The promise and perils of FAIR Data

Michel Dumontier 

FAIR data are data which meet the principles of findability, accessibility, interoperability, and reusability. The lecture will explain the need for FAIR data and the history of the FAIR principles. It will then discuss the FAIR principles themselves and examine guidelines, standards, and repositories for FAIR digital objects. In this context, it will also introduce the TRUST principles for repositories, where TRUST stands for transparency, responsibility, user focus, sustainability and technology. The lecture will also look at methods to automatically assess FAIRness and discuss how we can move towards an Internet of FAIR Data and Services. Finally, the lecture will explore applications of the FAIR principles in biomedicine.

Outline:

• The need for FAIR data
• The history of the FAIR principles
• The FAIR principles
• Guidelines, Standards, and Repositories for FAIR Digital Objects
  • TRUST principles for Repositories
  • Data
  • Software
  • Mappings
  • Queries
• Methods to automatically assess FAIRness
• Towards an Internet of FAIR Data and Services
  • Semantic Data Integration
  • SPARQL as a universal query language for data retrieval, computation, comparison
  • Applications in biomedicine