Choosing a dataset

Phil Gribbon at the FAIRplus SME event
Phil Gribbon (Fraunhofer) presenting the work of FAIRplus Work Package 1, who are identifying datasets to FAIRify.

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:

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

Work completed

First three datasets selected and available June 2019
A report containing the selection criteria and guidelines for data sources from IMI projects and EFPIA internal databases December 2019
The first 15 IMI datasets selected and available for inclusion in WP2-4 processes. December 2020

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.

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