A Semi-Automated Workflow for FAIR Maturity Indicators in the Life Sciences.

ABSTRACT: Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments in science. Although attitudes are increasingly favorable, data reuse remains difficult due to lack of infrastructures, standards, and policies. The FAIR (findable, accessible, interoperable, reusable) principles aim to provide recommendations to increase data reuse. Because of the broad interpretation of the FAIR principles, maturity indicators are necessary to determine the FAIRness of a dataset. In this work, we propose a reproducible computational workflow to assess data FAIRness in the life sciences. Our implementation follows principles and guidelines recommended by the maturity indicator authoring group and integrates concepts from the literature. In addition, we propose a FAIR ballo

SUBMITTER: Ammar A 

PROVIDER: S-EPMC7594074 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature