In March, I posted from the ACS meeting in San Diego on the topic of Research data: Managing spectroscopy-NMR, and noted a talk by MestreLab Research on how a tool called Mpublish in the forthcoming release of their NMR analysis software Mestrenova could help. With that release now out, the opportunity arose to test the system.
I will start by reminding that NMR data associated with a published article is (or should be) openly free: one should not need a subscription to the journal to access it (although one might in order to find it). Now, NMR data as it emerges from a spectrometer is highly sophisticated, comprising a collection of (sometimes) binary proprietary files containing the measured free induction decays (FID). Turning this raw data into an interpretable NMR spectrum, the visual form of the data that so appeals to human beings, is non trivial. This requires what may be highly sophisticated software and that in turn means that it may be a commercial product. Of course there are also examples of non-commercial open software packages that are best-of-breed; indeed in its early life-cycle MestreNova was known as MESTREC before becoming a commercial product. Could one achieve the benefits of both open and fully functional NMR data with no loss from the original instrument coupled with the ability to apply top-quality software for its analysis in an open manner? This is a demonstration of how Mpublish achieves this.
It is my hope that anyone who records NMR data and processes it using software such as MestreNova will now consider using the mechanism above to accompany their submitted articles, rather than just automatically pasting a static image of the spectrum into a PDF file as "supporting information". This is part of what is meant by "managed research data" (RDM).
One cannot help but note that many types of scientific instrument nowadays come with bespoke software for analysing the data they produce. Very often this software is unavailable to anyone who has not purchased the instrument itself. To make the data available to others, the processed data and its visual interpretation often have to be reduced, with much consequent information loss, to a lowest common denominator format such as Acrobat/PDF. Here we see a mechanism for avoiding any such information loss whilst enabling, for that dataset only, the full potential for (re)analysing the data. It will be interesting to see if other examples of this model or its equivalent emerge in the near future.
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The procedure described above works for downloading .mnova files, but a bug prevented the same procedure working for Bruker .zip archives. The release of MestreNova 11.0.1 fixes this bug. If you try
http://data.datacite.org/chemical/x-mnpub/10.14469/hpc/1095 this will now retrieve the .zip archive when you open the downloaded .mnpub file into MestreNova.
Some real-world examples of the technique described above are starting to appear.
1. Epimeric Face-Selective Oxidations and Diastereodivergent Transannular Oxonium Ion Formation-Fragmentations: Computational Modelling and Total Syntheses of 12-Epoxyobtusallene IV, 12-Epoxyobtusallene II, Obtusallene X, Marilzabicycloallene C and Marilzabicycloallene D, J. Org. Chem., 2016, doi: 10.1021/acs.joc.6b02008 with data at doi: 10.14469/hpc/1267
2. Addition of Carbon–Fluorine Bonds to a Mg(I)–Mg(I) Bond: An Equivalent of Grignard Formation in Solution, J. Am. Chem. Soc., 2016, doi: 10.1021/jacs.6b08104 with data at doi: 10.14469/hpc/1726
3. Chemoselective Polymerizations from Mixtures of Epoxide, Lactone, Anhydride, and Carbon Dioxide, J. Am. Chem. Soc., 2016, doi: 10.1021/jacs.5b13070 with data at doi: 10.14469/hpc/272
This collection DOI: 10.14469/hpc/1053 summarises our implementation of the Mpublish project. It includes an article recently published which goes into a little more detail about the implementation.