Published August 31, 2020 | Version 1.0
Project milestone Open

M4.9 Report on Fair Data Assessment Mechanisms to Develop Pragmatic Concepts for Fairness Evaluation at the Dataset Level

  • 1. University of Bremen (UniHB)
  • 2. Data Archiving and Networked Services (KNAW-DANS)
  • 3. Digital Curation Centre (DCC)
  • 4. UK Data Archive

Description

This report is a milestone of the FAIRsFAIR project. It includes two main results on FAIR assessment at the dataset level:

  • The FAIRsFAIR Data Object Assessment Metrics (v0.3) specification contains 15 metrics proposed by FAIRsFAIR to evaluate the FAIRness of research data objects in Trustworthy Digital Repositories (TDRs). We improved the metrics based on a focus group's feedback and the RDA-endorsed FAIR data maturity model guidelines and specification. A total of 33 FAIR stakeholders, such as research communities, data service providers, standard bodies, and coordination fora participated in the focus group.
  • A preprint of the journal article titled ‘From Conceptualization to Implementation: FAIR Assessment of Research Data Objects’, submitted to CODATA Data Science Journal Special collection on RDA. The article summarizes the metrics development, and its two applications: an awareness-raising self-assessment tool, and a tool for automated assessment of research data FAIRness. The article also covers the initial results of testing the tools with researchers and data repositories, and future improvements including the next steps to enable FAIR data assessment in the broader research data ecosystem.

Files

M4.9_FAIRsFAIR_Report_on_FAIR_Data_Assessment_Mechanisms_to_Develop_Pragmatic_Concepts_for_FAIRness_Evaluation_20200811_v1.0.pdf

Additional details

Related works

Has part
Working paper: 10.5281/zenodo.3775793 (DOI)

Funding

FAIRsFAIR – Fostering FAIR Data Practices in Europe 831558
European Commission