Choosing a dataset

A goal of FAIRplus is to develop a common approach for identifying and prioritising datasets to FAIRify. Both public (IMI funded) and industry (EFPIA) datasets will be included. The project will:

  1. Identify datasets from IMI consortia and example datasets from EFPIA participants, including pilot datasets from IMI projects. See the selected IMI projects.
  2. Evaluate the relevance, ELSI (Ethical, Legal and Social Implications) requirements and scientific value of datasets.
  3. Propose and implement selection criteria for dataset identification. These criteria will include availability, scientific value, and societal impact.
  4. Adjust guidelines and competency questions to help external (i.e. non-IMI and non-EFPIA) communities to FAIRify their datasets.

Next deliverables/milestones

March 2019 Established a procedure to identify ELSI issues and ascertain lawful processing and appropriate safeguards for personal data in selected datasets.
June 2019 First three datasets selected and available.
December 2019 A report containing the selection criteria and guidelines for data sources from IMI projects and EFPIA internal databases is published.

This work will be carried out by Work Package 1 (WP1) within the project. For an overview of this WP and how it interacts with the other WPs see How the project is organised.