialien sind Fragen rund um das Urheberrecht und K\u00fcnstliche Intelligenz ein Dauerbrenner. iRights.info hat als Kooperationspartnerin von OERinfo in den vergangenen Jahren zahlreiche Blogbeitr\u00e4ge hierzu beigesteuert. Der folgende Artikel gibt einen thematischen \u00dcberblick und soll als Orientierungshilfe dienen.\u00a0

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M\u00f6glichkeiten zur urheberrechtsfreien Nutzung von Bildungsinhalten

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KI und OER

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Creative-Commons-Lizenzen f\u00fcr OER-Materialien

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Creative-Commons-Module

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\u00c4nderungen und R\u00fccknahmen

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Besonderheiten und Herausforderungen

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Wo findet man Material?

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Ausblick f\u00fcr OER und das Urheberrecht

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Die K\u00fcnstliche Intelligenz fordert das Urheberrecht aktuell sehr heraus, und schafft damit auch im Kontext der Freien Bildungsmaterialien viele neue Fragen. Die Kooperation zwischen OERinfo und iRights.info wird daher auch in Zukunft spannende Themen bieten.

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Hinweis: Dieser Beitrag ist Teil einer Kooperation von\u00a0iRights.info, dem\u00a0Deutschen Bildungsserver\u00a0und\u00a0OERinfo. Der Text stammt von Jens Crueger, steht unter der Lizenz CC BY 4.0\u00a0und wurde zun\u00e4chst bei\u00a0OERinfo\u00a0ver\u00f6ffentlicht.

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Sie m\u00f6chten iRights.info unterst\u00fctzen?

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iRights.info\u00a0informiert und erkl\u00e4rt rund um das Thema \"Urheberrecht und Kreativit\u00e4t in der digitalen Welt\". Alle Texte erscheinen kostenlos und offen lizenziert.

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Wenn Sie m\u00f6gen, k\u00f6nnen Sie uns \u00fcber die\u00a0gemeinn\u00fctzige\u00a0Spendenplattform Betterplace\u00a0unterst\u00fctzen und daf\u00fcr eine Spendenbescheinigung erhalten. Betterplace akzeptiert PayPal, Bankeinzug, Kreditkarte, paydirekt oder \u00dcberweisung.

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Besonders freuen wir uns \u00fcber einen regelm\u00e4\u00dfigen Beitrag, beispielsweise als monatlicher Dauerauftrag.\u00a0F\u00fcr Ihre Unterst\u00fctzung dankt Ihnen herzlich der\u00a0gemeinn\u00fctzige iRights e.V.!

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DOI f\u00fcr diesen Text: \u00a0\u00b7 automatische DOI-Vergabe f\u00fcr Blogs \u00fcber The Rogue Scholar

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The post OER und das Urheberrecht \u2013 ein \u00dcberblick der Beitr\u00e4ge von iRights.info appeared first on iRights.info.

","doi":"https://doi.org/10.59350/cry6m-afz94","guid":"https://irights.info/?post_type=custom_artikel&p=32896","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787702400,"rid":"0xssx-9tw81","summary":"Im Bereich der Offenen Bildungsmaterialien sind Fragen rund um das Urheberrecht und K\u00fcnstliche Intelligenz ein Dauerbrenner. iRights.info hat als Kooperationspartnerin von OERinfo in den vergangenen Jahren zahlreiche Blogbeitr\u00e4ge hierzu beigesteuert. Der folgende Artikel gibt einen thematischen \u00dcberblick und soll als Orientierungshilfe dienen.","tags":["Allgemein","Bildung + OER","Generative KI","In Eigener Sache","K\u00fcnstliche Intelligenz"],"title":"OER und das Urheberrecht \u2013 ein \u00dcberblick der Beitr\u00e4ge von iRights.info","updated_at":1787731843,"url":"https://irights.info/artikel/urheberrecht-ueberblick-der-beitraege/32896","version":"v1"},{"authors":[{"contributor_roles":[],"family":"Neylon","given":"Cameron","url":"https://orcid.org/0000-0002-0068-716X"}],"blog":{"authors":[{"name":"Cameron Neylon","url":"https://orcid.org/0000-0002-0068-716X"}],"community_id":"57bf5fb9-8f97-4a80-83d7-c6a1910c7e8e","created":1707696000,"current_feed_url":null,"description":"The online home of Cameron Neylon","doi":"https://doi.org/10.59350/cameronneylon","favicon":"https://rogue-scholar.org/api/communities/57bf5fb9-8f97-4a80-83d7-c6a1910c7e8e/logo","feed_format":"application/atom+xml","feed_url":"https://cameronneylon.net/feed/atom/","filter":null,"generator":"WordPress","home_page_url":"https://cameronneylon.net","issn":null,"language":"eng","license":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"cameronneylon","status":"active","subfield":"1802","title":"Science in the Open","updated":1787726875,"use_api":true},"blog_name":"Science in the Open","blog_slug":"cameronneylon","content_html":"

This was originally a script for a video I recorded for a meeting of the Australian Deans and Directors of Creative Arts (DDCA) group. It is addressed to those who are in institutional positions who need to make judgements about the qualities of research outputs in Humanities and Social Sciences with a particular focus on outputs that are “non-traditional” (actually often very “traditional” in their field!) or otherwise “not easily measurable by a STEM audience”.

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In my view there are two key roles for those specifically engaged in supporting those doing HSS research. The first is to advocate for financial systems that can support small and numerous research projects and the funders who want to support them. The second key role is to defend the diversity of research practices, outputs and impacts in HSS and to create a meaningful narrative around their qualities for institutional audiences.

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I'm going to focus on the second here, but I wanted to link both to underline the point that what is of value in HSS research is precisely its diversity, and its difference from the homogeneity and scale of conventional STEM research and its outputs. There is not infrequently a greater diversity of research outputs from single HSS groups, centres and departments than there is from entire faculties of science, engineering and medicine.

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That diversity is at the core of the value that HSS research and scholarship brings to the table. 

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Every social epistemology of knowledge from Latour to Longino via Merton, Ravetz, Kuhn and Fleck have at their heart the idea that the core is the negotiation of knowledge across boundaries, or between groups. This places diversity, of all kinds, at the heart of this process, and linked to it the institutional systems that keep it alive. Arguably it is the purpose of a university to support and bring into contact diverse approaches, experiences and ways of knowing.

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The issue of course is that managing that diversity is a challenge. At the scale of a university, systems are a necessity. Consistency is needed and economies of scale are real. Particularly in HSS but across other disciplines as well, it is impossible for any leader to be across the detail of how good every specific body of work is. If you believe in the argument for diversity then this as it should be – anything else would be a sign of insufficient diversity. That doesn't mean that leaders can't be effective at telling the stories about why diverse research matters. Nor does it mean that they can't make judgement calls on the distribution of resources. But it means those decisions are subjective and contextual. And that the evidence that supports them will be specific to each case.

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But that doesn't solve the problem either. So what are the pragmatic and principled approaches available to addressing this complexity? In my view the key lies in separating out the challenge into two parts, one relatively straightforward and immediately useful, the other more complex but I would argue ultimately tractable.

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An important, but oddly overlooked distinction in research evaluation and particularly technology discussions is the distinction between tracking outputs and evaluating them. There is often a tendency to lump these together and to imagine for example, that if scholarly books were better tracked then that would necessarily mean there would be improved citation data for them. The homogeneity of STEM research outputs means that issues with data coverage and completeness are often conflated to the question \"is it indexed\" using the presence of a specific journal in a specific database both as a reliable marker of quality itself but also of confidence in the quality and relevance of generally accepted performance data.

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So, although this is an oversimplification, in STEM the tracking of outputs is standardised and homogenous. You look it up in an index like Web of Science.

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In HSS, and particularly for creative works, the situation is far more complex. Institutions generally have very poor data on the scope and volume of creative outputs, or other forms of (so-called) \"non-traditional\" outputs. Work done by Niamh Quigley, within the COKI team (Quigley, 2022) showed generally used recording systems (systems like Symplectic, Pure and the like) tended to be poor at capturing aspects of research outputs important to creative researchers. Further, there was a tendency for the information that was manually inputted by researchers (that they care enough to type in!) to be stripped away as it made its way through institutional systems to the data warehouses used for high level analysis.

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From a systems perspective what is needed is systems that make it easy for creative practice researchers to register outputs, to flexibly record the evidence that they consider important about the qualities of these works, and to also make it easy for institutions in turn to gather that information up. Recent technical developments provide improved paths to making this happen.

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The Open Research Contributor and ID (ORCID) system provides a mechanism for researchers to authoritatively identify themselves, and to record outputs they have contributed to. In 2025 ORCID have increased the number of work types (Petro, 2025) to include a range relevant in humanities (including images, video, designs, sound and other creative works) as well as improving the mapping of some other relevant work types including reports. A researcher can choose what works they make visible, and thereby designate as \"research\". This is an important distinction for some creative workers. Institutions can then harvest those outputs without requiring further work from researchers.\u00a0

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ORCID doesn't solve all the problems though. Badly implemented as an institutional system it is yet another place creative researchers have to battle through manually adding their work while colleagues in STEM subjects have it all done for them by journal publishers. Critical to making this work is a commitment from you and your teams that ORCID be the only place researchers have to make sure their work is available and pulling that information from ORCID is an institutional responsibility.

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But that still leaves the manual input issue. There isn't – currently – a complete solution for that (although one – or several – could be built) but there is at least a solution that offers some additional value for creative researchers. Zenodo is a large scale repository, managed by CERN (yes the particle accelerator in Switzerland CERN) that offers a place for anyone to deposit research outputs. It provides a safe, publicly accessible platform from which researchers can showcase their work. It even allows for dark deposit for those creative researchers who need to restrict access to the core of their work for artistic, ethical or commercial reasons.

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Most importantly Zenodo provides DataCite DOIs and this means that – while you do have to manually put information into Zenodo – that information can automatically flow through to ORCID. One place to input the information and then it can flow to the other places it needs to be.

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This flow of information should be the case for any repository that integrates with DataCite (or Crossref) to provide DOIs. Zenodo is large scale and flexible, but there can be an argument for specialist repositories. I am generally sceptical of the value of creating new local repositories, whether at institutions or nationally, but the key questions to ask of any repository are \"does it integrate with DOI providers\" and \"does it provide the recording functionality creative research practitioners need\"? That flexibility is key and Zenodo has some strengths here that can also help us to address, if not yet fully solve, the second problem.\u00a0

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Creative practice researchers know the reasons that their work is important, and can help provide evidence of that. But that evidence is highly diverse. 

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I know the pressures that institutional leaders face to articulate a comparative quantitative value of research outputs to the rest of the university. And I would argue that we nonetheless need to collectively hold the line that this makes no sense. If you value a diversity of research and researchers, you can't protect that diversity by homogenising the way that value is measured. 

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But that doesn't mean we can't articulate value. It doesn't mean we can't compare how disparate research projects and outputs achieve specific goals. It just means, in the best tradition of HSS scholarship, that the evidence that we use is contextual. That it is diverse.

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And here is how repositories like Zenodo can help. Where they support the creation of packages of work, researchers can bundle up the work itself with evidence of its value and impact. This will start unstructured, but over time, and in collaboration with research communities it will be possible to develop some standards. For specific cases. Where appropriate. This might mean giving some background on the gallery that invited an exhibition, the footfall or an audience survey. It might be details of the film festival that selected a documentary for screening, or audience numbers when it was syndicated or broadcast. It might be structured in a particular way to make it easier to process (or even generate). But the key is to build on systems that always allow for the flexibility of a narrative statement that allows for the flexibility that research statements already provide. 

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This workflow places researchers in control, gives them flexibility they need to provide access and to evidence the value of their work. It provides a single point of entry from which communities, institutions, and others can draw in the data to help track those outputs and collate the evidence of their value. It is not controlled by corporate interests but by academic communities. It is not subject to the funding whims of one national government but an international set of consortia.

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Perhaps best of all, this is an area where the humanities and social sciences can lead. It solves a problem by putting researchers in control while supporting institutional needs. It helps and simplifies monitoring while offering a path to gathering more sophisticated evidence to tell better stories. These are not problems that are restricted to HSS, but you could argue that much of STEM evaluation has lost its way, focusing on numbers instead of substance, journal lists instead of journal content, impact factors instead of actual impact. This recontextualisation, and re-situation is where humanities and social sciences scholars, and leadership can show a way to better forms of evaluation.

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References

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","doi":"https://doi.org/10.59350/gtm23-qy713","guid":"https://cameronneylon.net/?p=20122","language":"en","license":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","published_at":1787702400,"reference":[{"id":"https://info.orcid.org/new-work-types/","unstructured":"Petro, J. 2025. ORCID and Humanities: Celebrating the New Year with New Work Types. ORCID Blog. ORCID. ."},{"id":"https://doi.org/10.5281/zenodo.6501506","unstructured":"Quigley, N. 2022. Increasing the visibility of grey literature: Project report (Version 1). Zenodo. ."}],"rid":"h59g6-h3b89","summary":"This was originally a script for a video I recorded for a meeting of the Australian Deans and Directors of Creative Arts (DDCA) group.","tags":["Institution","Peer Review","Research-evaluation"],"title":"Tracking, Valuing and Evaluating the Diversity of HSS Research Outputs","updated_at":1787731729,"url":"https://cameronneylon.net/blog/tracking-valuing-and-evaluating-the-diversity-of-hss-research-outputs/","version":"v1"},{"authors":[{"affiliation":[{"id":"https://ror.org/05a28rw58","name":"ETH Zurich"}],"contributor_roles":[],"family":"Rutz","given":"Adriano","url":"https://orcid.org/0000-0003-0443-9902"}],"blog":{"authors":[{"name":"Adriano Rutz","url":"https://orcid.org/0000-0003-0443-9902"}],"community_id":"9d85a476-b411-4d80-89d5-500bb0f3750d","created":1780876800,"current_feed_url":null,"description":"Personal website of Adriano Rutz","doi":"https://doi.org/10.59350/adafede","favicon":"https://rogue-scholar.org/api/communities/9d85a476-b411-4d80-89d5-500bb0f3750d/logo","feed_format":"application/feed+json","feed_url":"https://adafede.github.io/posts.json","filter":null,"generator":"Other","home_page_url":"https://adafede.github.io","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":null,"slug":"adafede","status":"active","subfield":"1312","title":"Adriano Rutz","updated":1787700179,"use_api":null},"blog_name":"Adriano Rutz","blog_slug":"adafede","content_html":"

I have finally opened a Posts section on my website! Every post should now automatically get a DOI.

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This is something I have wanted to do for a long time, largely inspired by the tireless and consistent example set by Egon Willighagen (Willighagen 2024b, 2024a, 2025).

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It was today's post of (Fenner 2025) that finally motivated me to look into it again. That led me down a productive rabbit hole to set up Rogue Scholar: first landing on (Csefalvay 2023)'s excellent guide, and then (Fruehwald 2025)'s clear write-up, both of which made the process of integrating Rogue Scholar into a Quarto-based site surprisingly smooth.

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All the changes are documented in the following commit:

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https://github.com/Adafede/adafede.github.io/commit/bc2dfe6f

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If you care about attribution, long-term archiving, DOIs and metadata, I highly recommend looking into Rogue Scholar.

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Edit (1): I realized that integrating CiTO could be a significant enhancement. With some effort (and thanks again to Egon), I managed to implement a working solution for the HTML and PDF outputs, see (Willighagen 2023). However, the solution for the XML feed still feels suboptimal.

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Edit (2): After some help from Egon and Martin, I could improve my feed with correct CiTO annotations and their cool custom json feed, see: https://adafede.github.io/posts.json!

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References

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\nCsefalvay, Chris von. 2023. Auto-DOI for Quarto Posts via Rogue Scholar. http://dx.doi.org/10.59350/5hxdg-fz574.\n [cito:obtainsBackgroundFrom]
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\nFenner, Martin. 2025. Rogue Scholar Citation Tracking Launches to Production. http://dx.doi.org/10.53731/zyg15-qv911.\n [cito:obtainsBackgroundFrom]
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\nFruehwald, Josef. 2025. Setting up Rogue Scholar. http://dx.doi.org/10.59350/3fp6d-e6z90.\n [cito:usesMethodIn]
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\nWillighagen, Egon. 2023. \"Two Years of Explicit CiTO Annotations.\" Journal of Cheminformatics 15 (1). https://doi.org/10.1186/s13321-023-00683-2.\n [cito:usesMethodIn]
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\nWillighagen, Egon. 2024a. FAIR Blog-to-Blog Citations. http://dx.doi.org/10.59350/er1mn-m5q69.\n [cito:cites]
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\nWillighagen, Egon. 2024b. GoatCounter, Rogue Scholar and More New Things. http://dx.doi.org/10.59350/8x2f1-h6d21.\n [cito:cites]
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\nWillighagen, Egon. 2025. Blog Updates. http://dx.doi.org/10.59350/cf885-kee54.\n [cito:cites]
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Reuse

CC BY 4.0

Citation

BibTeX citation:
@online{rutz2025,\n  author = {{Adriano Rutz}},\n  title = {Open {Science} {Upgrade:} {Adding} {Blog} {Posts} to My\n    {Website} and {Linking} to {Rogue} {Scholar}},\n  date = {2025-08-04},\n  url = {https://adafede.github.io/posts/2025-08-04_rogue_scholar.html},\n  doi = {10.59350/yckwd-9vm79},\n  langid = {en}\n}\n
For attribution, please cite this work as:
\nAdriano Rutz. 2025. \"Open Science Upgrade: Adding Blog Posts to My\nWebsite and Linking to Rogue Scholar.\" August 4. https://doi.org/10.59350/yckwd-9vm79.\n
","doi":"https://doi.org/10.59350/yckwd-9vm79","guid":"https://doi.org/10.59350/yckwd-9vm79","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1754265600,"reference":[{"id":"https://doi.org/10.59350/5hxdg-fz574","unstructured":"[cito:obtainsBackgroundFrom]"},{"id":"https://doi.org/10.53731/zyg15-qv911","unstructured":"[cito:obtainsBackgroundFrom]"},{"id":"https://doi.org/10.59350/3fp6d-e6z90","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.1186/s13321-023-00683-2","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.59350/er1mn-m5q69","unstructured":"[cito:cites]"},{"id":"https://doi.org/10.59350/8x2f1-h6d21","unstructured":"[cito:cites]"},{"id":"https://doi.org/10.59350/cf885-kee54","unstructured":"[cito:cites]"}],"rid":"9hzx0-g6543","summary":"I have finally opened a Posts section on my website! Every post should now automatically get a DOI.","tags":["Open Science"],"title":"Open Science Upgrade: Adding Blog Posts to my Website and Linking to Rogue Scholar","updated_at":1787720776,"url":"https://adafede.github.io/posts/2025-08-04_rogue_scholar.html","version":"v1"},{"authors":[{"affiliation":[{"id":"https://ror.org/05a28rw58","name":"ETH Zurich"}],"contributor_roles":[],"family":"Rutz","given":"Adriano","url":"https://orcid.org/0000-0003-0443-9902"}],"blog":{"authors":[{"name":"Adriano Rutz","url":"https://orcid.org/0000-0003-0443-9902"}],"community_id":"9d85a476-b411-4d80-89d5-500bb0f3750d","created":1780876800,"current_feed_url":null,"description":"Personal website of Adriano Rutz","doi":"https://doi.org/10.59350/adafede","favicon":"https://rogue-scholar.org/api/communities/9d85a476-b411-4d80-89d5-500bb0f3750d/logo","feed_format":"application/feed+json","feed_url":"https://adafede.github.io/posts.json","filter":null,"generator":"Other","home_page_url":"https://adafede.github.io","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":null,"slug":"adafede","status":"active","subfield":"1312","title":"Adriano Rutz","updated":1787700179,"use_api":null},"blog_name":"Adriano Rutz","blog_slug":"adafede","content_html":"

Five years ago, LOTUS (Rutz et al. 2022) started as a small attempt to cultivate the flow of chemical knowledge, in the same way we study how metabolites flow through living systems, rather than to build yet another database.

\n

The idea was simple. Natural products data should be open, structured, reusable, and belong to everyone.

\n

Like many community-driven efforts, LOTUS had bursts of activity, long pauses, and years of invisible maintenance. From the outside, silence can look like disappearance. From the inside, it usually means people are still doing the work; slowly, carefully, and often without announcements.

\n
\n

From isolated datasets to global outreach

\n

The early focus of LOTUS was necessarily inward: assembling data, cleaning records, releasing versions. We built a website, curated entries, and archived releases.

\n

But we slowly realized something uncomfortable: data stored in a repository, even a good one, does not automatically live.

\n

Archiving on Zenodo (https://zenodo.org/communities/the-lotus-initiative) was the right thing to do, but archived data is mostly silent data. It waits to be discovered, and versioning remains labor-intensive.

\n

What we really needed were entry points where people already were.

\n

Wikipedia , Wikidata , and Scholia building on top of it are not dissemination platforms in the classical sense. They are circulatory systems. They persist because communities maintain them.

\n

The Scholia Chemistry preprint (Willighagen et al. 2025) co-authored with Egon , Denise , Daniel , and Finn belongs to this continuity. It does not introduce a new platform. It offers a lens for communities to see what they already collectively know.

\n
\n

Making knowledge visible: the Wikipedia P703 module

\n
\n

Knowledge needs channels, not just reservoirs.

\n
\n

One important step was enabling Wikipedia articles and infoboxes to directly access found in taxon (P703) relationships from Wikidata in an efficient way.

\n

This sounds like a small technical detail. It is not.

\n

The idea had circulated quietly for years, in hallway conversations, chats, and conferences. I also mentioned it during the WikiCite 2025 conference last August, but it took time before conditions were right. Infrastructure work rarely happens on schedule. It almost never happens on stage. It happens in version histories, talk pages, and tiny edits that fix one Lua bug, enabling thousands of articles to improve forever.

\n

Once data is in Wikidata, it can flow into thousands of chemical articles, in dozens of languages, without duplication or translation overhead. It becomes visible to non-experts, students, and readers who will never see a database interface. This is how open data becomes public knowledge.

\n

These modules are now available on multiple Wikipedias:

\n\n

If you speak another language, feel free to copy them and increase their use.

\n

Initially, I tried to reuse existing modules, and quickly learned why module reuse across Wikipedias is famously difficult. Each wiki evolves its own ecosystem of dependencies, conventions, and technical debt. So the modules were written fully contained, independent of language-specific infrastructure. Only lines that need to be changed are the language-specific translations at the top of the module, trying to follow 18n.

\n

These modules are not a new website or a new interface. They are simply better plumbing.

\n
\n
\n

\n
Screenshot of the P703 module on English Wikipedia
\n
\n
\n

By default, only 5 organisms are shown, keeping the text clean and readable. But the magic is in how the module handles the rest: each taxon links to its Wikipedia article, and if no article exists in the current language, the module gracefully redirects to an equivalent page in another wiki. A beautiful example of this is war for Quassia africana.

\n
\n
\n

Reaching non-experts

\n
\n

Not everyone wants to learn SPARQL.

\n
\n

I have heard this sentiment countless times. Regardless of personal preferences, if we want the data to truly live, it must reach as many people as possible.

\n

Small tools like the LOTUS Wikidata Explorer help lower that barrier. It is imperfect. It is still growing. But it already allows chemists, curators, and students to access and export data in formats they can actually use.

\n

The principle is simple: knowledge only flows when it reaches people. The data must be seen, explored, and reused. Only then does it fulfill its purpose.

\n
\n
\n

\n
Screenshot of the LOTUS Wikidata Explorer interface
\n
\n
\n

On a more technical note, the LOTUS Wikidata Explorer leverages the powerful IDSM endpoint (Galgonek and Vondr\u00e1\u0161ek 2021), which allows for chemical similarity searches thanks to Sachem (Kratochv\u00edl et al. 2018). Its speed for large-scale queries could never have been reached without QLever (Bast and Buchhold 2017), and chemical depictions come from CDK Depict.

\n

It returns structured metadata for traceability and reproducibility, together with hashes that uniquely identify the query and its results. It can be queried programmatically via simple API calls, for example ?taxon=Gentianaceae or ?smiles=c1ccccc1&formula_filter=true&f_state=required. It works directly in the browser without requiring heavy dependencies, almost everything works out of the box.

\n

Alternatively, users can take advantage of a local version, for example to extract a small, personal knowledge graph in TTL format, or to export all or selected LOTUS data in more chemistry-friendly formats such as JSON or CSV, ready for analysis, visualization, or integration into other workflows.

\n

For example, to export a complete or filtered snapshot locally:

\n
\n
uvx \\\n  --from \\\n  git+https://github.com/adafede/marimo \\\n  lotus_wikidata_explorer \\\n  export \\\n  --taxon \"*\" \\   # to get all taxa, else \"Gentianaceae\", for example\n  --format csv \\  # also supports json, ttl\n  --output 20260119_lotus.csv.gz \\\n  --compress \\\n  --verbose
\n
\n

And if you are curious where halogenated compounds appear most often, you can simply ask:

\n
\n
xan dedup 20260119_lotus.csv.gz \\\n  --select compound_inchikey,molecular_formula,taxon_name | \\\n  xan select compound_inchikey,molecular_formula,taxon_name | \\\n  xan filter \"contains(molecular_formula, 'Br') or\n              contains(molecular_formula, 'Cl') or\n              contains(molecular_formula, 'F') or\n              contains(molecular_formula, 'I')\" | \\\n  xan filter '!contains(molecular_formula, \"Fe\")' | \\\n  xan freq -s taxon_name | \\\n  xan hist -l value -R
\n
\n
\n
Histogram for taxon_name (bars: 11, sum: 11,604, max: 10,060):\n\nStreptomyces            |   374   3.22%|\u25a0\u25a0\u25a0\u25a0                                                                                                   |\nLaurencia dendroidea    |   314   2.71%|\u25a0\u25a0\u25a0\u25a0                                                                                                   |\nLaurencia obtusa        |   184   1.59%|\u25a0\u25a0                                                                                                     |\nPseudoceratina purpurea |   112   0.97%|\u25a0\u25a0                                                                                                     |\nAplysia dactylomela     |    99   0.85%|\u25a0\u25a0                                                                                                     |\nNostoc                  |    99   0.85%|\u25a0\u25a0                                                                                                     |\nLaurencia nipponica     |    95   0.82%|\u25a0                                                                                                      |\nPortieria hornemannii   |    94   0.81%|\u25a0                                                                                                      |\nLyngbya majuscula       |    88   0.76%|\u25a0                                                                                                      |\nChaetomium globosum     |    85   0.73%|\u25a0                                                                                                      |\n<rest>                  |10,060  86.69%|\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0\u25a0|
\n
\n
\n
\n
\n

Making flow reliable: curation and standards

\n
\n

At some point, flow only runs if it is maintained.

\n
\n

As I do not post as often as I probably should, here are some other pointers to related work and discussions from the past months, for those who want to follow the flow a bit further:

\n
\n

Blue Obelisk

\n\n
\n
\n

Reactions flow

\n

Recently, I also contributed to improving how chemical reactions are modeled in Wikidata.

\n

Previously, many reactions were modeled as instances of \"chemical reaction\", which violated disjointness, see (Do\u01e7an and Patel-Schneider 2025).

\n

The introduction of type of chemical reaction now allows reactions to be classified more precisely, while preserving their hierarchy using subclass of.

\n
\n
\n

Wikifunctions

\n

Out of curiosity, I also made a small contribution to chemistry-related functions in Wikifunctions: Z30950. It validates CAS Registry Numbers. It does one thing, and it does it reliably.

\n

It is tiny. But it is a seed.

\n
\n
\n
\n

Looking forward: flowing knowledge, flowing metabolites

\n

Projects like Wikifunctions and Abstract Wikipedia point to the next phase of open knowledge: knowledge that is not only stored, but executed, reused, and recombined.

\n

A global, open metabolomics knowledge graph is slowly taking shape, one where chemical structures, organisms, reactions, and evidence can finally be traced together.

\n

LOTUS is no longer an initiative. It is one contributor among many in that graph.

\n

If you edit Wikipedia, curate Wikidata, maintain a SPARQL endpoint, write a template, review a module, or fix a tiny detail no one will notice, thank you. This work only matters because you are here.

\n
\n

References

\n
\n
\nBast, Hannah, and Bj\u00f6rn Buchhold. 2017. \"QLever: A Query Engine for Efficient SPARQL+text Search.\" Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, CIKM '17, November, 647\u201356. https://doi.org/10.1145/3132847.3132921.\n [cito:usesMethodIn]
\n
\nDo\u01e7an, Ege Atacan, and Peter F. Patel-Schneider. 2025. \"Disjointness Violations in Wikidata.\" In Knowledge Graphs and Semantic Web. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-81221-7_18.\n [cito:citesAsRecommendedReading]
\n
\nGalgonek, Jakub, and Ji\u0159\u00ed Vondr\u00e1\u0161ek. 2021. \"IDSM ChemWebRDF: SPARQLing Small-Molecule Datasets.\" Journal of Cheminformatics 13 (1). https://doi.org/10.1186/s13321-021-00515-1.\n [cito:usesMethodIn]
\n
\nKratochv\u00edl, Miroslav, Ji\u0159\u00ed Vondr\u00e1\u0161ek, and Jakub Galgonek. 2018. \"Sachem: A Chemical Cartridge for High-Performance Substructure Search.\" Journal of Cheminformatics 10 (1). https://doi.org/10.1186/s13321-018-0282-y.\n [cito:usesMethodIn]
\n
\nRutz, Adriano, Maria Sorokina, Jakub Galgonek, et al. 2022. \"The LOTUS Initiative for Open Knowledge Management in Natural Products Research.\" eLife 11 (May). https://doi.org/10.7554/elife.70780.\n [cito:cites]
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\nWillighagen, Egon. 2025. August. https://doi.org/10.59350/krw9n-dv417.\n [cito:citesAsRecommendedReading]
\n
\nWillighagen, Egon, Denise Slenter, Adriano Rutz, Daniel Mietchen, and Finn Nielsen. 2025. Scholia Chemistry: Access to Chemistry in Wikidata. May. https://doi.org/10.26434/chemrxiv-2025-53n0w.\n [cito:cites]
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Reuse

CC BY 4.0

Citation

BibTeX citation:
@online{rutz2026,\n  author = {{Adriano Rutz}},\n  title = {Cultivating {Knowledge} {Flow} in {Open} {Chemistry}},\n  date = {2026-01-20},\n  url = {https://adafede.github.io/posts/2026-01-20_chem_flow.html},\n  doi = {10.59350/sk00y-3gh44},\n  langid = {en}\n}\n
For attribution, please cite this work as:
\nAdriano Rutz. 2026. \"Cultivating Knowledge Flow in Open\nChemistry.\" January 20. https://doi.org/10.59350/sk00y-3gh44.\n
","doi":"https://doi.org/10.59350/sk00y-3gh44","guid":"https://doi.org/10.59350/sk00y-3gh44","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1768867200,"reference":[{"id":"https://doi.org/10.1145/3132847.3132921","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.1007/978-3-031-81221-7_18","unstructured":"[cito:citesAsRecommendedReading]"},{"id":"https://doi.org/10.1186/s13321-021-00515-1","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.1186/s13321-018-0282-y","unstructured":"[cito:usesMethodIn]"},{"id":"https://doi.org/10.7554/elife.70780","unstructured":"[cito:cites]"},{"id":"https://doi.org/10.59350/krw9n-dv417","unstructured":"[cito:citesAsRecommendedReading]"},{"id":"https://doi.org/10.26434/chemrxiv-2025-53n0w","unstructured":"[cito:cites]"}],"rid":"80nkb-cq953","summary":"Five years ago, LOTUS (Rutz et al. 2022) started as a small attempt to cultivate the flow of chemical knowledge, in the same way we study how metabolites flow through living systems, rather than to build yet another database.","tags":["Chemistry","LOTUS","Open Science","Wikidata"],"title":"Cultivating Knowledge Flow in Open Chemistry","updated_at":1787701339,"url":"https://adafede.github.io/posts/2026-01-20_chem_flow.html","version":"v1"},{"authors":[{"contributor_roles":[],"family":"Richardson","given":"Reese"}],"blog":{"authors":null,"community_id":"40570e0b-b289-4145-9c60-6fb881efaa45","created":1721779200,"current_feed_url":null,"description":"Case studies in scientific reproducibility","doi":"https://doi.org/10.59350/reeserichardson","favicon":"https://rogue-scholar.org/api/communities/40570e0b-b289-4145-9c60-6fb881efaa45/logo","feed_format":"application/atom+xml","feed_url":"https://reeserichardson.blog/feed/atom","filter":null,"generator":"WordPress.com","home_page_url":"https://reeserichardson.blog","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.59350","relative_url":null,"secure":true,"slug":"reeserichardson","status":"active","subfield":"1802","title":"Reese Richardson","updated":1787662200,"use_api":false},"blog_name":"Reese Richardson","blog_slug":"reeserichardson","content_html":"

On May 17, 2026, Sholto David identified one fabricated image presented as validation data in Thermo Fisher's antibody catalog. By May 28, we had identified more than 100 fabricated images, which expanded to more than 450 images in Thermo Fisher's catalog and one in Abcam's catalog by June 3 (see my previous blog post). We set up a Zenodo repository to collect all these instances of apparent manipulation of antibody validation data and a form for others to report suspicious images in vendor's antibody validation data that they had found themselves.

\n

Understandably, this revelation prompted considerable outrage among biomedical scientists, as reported by Nature, Chemistry World, The Scientist, GenomeWeb and others. Phillip Broadwith, Business editor for Chemistry World, summarizes: \"The discovery of extensive manipulation in Western blot images used by laboratory supply giant Thermo Fisher Scientific as verification data for antibody reagents has led to a serious breakdown of trust between the company and its customers.\"

\n

This update is to say that this newfound distrust should probably extend to a good fraction of the research antibody industry at large. Our repository now contains 18,943 images presented as validation data for 17,495 unique antibody products sold by 15 different vendors1. In order of discovery, these vendors are:

\n\n

Below, I summarize the findings for each company and provide a short postscript detailing my own opinion about what should happen from here. Note that while I have tried to document as many instances of apparent manipulation as possible, the figures shown here do not represent a complete audit of each company's catalog. Moreover, many images I've reviewed look as though they may have been manipulated, but are too low-resolution for me to offer a confident opinion. I've elected not to include these images in the repository. For all of these images, the best way to know if falsification has occurred is to inspect the original, high-resolution images, which may or may not be available, even to the vendors themselves.

\n

For these reasons, a vendor having a larger or smaller number of manipulated images documented here should not be interpreted as an indication that it has a larger or smaller manipulation problem than the other companies listed here. All of these companies have some level of manipulated images in their catalogs and they should each comprehensively and transparently audit the images in their respective catalogs. Finally, if a vendor is not present here, it is not an indication that their catalog is free of manipulation.

\n

Hundreds of these problematic images were first identified by others, including Sholto David, Elisabeth Bik, Javeria Nishtar, Maxwell Marley, Marvin Bader, HKADolan, Bryan Heit and several community members that prefer to remain anonymous. Many other community members submitted images that they found suspicious, but were too low-resolution for me to make a confident determination and include them in the repository. I want to thank all these people for taking the time to document and report their findings. I encourage readers to report any suspicious validation data they notice in vendor catalogs here.

\n

Vendors frequently use the same validation images as one another, probably reflecting private labeling

\n

It is clear that many of these vendors are using the same images as one another for their own versions of the same product. For instance, this HAS1 antibody from Thermo Fisher uses the same Western blot image as similar products from Millipore Sigma, Novus (R&D Systems) and Boster Bio. I only noticed this because the image used for the HAS1 antibody has the exact same pattern of background noise as a different Western blot image used for a different antibody also sold by Thermo Fisher, implying that at least one of these images is fabricated.

\n
\"\"
My annotation of the problematic images described above.
\n

At least six companies (Thermo Fisher, Abcam, LSBio, Antibodies.com, G-Biosciences and GeneTex) present a Western blot using the exact same \"background pattern A\" as thousands of other antibody products. I described background pattern A in my previous blog post.

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Thermo Fisher's catalog all featuring \"background pattern A\".
\n

If they aren't using the exact same images as one another, different companies will often use images that are so stylistically similar that it is clear that they originated from the same art studio laboratory.

\n
\"\"
Three Western blot validation images from LSBio, Origene and Thermo Fisher, all of which feature a background that has apparently been painted in. Note that the images all feature a two-lane Western blot without lane labels and feature the same molecular weight markers written in the same italic font at the same molecular weights. These images are among hundreds from multiple vendors featuring the same style, many of which also feature signs of apparent painting.
\n

Identical images across multiple vendors probably reflect the industry practicing private labeling, where one manufacturer produces a product that they then sell to other companies to market and sell under their own branding. It appears that the original manufacturer of these antibodies also passed along their validation data to the final vendor, who then placed them on their website.

\n

Thermo Fisher Scientific (5,580 images across 4,819 products)

\n

Thermo Fisher Scientific, headquartered in Waltham, Massachusetts, is probably the world's largest supplier of laboratory equipment and reagents and was the first company that was noted to have presented fabricated images as validation data. In response to the public outrage, Thermo Fisher released a baffling 15-point FAQ wherein they promise an investigation, but repeatedly state that \"antibody images may have been optimized for presentation and clarity on the website\". Shortly after, they revised their FAQ to just seven points. To the carefully-worded question \"Did Thermo Fisher manipulate or fabricate antibody data?\", they emphatically respond:

\n
\n

No. The Company fully stands by the data and underlying science.\u00a0 We are confident in the quality of the products within our antibody catalog and our performance guarantee is valid for products purchased directly from Thermo Fisher Scientific or any of our authorized distributors. For further information, please refer to the Invitrogen\"\u2122\" antibody performance guarantee.

\n
\n

Note that this answer only claims that Thermo Fisher itself did not manipulate or fabricate antibody data, which leaves the company room to offer a clean mea culpa if their review finds that the images were manipulated by a third party. Regardless of which party is responsible for the manipulation, Thermo Fisher used these images to market their products to scientists hungry for antibodies that actually perform as advertised.\u00a0

\n

Around the same time that their FAQ was revised, Thermo Fisher and added a disclaimer to all antibody product pages in small gray type:

\n
\n

Please note: We are reviewing Western blot images included in the antibody testing data in our catalog, including those provided by third parties. Unless expressly labeled or annotated as \"raw-unedited\", Western blot images included in the antibody testing data in our catalog may have been edited, optimized or otherwise adjusted for presentation.

\n
\n

Thus far, I have not seen any images in Thermo Fisher's catalog that are labeled as \"raw-unedited\". Note that Thermo Fisher has not committed to making the findings of their investigation public.

\n

More than a thousand newly-documented images from Thermo Fisher's catalog contain artefacts of \"painting\", where someone presumably has brushed over some undesirable image features in Photoshop or a similar program (some highlights below).

\n
\"\"
A Western blot image presented as validation data for a Thermo Fisher alpha-II spectrin antibody.\u00a0
\n
\"\"
An immunocytochemistry image presented as validation data for a Thermo Fisher XBP1 antibody.
\n
\"\"
A Western blot image presented as validation data for a Thermo Fisher PCMT1 antibody.
\n
\"\"
An immunofluorescence image presented as validation data for a Thermo Fisher APC2 antibody.
\n

Dozens of other images feature duplicated regions of background noise.

\n
\"\"
A Western blot image presented as \"Advanced Verification\" data for a Thermo Fisher CRMP2 antibody.
\n

Thousands of other images feature the same background patterns with the bands repositioned to correspond to the expected molecular weight, as in the previously-documented \"background pattern A\" and \"background pattern B\".

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Thermo Fisher's catalog all featuring \"background pattern C\"
\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Thermo Fisher's catalog all featuring \"background pattern D\", which appears to be a two-lane version of \"background pattern C\".
\n

If 450 images was not enough to convince Thermo Fisher that this is not data they should \"fully stand behind\", maybe 5,000 images will be.

\n
An aside about Thermo Fisher's \"quotations\"
\n

Another way to stoke confidence in buyers that an antibody works as advertised is to show them that other scientists have successfully used it. To that end, most antibody vendors show \"citations\" and \"references\" on product pages, listing published articles wherein the authors state that they used the antibody in their experiments. These product citations are compiled by services like CiteAb, the Antibody Registry and BenchSci. Thermo Fisher's product pages collect citations to the product and provide a short quotation from each describing how the reagent was used.

\n
\"\"
The References section on Thermo Fisher's product page for a XBP1 antibody.
\n

I was alerted to a problem with these citations by a post by Sander Kersten, who complained that:

\n
\n

[Thermo Fisher] is quoting a sentence from our manuscript, written 25 years ago, indicating that we used their antibody. However, we didn't, and the quote is a total fabrication.

\n
\n
\"\"
The reference to Kersten's publication shown on Thermo Fisher's product page for an ANGPTL4 antibody. Note the quotation marks around the apparent excerpt. This reference has since been removed.
\n

The product page makes it appear as if it is quoting directly from Kersten et al. (2000): \"PA1-1053 was used in western blot to investigate the function of PPAR alpha and characterize FIAF during fasting\". The actual relevant quotation from Kersten et al. is \"[t]he polyclonal antibody used was directed against the epitope CQGPKGKDAPFKDSE in the N-terminal region of FIAF. The peptide affinity-purified antibody was generated in rabbit and ordered via Eurogentec's customized antibody production service.\" In other words, Kersten et al. never claim to use the Thermo Fisher product in question. The antibody they used binds the same epitope (amino acid sequence) as PA1-1053 claims, but the authors explicitly state that it came from a different manufacturer.\u00a0

\n

In fact, every single apparent quotation from a product reference on Thermo Fisher's site is not actually from the reference manuscript. For instance, the same product page that misquoted Kersten et al. also makes it appear as if it is quoting directly from Choudhuri et al. (2021): \"PA1-1053 was used in Western Blotting to gain insight into the mechanisms that result in such changes by Tempol in female C3H mice\". The actual relevant quotation from Choudhuri et al. reads \"[f]ollowing transfer to nitrocellulose, samples were probed with primary antibodies ALDH1A1 (ab52492) from Abcam (Waltham, MA), ANGPTL4/FIAF (PA1-1053) from Thermo Fisher Scientific (Waltham, MA) followed by rabbit secondary antibody from Santa Cruz Biotechnology (Dallas, TX), and were visualized by chemiluminescence (PerkinElmer; Billerica, MA)\".

\n

I believe these summaries are AI-generated, but they are clearly presented (in quotation marks, no less) as if they are direct quotations from the manuscript. While product pages on Thermo Fisher are littered with buttons prompting users to \"Ask AI about this product\", users are given no indication that these quotations are AI-generated nor that they are not actually quotations. Every Reference section does have an \"AI-generated summary\" at the top, however, this part is not presented in quotation marks and is clearly disclaimed as being AI-generated, unlike the references themselves.

\n

Moreover, many of these summaries are inaccurate, such as the reference to Kersten et al.! I ran spot-checks of 15 references from another antibody (MA5-14520, Ki-67 Recombinant Rabbit Monoclonal Antibody clone SP6) and found 4 listed references (1, 2, 3, 4) that state that they used a rabbit antibody from Thermo Fisher (or one of the brands acquired by Thermo Fisher) but don't actually specify that it was MA5-14520. Thermo Fisher currently sells 54 antibodies targeting Ki-67 with rabbits as the host organism.

\n

Abcam (185 images across 115 products)

\n

Abcam is based in Cambridge, UK and was acquired by the Danaher Corporation, headquartered in Washington, DC, in 2023. We previously found just one instance of image manipulation in Abcam's catalog (an appearance by \"background pattern A\"). After making this public, Abcam issued a short statement to The Scientist and wordlessly removed the image from the antibody's product page. The product remains for sale.

\n

The newly-documented manipulations contain a lot of patchwork painting of background noise in Western blots, as well as several dozen appearances of background patterns C and D.

\n
\"\"
A Western blot image presented as validation data for an Abcam HSP90 alpha/beta antibody.
\n
\"\"
A Western blot image presented as validation data for an Abcam ADSS2 antibody.
\n

Novus Biologicals / R&D Systems (263 images across 171 products)

\n

Novus Biologicals is a brand owned by R&D Systems, a brand of Bio-Techne, based in Minneapolis, Minnesota. Bio-Techne announced in June that they would be acquired by Merck KGaA, headquartered in Darmstadt, Germany (not to be confused with the American company Merck & Co., Inc.). The images flagged in our repository mostly feature background pattern C and background pattern D.

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from R&D System's catalog all featuring \"background pattern D\". Although the images are heavily compressed, the pattern is distinguishable by a unique set of \"freckles\" in the gel (for instance, see the three dots on the left edge of the image just above the 55 kDa marker).
\n

Proteogenix (362 images across 362 products)

\n

Proteogenix is headquartered in Schiltigheim, France. An anonymous community member noticed that several images in Proteogenix's catalog use the exact same background pattern (which I've called \"background pattern E\"). According to this person, they alerted Proteogenix to the first handful of problematic images that they noticed. Proteogenix apparently answered this courtesy by silently removing the offending images from the catalog (note that since the catalog pages were not previously archived, I cannot independently verify if Proteogenix did indeed remove these images after the community report). This person went on to document 200 additional occurrences of the background pattern in Proteogenix's catalog, after which I found more than 150 more.

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from Proteogenix's catalog all featuring \"background pattern E\". Notice that the single band in the \"R\" lane also appears to be repeatedly reused.
\n

Origene (2,236 images across 1,959 products)

\n

Origene is headquartered in Rockville, Maryland. Most of their newly-documented image manipulations contain evidence of background painting.\u00a0

\n
\"\"
A Western blot image presented as validation data for an Origene SMAD1 antibody.
\n
\"\"
A Western blot image presented as validation data for an Origene SERPINB1 antibody.
\n
\"\"
An immunofluorescence image presented as validation data for an Origene HRASLS3 antibody.
\n
\"\"
Three Western blot images used by Origene that share the same repetitive background. One image was also used by R&D Systems for a Novus Biologicals antibody.
\n

Even one of the images shown as \"Example Data\" for \"Specificity Validation\" on Origene's \"Antibodies\" landing page appears to have been manipulated.

\n
\"\"
An image shown as example validation data on Origene's \"Antibodies\" landing page. The same image appears in a promotional video about Origene's \"rigorous process\" for knockout-based validation.
\n

(As it turns out, some of the images I had previously annotated as belonging to Thermo Fisher products actually belonged to Origene products and only appeared on Thermo Fisher's website as part of a partnership with Origene to also include their catalog in Thermo Fisher's search interface. This error has been corrected in the updated version of the repository.)

\n

Millipore Sigma (39 images across 31 products)

\n

Millipore Sigma is a subsidiary of Merck KGaA, headquartered in Darmstadt, Germany. Most of these image manipulations involve reuse of background patterns C and D.

\n
\"\"
A Western blot image presented as validation data for a Millipore Sigma CEACAM5 antibody.
\n

LSBio (2,695 images across 2,536 products)

\n

LSBio is a subsidiary of Vector Laboratories, based in Newark, California. Their catalog features more than 1,000 repetitions each of background pattern A and background pattern B and hundreds of instances of apparent painting in Western blot and immunofluorescence images.

\n
\"\"
A Western blot image presented as validation data for a LSBio CD79 antibody.
\n
\"\"
A Western blot image presented as validation data for a LSBio ESRRA antibody.
\n
\"\"
An immunofluorescence image presented as validation data for an LSBio MTCH2 antibody.
\n

Bioss (305 images across 292 products)

\n

Bioss is headquartered in Woburn, Massachusetts. Hundreds of images in its catalog feature apparent painting or stitching-together of background noise.

\n
\"\"
An immunofluorescence image presented as validation data for a Bioss ALAS1 antibody.
\n
\"\"
A Western blot image presented as validation data for a Bioss Caspase-8 antibody.
\n
\"\"
An immunofluorescence image presented as validation data for a Bioss E2F4 antibody.
\n
\"\"
A Western blot image presented as validation data for a Bioss SCM1 alpha antibody.
\n

Boster Bio (120 images across 96 products)

\n

Boster Bio is headquartered in Pleasanton, California. Many images in Boster's catalog feature signs of apparent painting.

\n
\"\"
A Western blot image presented as validation data for a Boster AKT1 antibody.
\n
\"\"
A Western blot image presented as validation data for a Boster IKB epsilon antibody.
\n

G-Biosciences (6,388 images across 6,373 products)

\n

G-Biosciences is headquartered in St. Louis, Missouri. A stunning volume of images presented as validation data in G-Biosciences' catalog feature either background pattern A (4,278 images) or background pattern B (2,110 images).

\n
\"\"
An animated slideshow of contrast-adjusted Western blots from G-Biosciences' catalog all featuring \"background pattern B\".
\n

GeneTex (38 images across 38 products)

\n

GeneTex is headquartered in Irvine, California. Problematic images in GeneTex's catalog include repetitions of background patterns A and B and at least one instance of copy-pasted background noise.

\n
\"\"
A Western blot image presented as validation data for a GeneTex TET3 antibody.
\n

HUABIO (209 images across 203 products)

\n

HUABIO is headquartered in Hangzhou, China. HUABIO's catalog features many instances of apparent painting and repetitive patterns in background noise.\u00a0

\n
\"\"
A Western blot image presented as validation data for a HUABIO GPC1 antibody.
\n
\"\"
A Western blot image presented as validation data for a HUABIO RBBP5 antibody.
\n

Some of the repetitive regions of background noise also inexplicably contain numerals. I do not have a satisfactory explanation for what happened here.

\n
\"\"
A Western blot image haunted by the number 15, presented as validation data for a HUABIO CLIC2 antibody.
\n

Antibodies.com (242 images across 242 products)

\n

Antibodies.com is headquartered in Cambridge, UK. At least 242 validation images in their catalog feature background pattern A. On August 21, I was alerted that several of these products had been discontinued from the Antibodies.com online catalog since I downloaded these images on August 12 and can no longer be found by search.

\n
\"\"
The product page for a CREB (pSer111) antibody that was discontinued by Antibodies.com sometime between 12 August and 21 August. The validation image displayed features background pattern A.
\n

Abnova (154 images across 145 products)

\n

Abnova is headquartered in Taipei, Taiwan. Many validation images in their catalog feature background pattern C or D, signs of apparent painting or compositing, or other common background patterns (\"background pattern G\" and \"background pattern H\") that I have not observed in other vendors' catalogs.

\n
\"\"
A collage of contrast-adjusted Western blots from Abnova's catalog all featuring \"background pattern G\", distinguishable by a patch of apparent painting around 34 kDa on the left side of the frame.
\n
\"\"
A collage of contrast-adjusted Western blots from Abnova's catalog all featuring \"background pattern H\", distinguishable by a patch of apparent painting around 20 kDa in the lower left corner of the frame.
\n
\"\"
A Western blot image presented as validation data for an Abnova FXR1 antibody (sold through Thermo Fisher's online catalog).
\n

Santa Cruz Biotechnology (125 images across 111 products)

\n

Santa Cruz Biotechnology is headquartered in Dallas, Texas. In 2016, the company paid a historically high 3.5 million USD fine to the United States Department of Agriculture to settle numerous allegations of violating the Animal Welfare Act in its treatment of animals used to produce antibodies. Problematic images in Santa Cruz's catalog feature background painting and apparent cloning of background noise.

\n
\"\"
A Western blot image presented as validation data for a Santa Cruz Biotechnology 14-3-3 eta antibody.
\n
\"\"
A Western blot image presented as validation data for a Santa Cruz Biotechnology G alpha 13 antibody.
\n

Postscript

\n

It cannot be overstated how much biomedical research rides on antibodies performing as intended and how much time researchers lose to working with antibodies that do not perform. Increased recognition of the importance of antibody validation has led to vendors near-universally embedding validation data in their catalogs. However, to many vendors, selling validated antibodies apparently matters less than the semblance of selling validated antibodies.\u00a0

\n

If an antibody fails internal validation testing by its manufacturer, a responsible vendor would elect not to sell it. However, a large fraction of research antibodies currently for sale do not perform as advertised, as detailed by Ayoubi et al. (2024). Thus, either manufacturers and vendors are willfully ignoring the results of their validation testing or are not performing validation testing in the first place. When a vendor sells an antibody with validation data that has been painted over or otherwise altered, it suggests the former possibility. The many wholly-fabricated Western blots using a common background pattern suggest the latter. Many companies are clearly attaching their quality guarantees to private-label products that they had no part in testing, if testing occurred at all.

\n

Skirting validation makes perfect business sense; running validation tests is expensive and it is more profitable to sell a large catalog of untested antibodies than a small catalog of properly-validated products. Ayoubi et al. address this:

\n
\n

Commercial antibody suppliers support a large and diverse catalogue of products, with most antibody products generating <$5000 in total sales, far less than the costs of [knockout]-based validation, estimated at $25,000. While leading companies are increasingly assessing antibody performance, it is exceedingly difficult, and cost restrained, to properly characterize all their products. Even when available, high-performing antibodies may remain hidden within the millions of reagents of unknown quality.\u00a0

\n
\n

An inconvenient result in validation testing could also mean that the cost of developing an antibody goes unrecouped. I wonder, then, why we feel comfortable outsourcing the critical task of antibody production and distribution to entities whose profit motive encourages them to market products that have not been tested.

\n

I do think that readers should direct their ire towards the companies that have been marketing antibodies with faked data. A simple way to do this is for scientists to request the original, unedited validation data images for antibodies they have purchased (Thermo Fisher has already promised that such images will be provided to customers \"where available\"). However, even the most protracted opprobrium will bounce off of large companies like Thermo Fisher or Merck KGaA. Regulation of how research antibodies are produced and marketed will induce longer-term change (and I believe regulation is a minimum necessary step), but there still remains a fundamental mismatch between the needs of the biomedical research community and the interests of the for-profit enterprises producing their crucial reagents. In the long term, I think that the biomedical research community would be better served by the creation of publicly-funded antibody vendors whose interest is in producing antibodies that work, not in producing antibodies that sell.

\n

Footnotes

\n
  1. The repository also contains two images from NeoBiotechnologies (based in Union City, California) which represent a re-used image of an SDS PAGE gel on the product pages for two different TP53 antibodies. Since these were the only potentially problematic images identified in their catalog, I did not profile NeoBiotechnologies here. These products were previously annotated as Thermo Fisher products. This error has been corrected in the latest version of the repository. \"\u21a9\"\ufe0e
\n

","doi":"https://doi.org/10.59350/txnbb-prj57","guid":"http://reeserichardson.blog/?p=4960","image":"https://reeserichardson.blog/wp-content/uploads/2026/08/ma5-15569_ma5-15671_annotated.png?w=1024","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787616000,"rid":"an620-j7872","summary":"On May 17, 2026, Sholto David identified one fabricated image presented as validation data in Thermo Fisher's antibody catalog.","tags":["Research Integrity"],"title":"At least 15 companies are selling antibodies using faked validation data","updated_at":1787662567,"url":"https://reeserichardson.blog/2026/08/25/at-least-15-companies-are-selling-antibodies-using-faked-validation-data/","version":"v1"},{"authors":[{"affiliation":[{"id":"https://ror.org/046ak2485","name":"Freie Universit\u00e4t Berlin"}],"contributor_roles":[],"family":"Fischer","given":"Georg","url":"https://orcid.org/0000-0001-5620-5759"},{"affiliation":[{"id":"https://ror.org/0546hnb39","name":"University of Konstanz"}],"contributor_roles":[],"family":"Flaig","given":"Sebastian","url":"https://orcid.org/0009-0001-1247-6976"},{"affiliation":[{"name":"Freie Universit\u00e4t Berlin, Open Research Office Berlin"}],"contributor_roles":[],"family":"Neufend","given":"Maike","url":"https://orcid.org/0000-0002-1484-0516"}],"blog":{"authors":[{"name":"Open Access Network"}],"community_id":"969d397b-49b9-4c53-9220-607ef85409e5","created":1780876800,"current_feed_url":null,"description":"Neueste Beitr\u00e4ge","doi":"https://doi.org/10.64395/oa_network","favicon":"https://rogue-scholar.org/api/communities/969d397b-49b9-4c53-9220-607ef85409e5/logo","feed_format":"application/rss+xml","feed_url":"https://open-access.network/rss-feed?type=200","filter":null,"generator":"Other","home_page_url":"https://open-access.network/rss-feed?type=200","issn":null,"language":"deu","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.64395","relative_url":null,"secure":null,"slug":"oa_network","status":"active","subfield":"1802","title":"OA Network","updated":1787646360,"use_api":null},"blog_name":"OA Network","blog_slug":"oa_network","content_html":"\"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin\n\n\nAnfang Juli 2026 hat die Landesinitiative Open Research Berlin ein Positionspapier zur Entwicklung von Open Research in Berlin ver\u00f6ffentlicht. Unter dem Titel \"Offenheit als Grundsatz\" enth\u00e4lt das neue Papier diverse Vorschl\u00e4ge und Ideen f\u00fcr Ma\u00dfnahmen, um Open Access auf Open Research strategisch f\u00fcr Wissenschaft und Kulturerbe auszuweiten und im Berliner Forschungsraum zu verankern. Im Interview mit dem oa.blog erz\u00e4hlen Georg Fischer und Maike Neufend vom Open Research Office Berlin (OROB), das den Prozess koordiniert hat, von den Hintergr\u00fcnden, der Motivation und den Kernpunkten des Positionspapiers.\n\n\noa.blog: Wie kam es zur Erarbeitung des neuen \"Positionspapiers zur Entwicklung von Open Research in Berlin\"?\nOROB: Dazu ist es wichtig, einen Schritt zur\u00fcck zu gehen: 2015 erschien die \"Open-Access-Strategie Berlin\", die vom Berliner Abgeordnetenhaus verabschiedet worden war. Das Dokument legte den Grundstein f\u00fcr die kooperative Entwicklung von Open-Access-Aktivit\u00e4ten f\u00fcr den Standort Berlin. Als Ziel wurde damals unter anderem ausgegeben, bis 2020 den Anteil der wissenschaftlichen Open-Access-Publikationen f\u00fcr Zeitschriftenartikel aus allen wissenschaftlichen Einrichtungen in der Zust\u00e4ndigkeit des Landes Berlin auf mindestens 60% zu erh\u00f6hen. Daneben sollten Open Access in den Berliner Hochschulvertr\u00e4gen verankert und die Diskussion \u00fcber die Einbeziehung von Open Access als Indikator f\u00fcr die leistungsorientierte Mittelvergabe gef\u00f6rdert werden. Die Open-Access-Strategie sah au\u00dferdem vor, neben Text-Publikationen auch Forschungsdaten und Kulturdaten bzw. kulturelles Erbe als Handlungsfelder zu entwickeln. Das Open Research Office Berlin ist ebenfalls als Ma\u00dfnahme aus der Berliner Open-Access-Strategie von 2015 hervorgegangen (2016 als \"Open-Access-B\u00fcro Berlin\" gegr\u00fcndet, umbenannt 2025).\n\nNun sind gut zehn Jahre vergangen und die Wissenschaftswelt hat sich weitergedreht. Open Research wurde etwa in das Berliner Hochschulgesetz (BerlHG) aufgenommen: In Paragraph 41 werden Open Access und Open Science definiert und der Auftrag der Hochschulen beschrieben. Auch in der Praxis hat sich Open Access in vielen Bereichen als genereller Standard etabliert; Forschungsdaten zu teilen wird zunehmend beliebter und auch im Kulturbereich tut sich allerhand bei der digitalen \u00d6ffnung und Nutzung der Best\u00e4nde, wie wir 2024 im Open-Access-Bericht Berlin festgehalten haben. Um den Entwicklungen Rechnung zu tragen und die Bedingungen \u2013 z. B. auf infrastruktureller oder rechtlicher Ebene \u2013 aktiv zu gestalten, wurde die \"Landesinitiative Open Research Berlin\" ins Leben gerufen. Damit werden die Erfolge aus der Open-Access-Strategie von 2015 weitergef\u00fchrt, mit Open Research wird aber nun der gesamte Forschungszyklus ins Auge genommen und neben der Wissenschaft werden weitere Wissenssysteme einbezogen. Die Landesinitiative legt nun nach einem partizipativen Prozess das \"Positionspapier zur Entwicklung von Open Research in Berlin\" vor, das zahlreiche Vorschl\u00e4ge und gangbare Wege konturiert, um die Vorreiterrolle Berlins in Sachen Offenheit zu festigen.\n\n\noa.blog: In einem Satz zusammengefasst: Was versteht ihr unter \"Open Research\" konkret?\nOROB: In der Landesinitiative haben wir uns auf folgenden Konsens verst\u00e4ndigt: Mit Open Research meinen wir einen gemeinsamen Bezugsrahmen, in dem verschiedene Praktiken und Prinzipien offener Forschung zusammengef\u00fchrt werden, um Offenheit, Nachvollziehbarkeit und Teilhabe in Wissenschaft und Kultur zu erh\u00f6hen und den Dialog mit anderen Wissenssystemen zu verbessern.\n\n\noa.blog: Was versprecht ihr euch vom Positionspapier?\nOROB: Berlin hat aufgrund der zahlreichen wissenschaftlichen und kulturellen Einrichtungen, die bereits jetzt vielfach miteinander vernetzt sind, einige Standortvorteile. Es gibt hier diverse gut eingespielte Verb\u00fcnde und Kooperationen, die zu verschiedenen Themen gemeinsam arbeiten und L\u00f6sungen f\u00fcr geteilte Herausforderungen suchen. Dennoch k\u00f6nnen mit Open Research neue Potentiale gehoben und \u00fcber Wissenschaft und Kultur hinaus verankert werden: etwa um die gegenseitige Durchdringung der Bereiche zu st\u00e4rken oder die demokratische Aushandlungsf\u00e4higkeit \u2013 und damit auch das Gemeinwohl der Stadtgesellschaft \u2013 zu verbessern.\n\nDie Landesinitiative kn\u00fcpft hier mit ihrem Positionspapier zu Open Research an. Open Research kann folgende drei Standortvorteile f\u00fcr Berlin st\u00e4rken: erstens Wissenstransfer und Vermittlung von Kunst und Kulturerbe, zweitens digitale Souver\u00e4nit\u00e4t und Resilienz sowie drittens Kooperation und gemeinsame Infrastruktur. Offene Forschung und offene Kultur leisten einen elementaren Beitrag zur St\u00e4rkung von demokratischen Prozessen, Vielfalt und Wissensgerechtigkeit. Informationsinfrastrukturen stellen auf der anderen Seite, insbesondere wenn sie offen und kooperativ getragen sind, eine wesentliche Voraussetzung f\u00fcr die digitale Handlungsf\u00e4higkeit und Unabh\u00e4ngigkeit der Wissenschafts- und Kulturerbe-Einrichtungen dar. Kooperationen innerhalb Berlins schlie\u00dflich schaffen Synergien, k\u00f6nnen die Effizienz erh\u00f6hen und st\u00e4rken die Widerstandsf\u00e4higkeit des Wissenschafts- und Kulturstandorts. In dem Positionspapier skizziert die Landesinitiative entsprechende Ma\u00dfnahmen und legt dar, wie diese ineinandergreifen.\n\n\noa.blog: Was sind die wichtigsten Eckpunkte und Themen?\nOROB: Das Papier formuliert insgesamt vier gro\u00dfe Themen: Kulturen der Offenheit, Souver\u00e4ne Wissens\u00f6kosysteme, Faire Finanzierung und Open Research Monitoring.\n\nKulturen der Offenheit f\u00f6rdern Transparenz, Zusammenarbeit und den Austausch von Wissen in Fachdom\u00e4nen und \u00d6ffentlichkeit. Erst in und mit Kulturen der Offenheit lassen sich souver\u00e4ne Wissens\u00f6kosysteme entwickeln, die es den Akteur*innen erm\u00f6glichen, ihre Publikationen, Informationen und Daten selbstbestimmt zu verwalten, ihre Forschungsprozesse offen zu gestalten und im Rahmen offener Praktiken langfristig zu etablieren und zu pflegen.\n\nGleichzeitig ist eine den Kosten angemessene, also faire Finanzierung notwendig, um die genannten Kulturen der Offenheit zu st\u00e4rken und die Entwicklung souver\u00e4ner Wissens\u00f6kosysteme institutionell und langfristig zu verankern. Hier sieht es die Landesinitiative als unabdingbar an, die Berliner Einrichtungen mit angemessenen finanziellen Mitteln auszustatten. Zugleich m\u00fcssen die Einrichtungen die Finanzentscheidungen so diversifizieren, dass die Finanzierung von Forschung inklusive Publikationen gerechter wird, d.h. nicht-gewinnorientiertes Open Research gef\u00f6rdert wird. Erst dann lassen sich die oben genannten Ziele erreichen.\n\nAu\u00dferdem sehen wir ein intelligentes, kontextsensitives Monitoring von Open Research vor, das die Entwicklung in den vorherigen Themenbereichen dokumentiert und damit nachvollziehbar macht, ob die Prinzipien der Offenheit, Souver\u00e4nit\u00e4t und Fairness gelebt werden und wo ein Nachsteuern ggfls. notwendig ist. Ein solches Monitoring erm\u00f6glicht also eine kontinuierliche Verbesserung und Anpassung der Ma\u00dfnahmen.\n\n\noa.blog: Und welche konkreten Ziele adressiert das Papier?\nOROB: Konkret sollen innerhalb der vier Themen folgende neun Ziele erreicht werden: Anerkennung, Kompetenzen und Rechtssicherheit in Bezug auf Open Research st\u00e4rken; robuste Informationsinfrastrukturen kooperativ entwickeln und pflegen sowie das Engagement zur Unterst\u00fctzung von Open Research verbessern; transparente Finanzierungsmodelle entwickeln und mit Leben f\u00fcllen sowie eine koordinierte Transformation und Diversifizierung des Investitionsverhaltens einleiten; geeignete Methoden zur Beobachtung, Dokumentation und Monitoring von Open Research entwickeln und umsetzen.\n\n\noa.blog: Was habt ihr speziell f\u00fcr Open Access festgehalten? Welche Rolle sieht das Papier f\u00fcr Open Access im gr\u00f6\u00dferen Kontext von Open Research vor?\nOROB: Die Definition von Open Research basiert auf den vorhergehenden Initiativen und Empfehlungen, wie die Budapest Open Access Initiative (2002), das Bethesda Statement on Open Access Publishing (2003) und die Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities (2003). Wenn es um die Ver\u00f6ffentlichung von wissenschaftlicher Information und Forschung durch die Mitglieder der Hochschulen geht, soll diese unter freien Lizenzen mit dem Ziel der Nachnutzbarkeit erfolgen (Open Access). Da Open Access sich in den vergangenen Jahren zu einem sehr lukrativen Gesch\u00e4ftsmodell f\u00fcr gewinnorientierte Verlage entwickelt hat, liegt ein Fokus aktuell auf einer Diversifizierung der Finanzentscheidungen von Hochschulen (faire Finanzierung) und entsprechend einer F\u00f6rderung von Open Access als nicht-gewinnorientiertes Publizieren. Darunter verstehen wir nicht, dass faires Open-Access-Publizieren zwingend weniger kostet, aber die Investition in nachhaltige und wissenschaftsgeleitete Publikationsinitiativen und -Modelle erlaubt, Kosten und Preise nachvollziehbar und damit die Finanzierung durch die \u00f6ffentliche Hand gerechter zu machen. Zugleich k\u00f6nnen die technologischen Investitionen und das Engagement der Wissenschaft f\u00fcr innovative Verfahren der Wissenschaftskommunikation an den Hochschulen besser verankert werden.\n\n\noa.blog: Wieso ist das Positionspapier auch f\u00fcr andere Einrichtungen und OA-Professionals interessant, obwohl es sich auf Berlin bezieht?\nOROB: Bei der Erarbeitung des Papiers hat sich die Landesinitiative von zahlreichen existierenden Initiativen, Strategien und anderen Papieren inspirieren lassen, etwa von der UNESCO, der DFG und nat\u00fcrlich von Entwicklungen im Berliner Raum. Damit bilden wir den Status Quo in Sachen Open Research im Jahre 2026 ab, was f\u00fcr Einrichtungen und OA-Professionals, aber auch f\u00fcr interessierte Forschende insgesamt von Interesse sein d\u00fcrfte. Die von uns adressierten neun Ziele enthalten kulturelle, rechtliche, infrastrukturelle, technische und finanzielle Aspekte in Sachen Open Research und sollen Impulse setzen, offene Wissenschaft und Kultur gemeinsam weiterzuentwickeln, also etwa die Arbeit von Bibliotheken, Archiven und Kulturerbe-Einrichtungen zusammen mit wissenschaftlicher Forschung und Lehre zu verzahnen und damit Synergien zu heben. Interessierte d\u00fcrften daher Denkanst\u00f6\u00dfe f\u00fcr einzelne Problemstellungen erhalten wie auch f\u00fcr das Gesamtpaket, das die Landesinitiative f\u00fcr Berlin nun anbietet. Schlie\u00dflich unterst\u00fctzt das Papier auch die \u00fcberregionale Zusammenarbeit, z. B. mit Landesinitiativen aus anderen Bundesl\u00e4ndern oder lokalen Akteur*innen. Wir haben hier gute Erfahrungen und eine enge Zusammenarbeit etwa mit den Kolleg*innen aus Nordrhein-Westfalen, dem Saarland oder Brandenburg.\n\n\noa.blog: Habt ihr im Strategieprozess Erfahrungen gemacht, von denen andere Akteure lernen k\u00f6nnen, die \u00e4hnliche Vorhaben verfolgen?\nOROB: Es braucht einen langen Atem, um die verschiedenen Interessen der einzelnen Stakeholder zu diskutieren und unter dem Dach eines gemeinsamen Papiers zusammenzubringen. Das war im Berliner Fall nicht innerhalb von ein paar Monaten zu bewerkstelligen. Gleichzeitig war uns von Anfang an ein transparenter und partizipativer Konsultationsprozess zur gemeinsamen Erarbeitung des Papiers wichtig. Dies haben wir in einem Addendum dokumentiert, das vergleichbaren Initiativen hoffentlich Anregungen bietet.\n\nMan muss darauf vorbereitet sein, dass sich externe Rahmenbedingungen \u00e4ndern k\u00f6nnen, auf die man selbst keinen Einfluss hat. In unserem Fall etwa die Wiederholungswahl zum 19. Abgeordnetenhaus von Berlin am 12. Februar 2023, aber auch der \u00dcberfall Russlands auf das gesamte Staatsgebiet der Ukraine oder der Erfolg von KI-Technologien, der nun weite Teile des Forschungsprozesses ber\u00fchrt. In diesem Zuge wurden etwa Themen wie digitale Souver\u00e4nit\u00e4t und Resilienz von technischen Systemen im Kontext Offenheit wichtiger, so dass wir in der Landesinitiative darauf reagierten. \n\nLast but not least ist das Positionspapier die Frucht des regelm\u00e4\u00dfigen Austauschs: nicht nur in der Landesinitiative sondern auch etwa vier Mal im Jahr mit den Open-Access-Beauftragten der Berliner Universit\u00e4ten und Hochschulen. In diesen Runden sind \u00fcber die Jahre zahlreiche Herausforderungen, L\u00f6sungswege und strategische Ans\u00e4tze diskutiert worden, die in das Positionspapier gem\u00fcndet sind.\n\n\noa.blog: Wie geht es nun mit dem Positionspapier weiter? Habt ihr bereits konkrete n\u00e4chste Schritte f\u00fcr die praktische Umsetzung der Ziele vorgesehen?\nOROB: Der Konsultationsprozess ist mit der Ver\u00f6ffentlichung des Papiers nicht abgeschlossen, sondern nun f\u00fcr die interessierte \u00d6ffentlichkeit ge\u00f6ffnet. Auf PubPub k\u00f6nnen alle, die m\u00f6gen und sich einen Account anlegen, im Rahmen eines Public Review-Verfahrens das Papier kommentieren, Vorschl\u00e4ge, Ideen, Anregungen eingeben und sich so in den Prozess einbringen. Aktuell wird das Papier in den Gremien der betroffenen Berliner Einrichtungen diskutiert und weitere Schritte werden in den kommenden Sitzungen der Landesinitiative er\u00f6rtert. Mit Spannung blicken wir auf die Wahl zum Abgeordnetenhaus von Berlin am 20. September, nach der sich f\u00fcr die gro\u00dfen wissenschaftspolitischen Vorhaben in Berlin die Weichen stellen werden.\n\n\noa.blog: Vielen Dank!\n\n\nDas Interview f\u00fchrte f\u00fcr den oa.blog Sebastian Flaig. F\u00fcr das OROB beantworteten die Fragen Georg Fischer und Maike Neufend.\n\n\nZitiervorschlag\nFlaig, S., Fischer, G., Neufend, M. (2026): \"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin. open-access.network. DOI: \n\n\n\nDieser Beitrag ist lizenziert unter der Creative Commons Namensnennung 4.0 International Lizenz (CC BY 4.0)","doi":"https://doi.org/10.64395/3zj8s-kxd10","guid":"https://open-access.network/blog/interview-zum-strategiepapier-open-research-berlin","language":"de","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1787616000,"rid":"vw51w-tc197","summary":"\"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin Anfang Juli 2026 hat die Landesinitiative Open Research Berlin ein Positionspapier zur Entwicklung von Open Research in Berlin ver\u00f6ffentlicht.","tags":["Open Access Transformation"],"title":"\"Offenheit als Grundsatz\": Das Positionspapier zur Entwicklung von Open Research in Berlin","updated_at":1787658400,"url":"https://open-access.network/blog/interview-zum-strategiepapier-open-research-berlin","version":"v1"},{"authors":[{"contributor_roles":[],"family":"Neylon","given":"Cameron","url":"https://orcid.org/0000-0002-0068-716X"},{"affiliation":[{"name":"Sesame Open Science"}],"contributor_roles":[],"family":"Kramer","given":"Bianca","url":"https://orcid.org/0000-0002-5965-6560"},{"contributor_roles":[],"family":"Mazoni","given":"Alysson","url":"https://orcid.org/0000-0001-5265-6894"},{"affiliation":[{"id":"https://ror.org/027bh9e22","name":"Leiden University"}],"contributor_roles":[],"family":"Costas","given":"Rodrigo","url":"https://orcid.org/0000-0002-7465-6462"},{"contributor_roles":[],"family":"Jahn","given":"Najko","url":"https://orcid.org/0000-0001-5105-1463"},{"affiliation":[{"name":"Leiden University, Centre for Science and Technology Studies"}],"contributor_roles":[],"family":"van Eck","given":"Nees Jan","url":"https://orcid.org/0000-0001-8448-4521"}],"blog":{"authors":null,"community_id":"b56ef314-34f7-4c7f-b0e2-d0bf13bfe83b","created":1673568000,"current_feed_url":"https://upstream.force11.org/atom/","description":"The community blog for all things Open Research.","doi":"https://doi.org/10.54900/upstream","favicon":"https://rogue-scholar.org/api/communities/b56ef314-34f7-4c7f-b0e2-d0bf13bfe83b/logo","feed_format":"application/atom+xml","feed_url":"https://upstream.force11.org/atom-complete/","filter":null,"generator":"Ghost","home_page_url":"https://upstream.force11.org","issn":null,"language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.54900","relative_url":null,"secure":true,"slug":"upstream","status":"active","subfield":"1802","title":"Upstream","updated":1785846998,"use_api":true},"blog_name":"Upstream","blog_slug":"upstream","content_html":"

The rise of open research information resources is transforming the way we track, analyse and study research systems. Increasingly, sources like OpenAIRE, OpenAlex, Crossref, DataCite, ORCID, ROR and others are being used as the basis for making decisions, designing interventions and understanding progress in the science system. This operates both at the small scale, where access to data and evidence is easier than it has ever been, to the very large scale analysis of whole systems.

Traditionally, the capacity to do large-scale analyses was restricted to a very small set of players, like specialised research centres or companies. This kind of large scale analysis usually requires access to an actionable version of the whole dataset, particularly if the goal is combining data resources. The set of sites with access to complete copies of proprietary databases is tiny. 

Modern open data sources provide access, including access to full copies of the data, but there has been less focus on providing this access in a way that allows large scale complex querying and connecting of whole data archives - for example to compare the coverage of research outputs by OpenAlex and OpenAIRE or analyse global information on clinical trials using affiliation data from OpenAlex and clinical trials information from Pubmed. Another valuable possibility is the ability to incorporate local data enrichments from national or regional data sources to support local data needs, or improve the overall pool of data.

Google BigQuery has emerged as one powerful tool for combining and working on these large datasets at scale. Multiple groups (including the MultiObs team - continuing the work of the InSySPo team at Campinas, SUB G\u00f6ttingen, Sesame Open Science and CWTS amongst others), have created 'public' versions of specific open datasets in the BigQuery system, which anyone can access and run their own analyses. Through these public versions, the 'provider' (i.e. the teams mentioned above) pays for storage, and the user freely accesses the 'public' versions taking responsibility for covering the costs of data querying and processing.  

Having worked independently so far, this small group came together last year to ask whether we could coordinate actions. Could it be possible to build a comprehensive open research information resource where the load of providing specific core and relevant open data sources was distributed? Rather than each separately trying to tackle the whole, potentially duplicating efforts, could we collectively create a resource that was more than the sum of its parts? 

We met with a series of key questions:

  1. Can we share resources and burdens to make available key open research information resources in actionable and connectable form in the cloud?
  2. Through sharing processes and systems, is it possible, over time, to build a standard for how these data sources should be made available?
  3. What are the challenges that we can usefully approach collectively?
  4. What are the benefits and risks of Google BigQuery as an environment and do we agree it is the best place to start?
  5. What are the blockers for engagement with such an effort? What is needed for different stakeholders to make it attractive both as users and (for some) as providers?

User and use case driven

Core to our shared interest in working together was the idea of making it easier for more people to undertake large scale analysis. There are many kinds of analysis for which access to APIs is sufficient. We share a belief that large scale analysis will be useful in multiple settings, but that it has been relatively inaccessible. This inaccessibility is a hurdle to realising the promise of democratization and broader adoption of open research information in all decision making processes around science and scholarship, as proposed by the Barcelona Declaration. APIs are also expensive to run, by taking some of the heavy load use-cases away from APIs we can support providers by reducing their costs, centralising distribution, and allowing APIs to focus on the use cases they are best suited for.

There is a growing set of research projects that are exploiting this capacity for large scale and combined analysis in a range of ways. Two recent pieces of work provide examples of what is possible. One by Camilla Lindelow and Eline Vandewalle, used the combination of ORCID and OpenAlex provided by InSySPo (now MultiObs) to analyse researchers without a formal affiliation from around the world. The second example, from Cespedes and colleagues associated with the UNESCO Chair in Open Science, used a global analysis of language in OpenAlex to examine affiliation. This combines with other efforts, including comparisons of metadata coverage across sources, and combinations of data sets that exploit the capacity to do analysis at scale.

These use cases have a few things in common. They tend to be global in scope (or at least aspire to be) so they require analysis across the whole of a datasource (or a combination of datasources). They generally involve a complex form of query, requiring filtering or analysis on multiple database elements, or a combination of multiple data sources, that is difficult or impossible using the API for any given datasource. And the generated dataset is often very large in its own right - perhaps involving hundreds of millions of rows of data - and requires further reduction and analysis.

Overall, the common theme here is analyses that require entire data sources to be combinable and actionable at scale. We believe if we focus on that set of use cases we can add something valuable to the overall Open Research Information ecosystem.

Opportunities for shared systems

If people are already doing this what is the value of coordination? The first and most obvious is that with a shared cloud system we only need to pay for online storage of each dataset once and then anyone can use it (backups and versions over time are a separate issue, which we aim to address, but not as the first priority). Cloud storage costs are generally larger than the usage costs involved in running queries so sharing this load is valuable in its own right.

The second advantage is the ability to share capacities. One example of this is data preprocessing. These datasets are not \"clean\" in the sense that they change over time, have some internal inconsistencies, and often contain elements that raise compatibility issues with database systems. Processing hundreds of millions of lines of JSON to convert hyphens to underscores in variable names takes time and computing power (and money!). 

Systems developed within the Curtin Open Knowledge Initiative (COKI) use cloud VMs to do this on demand which scales but adds costs. The team at G\u00f6ttingen are using code derived from this on their own HPC resources. The team at CWTS uses their own code to process datasource dumps on local servers so that relational databases can be integrated into their internal database system, while also exporting the results to Google BigQuery. Within the Sesame Open Science system a further evolution of the COKI code is used to process dumps on local computers. There is a clear benefit to be gained by using a common code base for necessary transformations. But also in having a community discussion on what pathways and transformations are necessary. The MultiObs team uses a quite different approach -- creating relational structures from datasource dumps -- with advantages (reduced costs, timestamps, etc.) but also disadvantages (lack of live data, need for updates, etc.) we can learn from. Different approaches and experiences, but also different sets of resources like HPC could be shared amongst an effective collaboration.

This leads to the third advantage. If we use common systems we help to develop quasi-standards that can be adopted by others. That creates an opportunity to spread the load further, as well as to increase the diversity of datasets available (again, thinking of those highly curated national datasets that are used locally but not always recombined into the global data ecosystem). If we have a clear shared approach to the data and how it is managed it makes it easier for others to contribute, and makes the whole set of resources more valuable and sustainable. In essence, the more we share the load, the less we pay for the costs of our contributions. 

A final benefit of a shared approach would be a virtuous loop in which shared systems encourage shared approaches to analysis. Common approaches can form the basis for training resources that give end-users an easy point of entry to using these data sources at scale. They will also encourage the sharing of analysis scripts and protocols creating advanced and transparent resources to support developing users.

Key to this is understanding both what has value to keep in common, but also what needs to be different to serve a diversity of use cases. We can see value in technical standards (where they are useful) and in agreements around archiving and preservation. Documentation, where it can reach common standards, will be helpful not just for users of the data, but potentially for upstream producers in understanding how the data is being used and how to optimize the provision of their data snapshots to facilitate downstream usage.

The Google-shaped elephant in the room 

A big question is why Google BigQuery? It is certainly not an open system in any meaningful sense and Google is not an organisation many of us feel able to trust. The short answer is pragmatism. There are reasons why we independently arrived at GBQ as a useful tool. Google solves a bunch of the hard problems, including authentication without the need for institutional affiliation, systems provisioning and a highly performant database system. In practice, this means datasets can be made publicly available, without the need for specific hard-or software on the side of the user, and, from a user perspective, access to datasets hosted by different providers is possible using a single system. Standing up an independent infrastructure to do this is a big job and not one we're equipped to tackle at the moment.

That said, none of us believe that reliance on Google is a desirable long term solution, nor that it is fully equitable. There are some emerging alternatives both in the cloud and for local computing. These aren't fully mature but they show promise. In the meantime we believe it is important to ensure we have an exit strategy. One such strategy could be a commitment to creating backups in the form of parquet files. Parquet is an interesting interoperability format for databases and can be read in by an increasing number of tools. It holds schema information and allows for database partitioning. 

Perhaps the most important argument is that with Google BigQuery and external archiving, there is at least one plausible option to explore that can provide value immediately, but also provide a potential escape route. We can save the arguments for frozen duck lakes, glaciers, torrents and MySQL for later and for those who will want to have them! But we need to think seriously about how we will work towards more independence and resilience early on in the process. 

Next steps and a call for interest

We have made a small start. Small, but useful for us.  After all, we are already using these shared data resources. We have demonstrated that without much effort or technical hassle it is possible to share the load, reduce costs and maximize benefits and accessibility. We hope by engaging a wider community we can make this more useful for more people and move us all closer to ideals of democratization of open research information, supporting adoption. How far this goes and how big a community we can create is an open question.

We have made a small start under the label of ORION-DBs, standing for Open Research Information Online Databases. There is now a website that details the datasets available, where they can be accessed and when the most recent update was. We hope this will be a useful resource for people doing ad hoc analyses, occasional use, or just one-off interest in taking a look, as well as those with bigger use cases and ongoing needs for data access. We hope a community of users and also of providers will be interested to coordinate through this platform to aid discovery, adoption and democratization of open research information.

Looking forward, we're interested in how we can build on this base. We want to coordinate and build a shared capacity. If you have an interest in how this could be shaped, demonstrating specific use cases, or contributing additional hosted datasets, we'd love to hear from you. Coordination takes time, time requires resources. If there is sufficient interest, we will look at how we could coordinate resources and build something as lightweight as possible and as formalised as necessary.

Above all, we want to hear from those who share the vision for creating data resources that can be combined and used together and to make them as useful as possible. You can contact us through info@orion-dbs.community and depending on interest, we will set up other forums. It is through using these data sources that we identify their issues and can correct and improve them. When we do that work together, we increase the quality of all data resources faster, more sustainably and more effectively.

","doi":"https://doi.org/10.54900/2pnyq-nhx95","guid":"https://doi.org/10.54900/2pnyq-nhx95","image":"https://upstream.force11.org/content/images/2026/02/antique-orion.webp","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1771200000,"rid":"9xdwc-j6753","summary":"The rise of open research information resources is transforming the way we track, analyse and study research systems. Increasingly, sources like OpenAIRE, OpenAlex, Crossref, DataCite, ORCID, ROR and others are being used as the basis for making decisions, designing interventions and understanding progress in the science system.","tags":["Thought Pieces"],"title":"Sharing the load: Building a collective to support open research information online","updated_at":1787651919,"url":"https://upstream.force11.org/sharing-the-load-building-a-collective-to-support-open-research-information-online/","version":"v1"},{"authors":[{"affiliation":[{"id":"https://ror.org/008zgvp64","name":"Public Library of Science"}],"contributor_roles":[],"family":"Fenner","given":"Martin","url":"https://orcid.org/0000-0003-1419-2405"}],"blog":{"authors":[{"name":"Martin Fenner","url":"https://orcid.org/0000-0003-1419-2405"}],"community_id":"15a362ea-8138-42b8-917f-1840a92addf8","created":1672531200,"current_feed_url":null,"description":"The Front Matter Blog covers the intersection of science and technology since 2007.","doi":"https://doi.org/10.53731/front_matter","favicon":"https://rogue-scholar.org/api/communities/15a362ea-8138-42b8-917f-1840a92addf8/logo","feed_format":"application/atom+xml","feed_url":"https://blog.front-matter.de/atom","filter":null,"generator":"Ghost","home_page_url":"https://blog.front-matter.de/","issn":"2749-9952","language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.53731","relative_url":null,"secure":true,"slug":"front_matter","status":"active","subfield":"1710","title":"Front Matter","updated":1787642045,"use_api":true},"blog_name":"Front Matter","blog_slug":"front_matter","content_html":"

In October I published an essay on Article-Level Metrics (ALM) in PLOS Biology (Fenner, 2013). The essay is a good introduction into Article-Level Metrics, and I am proud that it is part of the Tenth Anniversary PLOS Biology Collection. Like all PLOS content, the article was published with a Creative Commons attribution license, allowing me to republish the article on this blog. I have now done so and the article is available here.

Of course I didn't want to simply republish the article, but I wanted to publish an improved version. The article has five figures, four of them show visualizations of ALM data that were generated using R (the fifth figure is a table reproduced from another article). The PLOS article includes the ALM dataset and the R scripts used to generate the figures as supplementary information. What I have done now is to recreate the article as a single markdown file (available here) that has all R code embedded. Using R and knitr - and the CSV file with the ALM data - everyone can now reproduce the figures from the paper by simply running the embedded code, and can dig deeper into the data.

\"Figure
Figure 3. Views vs. citations for PLOS Biology articles published in 2010.

This was a good opportunity to improve the accessibility of the article in other ways. Instead of the raster image formats PNG, JPEG and TIFF used by PLOS and almost every other publisher, I generated the figures in the vector format SVG. Not only does SVG produce images independent of device resolution and screen size (try to zoom in on the figure above), but SVG can also easily be manipulated in the browser since it is XML. This is beyond the scope of this blog post, but look at the d3.js Javascript library for great examples of how SVG can be dynamically generated and changed in the browser. Figure 3 above could for example be enhanced so that the article title is displayed when you hover over one of the bubbles, or we could enable zooming to show more detail.

Like all content on this blog, the article was created using Pandoc, and the bibliography was dynamically generated. This makes it easy to change the citation style, and I decided to use the APA Style that shows the citations in the text as author-date rather than numbered as with the PLOS style (see the example citation in the first paragraph). The combined bibliography for all blog posts including the article can be downloaded in bibtex format here.

Lastly, I wanted to generate nicer HTML for a better online reading experience. I haven't done anything fancy, but most publishers seem to focus on navigation around an article, so that very little screen real estate is left for the actual content of the article. I've tried to improve readability by reducing the navigation areas to a minimum, by using readable fonts in larger sizes: Adobe Minion Pro for the body text and Adobe Myriad Pro for headings, tables and figure legends.

References

Fenner, M. (2013). What can article-level metrics do for you? PLoS Biol, 11(10), e1001687. doi:10.1371/journal.pbio.1001687

","doi":"https://doi.org/10.53731/r294649-6f79289-8cw0n","guid":"https://doi.org/10.53731/r294649-6f79289-8cw0n","image":"https://storage.ghost.io/c/c5/33/c533c955-b5f3-4ff1-ae2d-6b52a212e602/content/images/2025/01/pbio.1001687.g003.png","language":"en","license":"https://creativecommons.org/licenses/by/4.0/legalcode","published_at":1386720000,"reference":[{"id":"https://doi.org/10.1371/journal.pbio.1001687","unstructured":"Unknown title"}],"rid":"5dqtd-94222","summary":"In October I published an essay on Article-Level Metrics (ALM) in PLOS Biology (Fenner, 2013). The essay is a good introduction into Article-Level Metrics, and I am proud that it is part of the Tenth Anniversary PLOS Biology Collection. Like all PLOS content, the article was published with a Creative Commons attribution license, allowing me to republish the article on this blog. I have now done so and the article is available here.","tags":["Feature"],"title":"Example article with embedded code and data","updated_at":1787651654,"url":"https://blog.front-matter.de/posts/example-article-with-embedded-code-and-data/","version":"v1"},{"authors":[{"affiliation":[{"name":"Front Matter"}],"contributor_roles":[],"family":"Fenner","given":"Martin","url":"https://orcid.org/0000-0003-1419-2405"}],"blog":{"authors":[{"name":"Martin Fenner","url":"https://orcid.org/0000-0003-1419-2405"}],"community_id":"15a362ea-8138-42b8-917f-1840a92addf8","created":1672531200,"current_feed_url":null,"description":"The Front Matter Blog covers the intersection of science and technology since 2007.","doi":"https://doi.org/10.53731/front_matter","favicon":"https://rogue-scholar.org/api/communities/15a362ea-8138-42b8-917f-1840a92addf8/logo","feed_format":"application/atom+xml","feed_url":"https://blog.front-matter.de/atom","filter":null,"generator":"Ghost","home_page_url":"https://blog.front-matter.de/","issn":"2749-9952","language":"eng","license":"https://creativecommons.org/licenses/by/4.0/legalcode","prefix":"10.53731","relative_url":null,"secure":true,"slug":"front_matter","status":"active","subfield":"1710","title":"Front Matter","updated":1787642045,"use_api":true},"blog_name":"Front Matter","blog_slug":"front_matter","content_html":"

Starting this week blog posts are archived in the Rogue Scholar science blog archive using a dedicated invenio module instead of an external service. This simplifies the maintenance of the service and is critical for the long-term future of the archived content.

Rogue Scholar started out as a bespoke service written in Javascript in early 2023. In September 2024 Rogue Scholar started the migration to the InvenioRDM repository platform. This migration is now complete with the release of the invenio-feeds module that provides functionality to automatically parse blog feeds and archive the metadata and content in a digital repository. This extends functionality already available in InvenioRDM, or added in previous work \u2013 DOI registration with Crossref, full-text search, and automated subject classification with the OpenAlex vocabulary falls in the later category.

Until the release of invenio-feeds, automatic parsing of newly published or updated science blog posts was done by a dedicated Javascript and later Python service hosted at api.rogue-scholar.org. This service is no longer needed and will be retired on November 1st, reducing the complexity and cost of Rogue Scholar infrastructure. One example is the use of GitHub Actions to trigger the parsing of all blog feeds every 10 min which is now handled by InvenioRDM background workers.

The switch from dedicated external service to Python module has been fairly smooth so far, but I absolutely expect issues to come up in the coming weeks and months.

The migration to invenio module not only simplifies Rogue Scholar infrastructure, but comes with new functionality: archiving of blog posts as PDF files in the PDF/A format as InvenioRDM file attachments.

\"\"

One fundamental archiving principle is LOCKSS (Lots of Copies Keep Stuff Safe), and these PDF files nicely complement archiving activities by the blog itself, archiving of metadata and full-text in Rogue Scholar, and archiving of participating science blogs in the Internet Archive Archive-It service.

These PDF files are generated the moment content is added or updated to Rogue Scholar, and it will take a few months to address issues with the PDF files (e.g. pagination, image sizing), and archiving the more than 50K science blog posts in Rogue Scholar.

The PDF files use the same layout as the PDF files generated by Rogue Scholar since January 2024, but are generated with every submission to Rogue Scholar instead of dynamically on demand (using the commonmeta-py library). The PDF files are again generated with the WeasyPrint and pikepdf Python libraries, but no longer use Pandoc and the markdown format as an intermediary step. Other formats (markdown, ePub or JATS XML) are no longer supported, and this simplification makes the PDF generation workflow simpler and faster \u2013 allowing me to generate more than 3000 PDF attachments this week.

I have a painful relationship with PDF and scholarly publishing, and have long thought the proper archiving format for Rogue Scholar. WARC is a widely used archiving format developed and used by the Internet Archive \u2013 supported in InvenioRDM since the recent v14 release. Markdown and ePub are open formats closer to the technologies used by blogging platforms. PDF is fine for reading and archiving, but very painful to work with to extract content out again. The decision for PDF/A (and not WARC or ePub) was mainly for two reasons:

The PDF/A that Rogue Scholar generates has two important features that overcome critical PDF shortcomings:

Over the coming months I will not only work on any issues that come up with the new invenio-feeds module and PDF generation, but reach out to participating science blogs about archiving the PDF/A files in associated repositories, starting with the Invenio blog and Zenodo.

Please reach out via Slack, email, Mastodon, or Bluesky if you have any questions or comments.

Rogue Scholar is a scholarly infrastructure that is free for all authors and readers. You can support Rogue Scholar with a one-time or recurring donation or by becoming a sponsor.

References

  1. Fenner, M. (2022, December 12). Building an archive for scholarly blog posts. Front Matter. https://doi.org/10.53731/br9f5xa-a556w2t
  2. Fenner, M. (2024, September 2). Rogue Scholar migrates to InvenioRDM. Front Matter. https://doi.org/10.53731/sdazp-kzn55
  3. Fenner, M. (2023, October 30). Starting November, all Rogue Scholar blog posts will be archived by the Internet Archive. Front Matter. https://doi.org/10.53731/hhtx0-wb293
  4. Fenner, M. (2024, January 8). Every Rogue Scholar blog post now available in Markdown, ePub, and PDF formats. Front Matter. https://doi.org/10.53731/1dfxr-hs665
  5. Fenner, M. (2010, October 6). Beyond the PDF \u2013 it is time for a workshop. Front Matter. https://doi.org/10.53731/r294649-6f79289-8cw7z
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