none 10.1021/acsomega.8b03005 American Chemical Society (ACS) American Chemical Society 316 104767077 300900 2026090210071663800 10.1021 2026-09-02T14:07:25Z 2019-02-14T09:47:25Z 22 ACS Omega 2470-1343 02 14 2019 02 28 2019 4 2 Agustin Barba Mestrelab Research, S.L. , Feliciano Barrera 9B − Bajo , , Santiago de Compostela, Spain, 15706 Santiago Dominguez Mestrelab Research, S.L. , Feliciano Barrera 9B − Bajo , , Santiago de Compostela, Spain, 15706 Carlos Cobas Mestrelab Research, S.L. , Feliciano Barrera 9B − Bajo , , Santiago de Compostela, Spain, 15706 David P. Martinsen David Martinsen Consulting , , , Rockville, Maryland, United States, 20850 Charles Romain Imperial College London , , 80 Wood Lane , , London, U.K., W12 0BZ http://orcid.org/0000-0002-1851-8612 Henry S. Rzepa Imperial College London , , 80 Wood Lane , , London, U.K., W12 0BZ http://orcid.org/0000-0002-8635-8390 Felipe Seoane Mestrelab Research, S.L. , Feliciano Barrera 9B − Bajo , , Santiago de Compostela, Spain, 15706 Abstract There is an increasing focus on the part of academic institutions, funding agencies, and publishers, if not researchers themselves, on preservation and sharing of research data. Motivations for sharing include research integrity, replicability, and reuse. One of the barriers to publishing data is the extra work involved in preparing data for publication once a journal article and its supporting information have been completed. In this work, a method is described to generate both human and machine-readable supporting information directly from the primary instrumental data files and to generate the metadata to ensure it is published in accordance with findable, accessible, interoperable, and reusable (FAIR) guidelines. Using this approach, both the human readable supporting information and the primary (raw) data can be submitted simultaneously with little extra effort. Although traditionally the data package would be sent to a journal publisher for publication alongside the article, the data package could also be published independently in an institutional FAIR data repository. Workflows are described that store the data packages and generate metadata appropriate for such a repository. The methods both to generate and to publish the data packages have been implemented for NMR data, but the concept is extensible to other types of spectroscopic data as well. 02 14 2019 02 28 2019 3280 3286 Imperial College London http://dx.doi.org/10.13039/501100000761 NA https://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html 10.1021/acsomega.8b03005 https://pubs.acs.org/acsodf/article/4/2/3280/1572653/Workflows-Allowing-Creation-of-Journal-Article https://pubs.acs.org/acsodf/article-pdf/4/2/3280/67782775/acsomega.8b03005.pdf https://pubs.acs.org/acsodf/article-pdf/4/2/3280/67782775/acsomega.8b03005.pdf https://pubs.acs.org/doi/pdf/10.1021/acsomega.8b03005 Nat. Prod. Rep. McAlpine 36 35 2019 10.1039/C7NP00064B The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research Acta Crystallogr. 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