Henry Rzepa's blog

In May 2015, the EPSRC funding council in the UK required researchers to publish the outcomes of the funded work to include an OA (open access) version of the narrative and to cite the managed research data used to support the research with a DOI (digital object identifier). I was discussing these aspects with a senior manager (research outcomes) at the EPSRC and he asked me to provide some examples from my area of chemistry; here are some.

The basics are covered by three broad actions:

1. The researcher should adopt a research data management plan. This can be quite brief, but it is important that it be updated as the strategies evolve with time and that it is consistent within the group (ideally the department).
   • It would include a general policy for the research group to access and if appropriate share a common, private, storage area for the so-called "active data" (data still being analysed and processed). It could for example take the form of cloud storage, using commercial providers such as Box, DropBox or GitHub. The data is accessible only to those who have been granted access.
   • It could be a software organizer in which cloud storage is implicit. For quantum calculations, we use a locally developed system for the purpose which serves a storage function and which has one other even more important attribute in functioning as a generator and collector of metadata associated with the datasets being generated.[1],[2],[3]
2. The narrative describing the research is then published as an OA article, conjointly with …
3. … the datasets being published to a data repository, and assigned a DOI.
4. There are some delicate aspects of ensuring that actions 2 and 3 are synchronised, ensuring that the article cites the data and that the data cites the article. I will not here detail the mechanisms for achieving this.

What follows here are 11 examples of OA articles in which managed data is cited in the manner decribed at the start. You may notice a diversity of styles and procedures. At the time most of these examples were being worked upon, there were few examples or indeed guidelines, and so these really constitute an exploration of various ways in which it can be done.

I hope this table adds to the open collection of pointers linking open access research articles to associated managed data.^† One really requires this association to be achieved using metadata and perhaps something along these lines might emerge quite soon from the fruits of the current collaborations between CrossRef and DataCite. Ideally, one should be able to pose search queries along the lines of identifying all research data associated with an article, and indeed vice versa.

When the scientific journal arose some 350 years ago, the format and presentation of the narrative evolved only relatively slowly, an evolution that has accelerated somewhat in the online era largely due to the author guidelines imposed by the publishers. I suspect most authors were happy to allow the publishers to take control of this aspect. There may now however be a similar expectation that the publishers specify how authors' data is managed and presented. I would however argue here that it is the authors themselves who know the attributes of their data best and the 11 examples above show one evolutionary process of the data publication process which in this instance was largely determined by the authors themselves. We should strive to allow the authors to retain these measures of creativity in the future, as RDM and its integration into journals matures and develops.

^‡Interactive tables here were created as convenient collections of dataset DOIs, and have been presented in conjunction with visualisation software such as Jmol or JSmol. These tables can themselves be published in a repository and assigned a DOI. Most of the examples we prepared were published in the Figshare repository (the DOIs for some of which are shown in the last column of the table above). Special actions had to be taken at the Figshare end to allow the tables to be incorporated into the landing page presentation corresponding to the DOI. In December 2015, the site was refactored and this functionality is currently disabled, but should be restored in the near future.

 ^†If anyone reading this post is aware of interesting chemistry examples illustrating formal data citation of managed research data using e.g. a DOI in published articles, do please let me know and if appropriate I will add them to the table above.

References

1. M.J. Harvey, N.J. Mason, and H.S. Rzepa, "Digital Data Repositories in Chemistry and Their Integration with Journals and Electronic Notebooks", Journal of Chemical Information and Modeling, vol. 54, pp. 2627-2635, 2014. https://doi.org/10.1021/ci500302p
2. M.J. Harvey, N.J. Mason, A. McLean, and H.S. Rzepa, "Standards-based metadata procedures for retrieving data for display or mining utilizing persistent (data-DOI) identifiers", Journal of Cheminformatics, vol. 7, 2015. https://doi.org/10.1186/s13321-015-0081-7
3. M.J. Harvey, N.J. Mason, A. McLean, P. Murray-Rust, H.S. Rzepa, and J.J.P. Stewart, "Standards-based curation of a decade-old digital repository dataset of molecular information", Journal of Cheminformatics, vol. 7, 2015. https://doi.org/10.1186/s13321-015-0093-3
4. H.S. Rzepa, "Chemical datuments as scientific enablers", Journal of Cheminformatics, vol. 5, 2013. https://doi.org/10.1186/1758-2946-5-6
5. H.S. Rzepa, "C 19 H 28 N 9 O 10 P 1", 2012. https://doi.org/10.14469/ch/13514
6. M.J. Gomes, L.F. Pinto, P.M. Glória, H.S. Rzepa, S. Prabhakar, and A.M. Lobo, "N-heteroatom substitution effect in 3-aza-cope rearrangements", Chemistry Central Journal, vol. 7, 2013. https://doi.org/10.1186/1752-153x-7-94
7. H.S. Rzepa, "C 11 H 16 N 1 O 5 -1", 2011. https://doi.org/10.14469/ch/8551
8. F.L. Cherblanc, Y. Lo, W.A. Herrebout, P. Bultinck, H.S. Rzepa, and M.J. Fuchter, "Mechanistic and Chiroptical Studies on the Desulfurization of Epidithiodioxopiperazines Reveal Universal Retention of Configuration at the Bridgehead Carbon Atoms", The Journal of Organic Chemistry, vol. 78, pp. 11646-11655, 2013. https://doi.org/10.1021/jo401316a
9. D. Christopher Braddock, J. Clarke, and H.S. Rzepa, "Epoxidation of bromoallenes connects red algae metabolites by an intersecting bromoallene oxide – Favorskii manifold", Chemical Communications, vol. 49, pp. 11176, 2013. https://doi.org/10.1039/c3cc46720a
10. H.S. Rzepa, "C 6 H 9 Br 1 O 2", 2013. https://doi.org/10.14469/ch/18928
11. A. Armstrong, R.A. Boto, P. Dingwall, J. Contreras-García, M.J. Harvey, N.J. Mason, and H.S. Rzepa, "The Houk–List transition states for organocatalytic mechanisms revisited", Chem. Sci., vol. 5, pp. 2057-2071, 2014. https://doi.org/10.1039/c3sc53416b
12. N. Mason, and N. Mason, "C 18 H 23 N 1 O 3", 2013. https://doi.org/10.14469/ch/18808
13. S. Lal, H.S. Rzepa, and S. Díez-González, "Catalytic and Computational Studies of N-Heterocyclic Carbene or Phosphine-Containing Copper(I) Complexes for the Synthesis of 5-Iodo-1,2,3-Triazoles", ACS Catalysis, vol. 4, pp. 2274-2287, 2014. https://doi.org/10.1021/cs500326e
14. H.S. Rzepa, "C 15 H 12 I 1 N 3", 2011. https://doi.org/10.14469/ch/10258
15. K.K.(. Hii, H.S. Rzepa, and E.H. Smith, "Asymmetric Epoxidation: A Twinned Laboratory and Molecular Modeling Experiment for Upper-Level Organic Chemistry Students", Journal of Chemical Education, vol. 92, pp. 1385-1389, 2015. https://doi.org/10.1021/ed500398e
16. H.S. Rzepa, "C 21 H 32 O 1 S 2", 2015. https://doi.org/10.14469/ch/177853
17. H.S. Rzepa, N. Mason, A. Mclean, and M. Harvey, "Interoperability for Data Repositories. Machine Methods for Retrieving Data for Display or Mining Utilising Persistent (data-DOI) Identifiers", 2014. https://doi.org/10.6084/m9.figshare.1266197
18. T. Lanyon-Hogg, M. Ritzefeld, N. Masumoto, A.I. Magee, H.S. Rzepa, and E.W. Tate, "Modulation of Amide Bond Rotamers in 5-Acyl-6,7-dihydrothieno[3,2-<i>c</i>]pyridines", The Journal of Organic Chemistry, vol. 80, pp. 4370-4377, 2015. https://doi.org/10.1021/acs.joc.5b00205
19. H.S. Rzepa, "C 15 H 15 N 1 O 1 S 1", 2014. https://doi.org/10.14469/ch/25041
20. H.S. Rzepa, M.J. Harvey, N.J. Mason, A. Mclean, P. Murray-Rust, and J.J.P. Stewart, "Standards-based curation of a decade-old digital repository dataset of molecular information.", 2015. https://doi.org/10.6084/m9.figshare.1330063

The first conference devoted to scientific uses of Wikipedia has just finished; there was lots of fascinating stuff but here I concentrate on one report that I thought was especially interesting. To introduce it, I need first to introduce WikiData. This is part of the WikiMedia ecosystem, and one of the newest. The basic concept is really simple.

1. It is a repository for data objects; 14,757,419 of them as I write this to be precise. These are called items, and each has an ID, prefaced with the letter Q. An example might be mauveine, which is Q421898.
2. Any item can have one or more properties which can only be selected from a controlled list, of which there are around 3000.^† An example here might be an individual’s ORCID identifier, which is P496. ORCID is also an item, Q51044.
3. As with Wikipedia itself, WikiData also has a set of community rules which contributors have to follow. One of the rules in Wikipedia (the COI or conflict of interest rule) which deprecates an interested party from making a significant contribution to any page. Items in Wikidata have a looser COI code; facts are basically facts rather than opinions, but their provenance still matters of course.

With the basic structure set out, I will now describe what I heard today.

1. An item can be a citation (to the scientific published literature), of which there are currently around 76 million, although currently nothing like that number are currently in WikiData.
2. One of the properties of a citation item is its DOI or digital object identifier (P356), which would nowadays be regarded as in effect mandatory. Citations can have other properties, which would be populated from CrossRef or DataCite such as metadata associated with e.g. the DOI itself; the journal, the authors, the date, etc. Citations from DataCite can in fact have far richer metadata than the usual, if you follow this link you can see an example of such data properties.
3. But here is the new stuff. Citations as items can have more subtle properties. Thus a citation could be invoked with a property: A disagrees with B, where A and B are both items (or perhaps properties).

You can see from this that allowing a citation to have such properties can potentially revolutionise the way a scientific article can be constructed. When a citation is invoked, the context the authors wish that citation to have can be added. Contrast this with the context-free way in which articles currently cite other articles. And as with anything in WikiData, instances can be counted, the context in which instances occur can be identified and statistics accumulated.

The way it might work is not so much that any interested reader (a human) would browse through WikiData. Instead it is something that a machine (software) might invoke. In Wikipedia for example, one can transclude or subsume into the article an item from Wikidata. This could be a citation, which you could transclude with one or more associated properties. In chemistry at the moment, the most prominent objects that are constructed from such Wikidata transclusions are ChemBoxes, or tables of properties of molecules as items (Q52426). This is done dynamically at the time of reading the Wikipedia article and so you can imagine that such transclusions can respond as the values of properties are updated/corrected/extended. Unfortunately I do not (yet) know of a good example of all of this which can be linked to here. If any do come to light, I will try to remember to add them here.

As often happens, the concepts above are not entirely new; many were already present in a variation of the Wiki called the Semantic MediaWiki and experiments in chemistry were tried as early as 2007.^‡ But WikiData is far easier to use and in symbiosis with a conventional Wiki it might just start to fly now.

The implications of all of this for the way in which a scientific article might work are deep from many different perspectives. I do wonder whether all this data-rich context in which a scientific article or narrative might be couched will be welcomed by either publishers or indeed authors. Perhaps the emotions that humans have but which machines do not will in fact dominate. But it does appear to have the potential for a sea-change in how scientists exchange information.

^†The number of itemised molecules recently reached 100 million, and there are a few thousand (>? <?) well defined properties that can be associated with molecules. So the whole of known molecular chemistry is actually not that different in scale from the current Wikidata.

^‡Semantic wiki as a model for an intelligent chemistry journal, Rzepa, Henry S. Abstracts of Papers, 233rd ACS National Meeting, Chicago, IL, United States, March 25-29, 2007, CINF-053. Abstract and talk.