{"references": ["(2016) M. Wilkinson, M. Dumontier, I. Aalbersberg, et al. The FAIR Guiding Principles for scientific data management and stewardship, Sci Data, 3:160018", "(2019) T. Gomez-Diaz, T. Recio. On the evaluation of research software: the CDUR procedure, F1000Research 2019, 8:1353", "(2020-21) T. Gomez-Diaz, T. Recio. Towards an Open Science definition as a political and legal framework: on the sharing and dissemination of research outputs, POLIS N.19. V3 dated 28 february 2021 available on Zenodo", "(2021) T. Gomez-Diaz, T. Recio. Open comments on the Task Force SIRS report: Scholarly Infrastructures for Research Software (EOSC Executive Board, EOSCArchitecture), Research Ideas and Outcomes (RIO), 7: e63872", "(2022) European Commission. Directorate-General for Research and Innovation, European Research Data Landscape: final report, Publications Office of the European Union", "(2022) T. Gomez-Diaz, T. Recio. Research Software vs. Research Data I: Towards a Research Data definition in the Open Science context (Definition), F1000Research 2022, 11:118", "(2022) T. Gomez-Diaz, T. Recio. Research Software vs. Research Data II: Protocols for Research Data dissemination and evaluation in the Open Science context (Dissemination, Evaluation/CDUR, FAIR), F1000Research 2022, 11:117"]}

In this work we propose to study the relationship between recent proposed work for research data evaluation and the FAIR data principles. The evaluation protocol that we consider includes four steps for data citation, dissemination, use and research impact. The FAIR data principles include steps to ensure that disseminated data becomes findable, accessible, interoperable and reusable. In this work we propose to highlight the connections between the different steps of both proposals. The conclusions will enhance both methodologies and will contribute to make FAIRER research data and FAIRER research outputs.

The poster is completed with an abstract and slides for its presentation.