Posts Tagged ‘chemical structures’

The challenges in curating research data: one case study.

Friday, April 28th, 2017

Research data (and its management) is rapidly emerging as a focal point for the development of research dissemination practices. An important aspect of ensuring that such data remains fit for purpose is identifying what curation activities need to be associated with it. Here I revisit one particular case study associated with the molecular structure of a product identified from a photolysis reaction[1] and the curation of the crystallographic data associated with this study.

This particular dataset (CSD, dataDOI: 10.5517/cctnx5j) is associated with an article entitled “Single-Crystal X-ray Structure of 1,3-Dimethylcyclobutadiene by Confinement in a Crystalline Matrix“.[1] Data for crystal structures supporting a research article is required (at least in part) to be deposited into the Cambridge structure database (internal reference MUWMEX) and for which a significant level of curation is performed. Although the definition of the term curation has evolved over the last few years, here I take it to include the following:

  1. Identification of appropriate metadata describing the data. For molecules, this would include any identifiers such as the name of the molecule and the connectivities of the atoms constituting that molecule.
  2. The submission of this metadata to a suitable aggregator, such as e.g. DataCite and its inclusion in any other databases associated with the data. These two tests are part of the FAIR data guidelines[2], covering the F (findable) and A (accessible).
  3. Performing any validation tests for the data that can be identified. With crystal structure data in CIF format, this is defined by the utility checkCIF and helps to ensure the I (inter-operable) of FAIR. The R refers in part to the licenses under which the data can be re-used.

On (it has to be said rare) occasions, these procedures can lead to a disparity between the author’s conclusions arrived on the basis of their acquired data and the metadata identified by the independent curators. This difference is most obviously illustrated in this case study by the chemical names inferred by the curation process for the structure represented by the data in the CSD:

  • chemical name: “tetrakis(Guanidinium) 25,26,27,28-tetrahydroxycalix(4)arene-5,11,17,23-tetrasulfonate 1,5-dimethyl-2-oxabicyclo[2.2.0]hex-5-en-3-one clathrate trihydrate
  • chemical name synonym: “tetrakis(Guanidinium) tetra-p-sulfocalix(4)arene 1,3-dimethylcyclobutadiene carbon dioxide clathrate trihydrate“.

Only the synonym agrees with the title given by the original authors in their publication.[1] One might indeed strongly argue that these two names are not in fact synonyms, since they refer to quite different chemical structures with different atom connectivities. A search of the database for the sub-structure corresponding to 1,3-dimethylcyclobutadiene does not reveal any hits and so the information implied by this synonym is not recorded in the index created for the CSD database.

I asked the scientific editors of the CSD for some guidance on the curation procedures applied to crystal structure datasets and they have kindly allowed me to quote some of this.

  1. “In cases such as this, we as editors are sometimes faced with conflicting information and have to try our best to strike a balance between the data presented in the CIF, a published interpretation and our knowledge based on the information already in the CSD”.
  2. “In areas where there is a particular conflict between these, we often would include a comment (usually in the Remarks or Disorder field as appropriate)”. For this particular dataset, one finds the following under the Disorder field:
    • “Under UV radiation the clathrated pyrone molecule converts to a disordered mixture of square-planar 1, 3-dimethylcyclobutadiene and rectangular-bent 1, 3-dimethylcyclobutadiene in van der Waals contact with a carbon dioxide molecule. The ratio of the square-planar to rectangular-bent 1, 3-dimethylcyclobutadiene clathrate is modelled with occupancies 0.6292:0.3708”.
    • It is not entirely obvious however whether this last comment originates from the original authors or from the data curators. It does not resolve the difference between the assigned chemical name and the indicated chemical name synonym.
  3. “In the case of MUWMEX, I think that the editor produced a diagram (below) which seems chemically reasonable based on the crystallographic data with which we were provided and tried to cover the situation regarding disorder, van der Waals contacts etc in the ‘Disorder’ field. At this point, it is left to the CSD user to decide for themselves.”

We have arrived at a point where the CSD user must indeed decide what the species described by this dataset actually is. Ideally, the best recourse would be to acquire the original data in full and repeat the crystallographic analysis. This is an aspect of the curation of crystallographic data that is not conducted as part of the current processes, which would require as a minimum a superset known as the hkl information to be present in the data. Again, to quote the CSD scientific editors:

  1. “With regard to your question: Is there any mechanism in the Conquest search to identify structures where the hkl information is present? I understand that it is not currently possible to do this in ConQuest. It is, however, possible … to access structure factor data (where available) using Access Structures.”

For MUWMEX, the hkl information is not present in the CSD dataset and in 2010 when the structure was published would have to be obtained directly from the authors. By 2016 however, its presence in deposited datasets was becoming far more common. It is worth pointing out that even the hkl information is not the complete data recorded for the experiment.  That is represented by the original image files recording the X-ray diffractions. This latter is hardly ever available as FAIR data even nowadays.

I hope I have here illustrated at least some of the challenging aspects of curating scientific data and the issues that can arise when derived metadata (in this case the name and the atom connectivities of a molecule) reveal conflicts with the original interpretations. This for an area of chemistry where both the data deposition and its curation is a very mature subject, having operated for ~52 years now. It is still a process that requires the intervention of skilled curators of the data, but perhaps even more importantly it reveals the need to identify even more strictly what the provenance of the interpretations is. Should the CSD curation rest merely at the stage of teasing out and flagging inconsistencies and allowing the user to then take over to resolve the conflicts? Should it be more active, in re-analyzing data for each entry where conflicts have been detected? Perhaps the latter is not practical now, but it might be in the near future. What is certain is that with increasing availability of FAIR data these sorts of issues will increasingly come to the fore. And not just for the very well understood case of crystallographic data but for many other types of data.

References

  1. Y. Legrand, A. van der Lee, and M. Barboiu, "Single-Crystal X-ray Structure of 1,3-Dimethylcyclobutadiene by Confinement in a Crystalline Matrix", Science, vol. 329, pp. 299-302, 2010. https://doi.org/10.1126/science.1188002
  2. M.D. Wilkinson, M. Dumontier, I.J. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J. Boiten, L.B. da Silva Santos, P.E. Bourne, J. Bouwman, A.J. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C.T. Evelo, R. Finkers, A. Gonzalez-Beltran, A.J. Gray, P. Groth, C. Goble, J.S. Grethe, J. Heringa, P.A. ’t Hoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S.J. Lusher, M.E. Martone, A. Mons, A.L. Packer, B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S. Sansone, E. Schultes, T. Sengstag, T. Slater, G. Strawn, M.A. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop, A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, and B. Mons, "The FAIR Guiding Principles for scientific data management and stewardship", Scientific Data, vol. 3, 2016. https://doi.org/10.1038/sdata.2016.18

Global initiatives in research data management and discovery: searching metadata.

Monday, March 7th, 2016

The upcoming ACS national meeting in San Diego has a CINF (chemical information division) session entitled "Global initiatives in research data management and discovery". I have highlighted here just one slide from my contribution to this session, which addresses the discovery aspect of the session.

Data, if you think about it, is rarely discoverable other than by intimate association with a narrative or journal article. Even then, the standard procedure is to identify the article itself as being of interest, and then digging out the "supporting information", which normally takes the form of a single paginated PDF document. If you are truly lucky, you might also get a CIF file (for crystal structures). But such data has little life of its own outside of its parent, the article. Put another way, it has no metadata it can call its own (metadata is data about an object, in this case research data). An alternative is to try to find the data by searching conventional databases such as CAS,  Beilstein/Reaxys or CSD, and there of course the searches can be very precise. But (someone) has to pay the bills for such accessibility.

We are now starting to see quite different solutions to finding data (the F in FAIR data, the other letters representing accessibility, interoperability and re-usability). These solutions depend on metadata being a part of the solution from the outset, rather than any afterthought produced as a commercial solution. The collection of metadata is part of the overall process called RDM, or research data management, perhaps even the most important part of it. In exchange for identifying metadata about one's data, one gets back a "receipt" in the form of a persistent identifier for the data, more commonly known as a DOI. The agency that issues the DOI also undertakes to look after the donated metadata, and to make it searchable. The table below shows eight searches of such metadata, one example of how to acquire statistics relating to the usage of the data and one search of how to find repositories containing the data.

Search queries enabled by the use of metadata in data publication
# Search query* Instances retrieved:
1 http://search.datacite.org/ui?q=alternateIdentifier:InChIKey:*  InChI identifier
2 http://search.datacite.org/ui?q=alternateIdentifier:InChI:*  InChI key 
3 http://search.datacite.org/ui?q=alternateIdentifier:InChIKey:CULPUXIDFLIQBT-UHFFFAOYSA-N InChI key CULPUXIDFLIQBT-UHFFFAOYSA-N 
4 http://search.datacite.org/ui?q=ORCID:0000-0002-8635-8390+alternateIdentifier:InChIKey:* ORCID 0000-0002-8635-8390 AND (boolean) InChI key.
5 http://search.datacite.org/ui?q=ORCID:0000-0002-8635-8390+alternateIdentifier:InChI:InChI=1S/C9H11N5O3* ORCID 0000-0002-8635-8390 AND (boolean) + InChI string 1S/C9H11N5O3 with the * wild.
6 http://search.datacite.org/ui?q=has_media:true&fq=prefix:10.14469 Has content media for Publisher 10.14469 (Imperial College)
7 http://search.datacite.org/ui?q=format:chemical/x-* Data format type chemical/x-* 
8 http://search.datacite.org/api?&q=prefix:10.14469& fq=alternateIdentifier:InChIKey:*& fl=doi,title,alternateIdentifier& wt=json&rows=15
http://api.labs.datacite.org/works?q=prefix:10.14469+AND+alternateIdentifier:InChIKey:*
First 15 hits in JSON format, batch query mode
9 http://stats.datacite.org/?fq=datacentre_facet:"BL.IMPERIAL – Imperial College London" resolution statistics for publisher 10.14469 (Imperial College) per month
10 http://service.re3data.org/search?query=&subjects[]=31 Chemistry Research data repository search for Chemistry (135 hits)

In this instance the three MIME media types are chemical/x-wavefunction, chemical/x-gaussian-checkpoint and chemical/x-gaussian-log. See[1] for chemical MIME (multipurpose internet media extensions).


Anyone familiar with the standard ways of finding data (CAS, CSD, Reaxys) will appreciate that the above does not yet have the finesse to find eg sub-structures of chemical structures, synthetic procedures or molecular properties. My including it here is primarily to show some of the potential such systems have, and to remark particularly that the batch query capability of this infrastructure could indeed be used in the future to construct much more sophisticated systems.  Oh, and to the end-user at least, the searches shown above do not require institutional licenses to use. Both the data and its metadata is free, mostly with a CC0 or CC BY 3.0 license for re-use (the R of FAIR).

If more of interest related to this topic emerges at the ACS session,  I will report back here.

References

  1. H.S. Rzepa, P. Murray-Rust, and B.J. Whitaker, "The Application of Chemical Multipurpose Internet Mail Extensions (Chemical MIME) Internet Standards to Electronic Mail and World Wide Web Information Exchange", Journal of Chemical Information and Computer Sciences, vol. 38, pp. 976-982, 1998. https://doi.org/10.1021/ci9803233

Chemistry data round-tripping. Has there been ANY progress?

Monday, December 2nd, 2013

This is one of those topics that seems to crop up every three years or so. Since then, new versions of operating systems, new versions of programs, mobile devices and perhaps some progress? 

Right, I will briefly recapitulate. Chemical structure diagrams are special; they contain chemical semantics (what an atom is, what a bond is, stereochemistry, charges, etc). One needs special programs to represent this. Take two well-known ones. ChemBioDraw V 13 is the latest in a long line dating back to 1985 or so. A newcomer is ChemDoodle, just updated to version 6. The idea is you express your molecule, and capture some of its semantics using one of these programs. And then paste the data into another veritable word processor, Word (also dating back to around 1984). Then send the Word document to a colleague. Who might want to copy the structure back out, and put it back into ChemBioDraw/ChemDoodle. And put those semantics to good use, by editing it, or re-purposing the information. This is round-tripping the data. Its been almost 30 years, surely the process should be seamless by now? Wrong!

One problem is that the “exchange-particle” is the clipboard, yet another ancient and presumed mature technology. Its invisible of course, we rarely get to see it. And very operating system specific! So what is the current state of play? Round tripping ChemBiodraw structures across a single operating system might work. Well, it currently does for just one of the two most common desktop operating systems (remember, Word is provided by the originator of one of these operating systems). The other program, ChemDoodle round trips within both operating systems.

But, here is the key point, not across operating systems. Paste either a ChemBioDraw or a Chemdoodle structure into Word on one of these OS, and try re-editing that diagram on the version of Word on the other OS. The data is lost unless you have the “right” operating system.

An experiment I have not tried, but regarding which I would welcome any feedback is to factor in the two newest operating systems, this time for mobile devices such as tablets and phones. Lets not even worry whether different flavours of one of these mobile OSs are compatible. Apps for drawing chemical structures are available for both of these. Here, the amazing clipboard still exists. One now has four OS to consider, and four homogenous permutations and a minimum of six heterogenous round trips the data could try to take for any given app. We do not even consider app2app transfers not involving discrete intermediate documents. I would predict that only a few of these permutations preserve round-tripped data and its semantics.

Perhaps we need to look at it in a different way? One simply avoids putting data from one program into another. Chemical data is kept in its own files, never mixed with data from other programs, but always kept/sent separately. Pre-1984 and the clipboard, this might have made sense. But in an era when XML was invented around 17 years ago to allow data to fully retain semantic information in any environment it finds itself in, it seems surprising that we still have this situation.

I mention all of this, since there is a current refocusing on the importance of data; “emancipating data” is now important. But the reality is that much current software destroys the semantics in data at almost every turn. Thirty years of no progress then. But what of Chem4Word, a combination of differently namespaced  XML in which the chemistry is expressed in CML (it is only available for a single operating system!). I will perhaps devote a separate post to that one; first I have to try a few experiments!

Data-round-tripping: moving chemical data around.

Saturday, November 20th, 2010

For those of us who were around in 1985, an important chemical IT innovation occurred. We could acquire a computer which could be used to draw chemical structures in one application, and via a mysterious and mostly invisible entity called the clipboard, paste it into a word processor (it was called a Macintosh). Perchance even print the result on a laserprinter. Most students of the present age have no idea what we used to do before this innovation! Perhaps not in 1985, but at some stage shortly thereafter, and in effect without most people noticing, the return journey also started working, the so-called round trip. It seemed natural that a chemical structure diagram subjected to this treatment could still be chemically edited, and that it could make the round trip repeatedly. Little did we realise how fragile this round trip might be. Years later, the computer and its clipboard, the chemistry software, and the word processor had all moved on many generations (it is important to flag that three different vendors were involved, all using proprietary formats to weave their magic). And (on a Mac at least) the round-tripping no longer worked. Upon its return to (Chemdraw in this instance), it had been rendered inert, un-editable, and devoid of semantic meaning unless a human intervened. By the way, this process of data-loss is easily demonstrated even on this blog. The chemical diagrams you see here are similarly devoid of data, being merely bit-mapped JPG images. Which is why, on many of these posts, I put in the caption Click for 3D, which gives you access to the chemical data proper (in CML or other formats). And I throw in a digital repository identifier for good measure should you want a full dataset.

It is only now that we (more specifically, this user) understand what had happened under-the-hood to break this round-tripping. In 1984, when Apple produced the Mac, they also produced a most interesting data format called PICT. A human saw the PICT as a PICTure, but the computer saw more. It (could) see additional data embedded in the PICT. The clipboard supported the PICT format, which meant that both picture and data could be transferred between programs. And ChemDraw and Word also understood this. Hence the ability to round-trip noted above (it has to be said between specifically these programs).

Times moved on and the limitations of PICT set in. Apple refocussed on the PDF format. Related, notice, to the Postscript format that Adobe had introduced in order to allow high quality laserprinting. PICT support was abandoned, and the various components no longer carried recognisable data (specifically the clipboard or the ability of Word to recognise the data). Round-tripping broke. Does this matter? Well, one colleague where I work had accumulated more than 1000 chemical diagrams, which he decided to store in Powerpoint (and yes, he threw the original Chemdraw files away). The day came when he wanted to round trip one of them. And of course he could not. He was rather upset I have to say!

PDF was not really a format designed to carry data (see DOI: 10.1021/ci9003688). But, bless their hearts, the three vendors involved in this story all agreed to support data embedded in the PDF hamburger (and Abobe to tolerate it) and now once again, a structure diagram can move into an Office program (on Mac) and out again and retain its chemical integrity. What lessons can be learnt?

  1. Firstly, out of side, out of mind. The clipboard is truly mostly out of sight, and it was not really designed from the outset to preserve data properly. Nowadays I wonder whether clipboards in general recognise XML (and hence CML) and preserve it. I truly do not know. But they should.
  2. Secondly, any system which relies on three or four commercial vendors, who at least in the past, devised proprietary formats which they could change without warning, is bound to be fragile.
  3. We have learnt that data is valuable. More so than the representation of it (i.e. a 2D or 3D structure diagram). But when its lost, the users should care! And tell the vendors.
  4. Peter Murray-Rust and his team have produced CML4Word (or as Microsoft call it, Chemistry add-in for Word). At its heart is data integrity. Fantastic! But I wonder if it survives on Microsoft’s clipboard (I know it does not on Apple’s, since CML4Word is not available on that OS. And is unlikely to ever become so).
  5. And I can see history about to repeat itself. The same seems about to happen on new devices such as the Apple iPad. It too has copy/paste via a clipboard. I bet this will not round trip chemistry (or much other) data! Want to bet that the lessons of this story have not yet been learnt?

Oh, for those who wish to round-trip chemistry on a Mac, you will have to acquire ChemDraw 12.0.2 and Word 2011 (version 14.01), as well as OS X 10.6 for it to work.