Ten simple rules for making training materials FAIR

• Published in: PLoS computational biology 2020-05, Vol.16 (5), p.e1007854-e1007854
• Main Authors: Garcia, Leyla, Batut, Bérénice, Burke, Melissa L, Kuzak, Mateusz, Psomopoulos, Fotis, Arcila, Ricardo, Attwood, Teresa K, Beard, Niall, Carvalho-Silva, Denise, Dimopoulos, Alexandros C, Del Angel, Victoria Dominguez, Dumontier, Michel, Gurwitz, Kim T, Krause, Roland, McQuilton, Peter, Le Pera, Loredana, Morgan, Sarah L, Rauste, Päivi, Via, Allegra, Kahlem, Pascal, Rustici, Gabriella, van Gelder, Celia W G, Palagi, Patricia M
• Format: Article
• Language: English
• Subjects: Bioinformatics; Biology - education; Biology and Life Sciences; Collaboration; Computational Biology; Computer and Information Sciences; Computer applications; Computer science; Computer-Assisted Instruction - standards; Computers; Datasets; Design and construction; Digital Object Identifier; Education; Genomes; Guidelines as Topic; Humanities and Social Sciences; Humans; Information Storage and Retrieval; Instructional materials; Laboratories; Life sciences; Metadata; Metric system; Molecular biology; Ontology; People and Places; Research and Analysis Methods; Scientists; Social Sciences; Training; URLs
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1007854

Everything we do today is becoming more and more reliant on the use of computers. The field of biology is no exception; but most biologists receive little or no formal preparation for the increasingly computational aspects of their discipline. In consequence, informal training courses are often needed to plug the gaps; and the demand for such training is growing worldwide. To meet this demand, some training programs are being expanded, and new ones are being developed. Key to both scenarios is the creation of new course materials. Rather than starting from scratch, however, it's sometimes possible to repurpose materials that already exist. Yet finding suitable materials online can be difficult: They're often widely scattered across the internet or hidden in their home institutions, with no systematic way to find them. This is a common problem for all digital objects. The scientific community has attempted to address this issue by developing a set of rules (which have been called the Findable, Accessible, Interoperable and Reusable [FAIR] principles) to make such objects more findable and reusable. Here, we show how to apply these rules to help make training materials easier to find, (re)use, and adapt, for the benefit of all.