WHAT IS IN THE FAIR TOOLKIT?

  • Why FAIR data matters for Life Science industry
  • Use cases to exemplify the benefits of FAIR implementation by Life Science industry
  • How-to methods for FAIR tools, training and change management
  • Tips for Life Science industry and links to relevant resources

WHO IS THE FAIR TOOLKIT FOR?

  • Data Stewards
  • Laboratory Scientists
  • Business Analysts
  • Science Managers

USE CASES

The Role of Curated Data in Accelerating the Identification of Putative Drug Targets for Cancer Immunotherapies – Elucidata

Elucidata tackles challenges in finding and reusing data through its curation app and custom curation of relevant data.

  • Reduced turnaround time; unlocked previously inaccessible datasets

  • Transformed target identification timeline in cancer immunotherapy

 

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FAIR data by design – Roche

Enabling transformationless data integration and automated FAIR Assessment

  • Provision of a FAIR data catalog for data discovery and data access.
  • Implementation of a FAIR end-2-end data management value chain for data sets offering transformation-less data integration. 
  • Application of FAIR principles not only to data but also application and API development.
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Streamlining Real-World Data Access: FAIR Data Practices at Bayer

Discover how Bayer empowers scientists by providing seamless access to Real-World Data (RWD) that supports their research inquiries using FAIR data products:

· Datasets are registered and discoverable in a FAIR data catalog

· We use a community standard to represent Terms of Use.

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METHODS

Change Agents

Learn how change agents, such as data stewards, play an important  role to support FAIR data management and application.

  • A network of change agents coordinate data management across the organisation to support the necessary changes.
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FAIRification Workflow

Find out how a generic workflow can be deployed by workshops or action team to make important datasets FAIR.

  • FAIRification as a retroactive workflow is common at this time
  • FAIRification by design (data “born” FAIR) is far more desirable for the future
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Data Capability Maturity Model

Capability Maturity Model applied to data helps an organisation to determine the capability for making data assets FAIR.

  • The method defines five levels of maturity for how an organisation makes and maintains FAIR data.
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CREATED BY LEADING LIFE SCIENCE ORGANISATIONS