Description
With the acceptance of the FAIR Data principles in the research community, the requirements and standards of data publications have changed significantly. While the FAIR principles are explicitly targeted at metadata and digital resources such as APIs, workflows, ontologies, and models, these digital objects can not be made FAIR without supporting infrastructure services that are themselves FAIR.
We are developing BEXIS2, an open-source, community-driven, web-based research data management system. In 2021, we conducted the self-assessment using the FAIR indicators, definitions, and criteria provided in the FAIR Data Maturity Model. The self-assessment results indicated that BEXIS2 remarkably conforms and supports FAIR indicators.
In our poster, we show the results of the FAIR self-assessment, our current developments with regard to improvements of the FAIR data principles, and our very next ideas for improving these aspects.
| Type of Poster | A challenge |
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