Towards FAIR principles for research software

Data Science

article

Anna-Lena Lamprecht¹  Leyla Garcia²  Mateusz Kuzak³  Carlos Martinez³  Ricardo Arcila⁵  Eva Martin Del Pico⁶  Victoria Dominguez Del Angel⁷  Stephanie van de Sandt⁸  Jon Ison⁹  Paula Andrea Martinez^1,10  Peter McQuilton^1,11  Alfonso Valencia⁶  Jennifer Harrow^1,13  Fotis Psomopoulos^1,14  Josep Ll. Gelpi⁶  Neil Chue Hong^1,16  Carole Goble^1,18  Salvador Capella-Gutierrez⁶ 

[1] Utrecht University;ZBMED Information Centre for Life Sciences;Netherlands eScience Center;Dutch Techcentre for Life Sciences;EMBL-EBI;Barcelona Supercomputing Center;L’Institut Français de Bioinformatique;CERN;National Life Science Supercomputing Center, Technical University of Denmark;National Imaging Facility;Oxford e-Research Centre;Institució Catalana de Recerca i Estudis Avançats;ELIXIR Hub;Institute of Applied Biosciences;University of Barcelona;Software Sustainability Institute;EPCC, University of Edinburgh;University of Manchester

关键词: FAIR;    research software;    software sustainability;    reproducible research;   

DOI  :  10.3233/DS-190026

来源: IOS Press

【 摘 要 】

The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. Until now the FAIR principles have been mostly applied to research data. The ideas behind these principles are, however, also directly relevant to research software. Hence there is a distinct need to explore how the FAIR principles can be applied to software. In this work, we aim to summarize the current status of the debate around FAIR and software, as basis for the development of community-agreed principles for FAIR research software in the future. We discuss what makes software different from data with regard to the application of the FAIR principles, and which desired characteristics of research software go beyond FAIR. Then we present an analysis of where the existing principles can directly be applied to software, where they need to be adapted or reinterpreted, and where the definition of additional principles is required. Here interoperability has proven to be the most challenging principle, calling for particular attention in future discussions. Finally, we outline next steps on the way towards definite FAIR principles for research software.

【 授权许可】

Unknown