Exchange of Clinical and Omics Data According to FAIR Principles: A Review of Open Source Solutions

Abstract

Background Due to the ongoing increase and importance of the sustainable reusability of data, the findable, accessible, interoperable, reusable or FAIR principles were developed which are also relevant in translational research. Objectives The study aims at identification of platforms by literature search that are suitable for implementation in translational research, in particular with regard to their FAIRness. Methods The collected information is summarized and compared. Results Platforms have been identified which are suitable for linking with other translational platforms with regard to documentation, long-term archiving, and processing as well as for FAIR handling of bioinformatic data. Conclusion There are already platforms in the translational environment that take FAIR principles into account and thus improve translational research. Due to the specialization of the research platforms and the fact that FAIR are only principles and not standards, the platforms have to be examined in individual cases to see whether and how they can be integrated with other platforms.