Authors : Agustin Barba, Santiago Dominguez, Carlos Cobas, David P. Martinsen, Charles Romain, Henry S. Rzepa; Felipe Seoane
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.