PDF icon Download PDF
Methods Inf Med 2020; 59(04/05): 117-118
DOI: 10.1055/s-0040-1721726
Editorial

The Challenge of the Effective Implementation of FAIR Principles in Biomedical Research

Carlos Luis Parra-Calderón
1   TI Research, Hospitales Universitarios Virgen del Rocío—Avda. Manuel Siurot, s/n Centro de Documentación Clínica Hospitales Universitarios Virgen del Rocío, Seville, Seville 41013, Spain
,
Ferran Sanz
2   Group of Research and Innovation in Biomedical Informatics, Biomedical Engineering and Health Economy, Institute of Biomedicine of Seville/Virgen del Rocío University Hospital/CSIC/University of Seville, Seville, Spain
,
Leslie D. McIntosh
3   Washington University in St. Louis, Missouri, United States
› Author Affiliations
› Further Information
   Permissions and Reprints
Preview

Background

Developing the Open Community for the Application of FAIR in Biomedical Research

The vision of implementing FAIR (findable, accessible, interoperable, and reusable) principles in health research over the next years includes a vast, open community of health research institutions and researchers fully engaged in enhancing their knowledge-based economy and their research excellence by adopting the FAIR data guiding principles. We envision high-quality health research and routine care data to be shared and reused in a secure, controlled, and legally compliant environment in both human and machine-readable formats. The idea is to accelerate knowledge discovery while reducing biases and enhancing the strength and quality of the scientific evidence raised by the FAIR community members.


 

Pillars for an Effective Incorporation of FAIR in the Biomedical Domain

Key pillars for an effective incorporation of the FAIR principles in the biomedical domain are as follows:

  • Build an open biomedical FAIR community composed of biomedical research institutions and health care organizations, as well as individual data scientists and professionals working in such institutions. This community should operate in synergy with related national and international initiatives based on innovative public engagement strategies.

  • Disseminate information: an effective outreach strategy targeting potential FAIR community members, relevant stakeholders, health informatics researchers, and patients who share their data will raise awareness on the advantages of the sharing and reuse of data derived from health research and care and will provide training on the FAIRification principles and processes.

  • Enhance health research data quality: there are expectations to build in and improve data quality as a result of the application of a FAIR data certification roadmap.

  • Research in tools for building and supporting the implementation of the FAIR data principles in health research and care institutions, while enabling the development of further data-driven innovative services.

  • Demonstrate the impact of adopting FAIR principles for the society.


 

The Vision of the Guest Editors

This Focus Theme “Application of FAIR principles in Health Research” aims to bring new knowledge about FAIRified health research datasets, as well as from new and more efficient methods of modeling, implementing, and evaluating the FAIRification processes.

The goal of the present Focus Theme of Methods of Information in Medicine devoted to the application of FAIR principles in the health domain is three-fold as follows: (1) highlighting the application of the FAIR principles in the biomedical research community; (2) showing progress in the implementation of these principles in health-related data collections, and 3) Demonstrating how the use of FAIR principles can contribute to the discovery of new knowledge and the development of digital health services. Combined, these topics may provide a useful perspective on the opportunities of accelerating, as well as the associated challenges, that data science offers to health research and innovation.


 

Issues for an Effective Implementation of the FAIR Principles in the Health Domain

  • The analysis of the alignment and existing gaps between the FAIR principles and the biomedical and health data interoperability and terminologies standards.

  • Evaluation of FAIR application on biomedical research.

  • Metrics models for the FAIRification in the health domain.

  • Particularities of FAIRification in the case of electronic health records (EHRs).


 


Publication History

Received: 06 November 2020

Accepted: 07 November 2020

Article published online:
22 February 2021

© 2021. Thieme. All rights reserved.

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany