Making experimental data tables in the life sciences more FAIR: a pragmatic approach.

Daniel Jacob,Sophie Aubin,Romain David,Yves Gibon

doi:10.1093/gigascience/giaa144

Abstract

Making data compliant with the FAIR Data principles (Findable, Accessible, Interoperable, Reusable) is still a challenge for many researchers, who are not sure which criteria should be met first and how. Illustrated with experimental data tables associated with a Design of Experiments, we propose an approach that can serve as a model for research data management that allows researchers to disseminate their data by satisfying the main FAIR criteria without insurmountable efforts. More importantly, this approach aims to facilitate the FAIR compliance process by providing researchers with tools to improve their data management practices.

Highlights

The publication of research data according to the FAIR principles [1] has become a major challenge with the aim of integrating them into the overall research process
According to Jacobsen et al [3], the FAIR principles can be seen as a consolidation of good data management practices to extend management to the notion of machine reuse of data
Efforts have been undertaken for several years to propose format standards that would make it possible to disseminate data according to FAIR principles and in particular experimental data tables (e.g., ISA-TAB [5])

Summary

Introduction

The publication of research data according to the FAIR principles [1] has become a major challenge with the aim of integrating them into the overall research process (e.g., the European Commission explicitly mentions FAIR principles as a mandatory reference [2]). According to Jacobsen et al [3], the FAIR principles can be seen as a consolidation of good data management practices to extend management to the notion of machine reuse of data. This is the starting point of the approach that we propose in order to integrate these principles into the practices of researchers.

Results

Conclusion