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

The Hyve present an approach to making new collaborative scientific research data FAIR in a real time manner on the internet.

  • Rapid development of a semantic model expressed as subset of schema.org
  • Reusable static web site generator code
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Discover how Bayer builds a harmonised FAIR data asset based on Health Care Professional partners.

  • A knowledge graph from federated data integration
  • Enables reuse by different consumers
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Find out how AstraZeneca deploy a policy for identifiers to construct a FAIR infrastructure across the enterprise.

  • A Uniform Resource Identifiers (URI) policy for the enterprise
  • A pilot server for persistent URIs
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Find out how to apply the FAIR Maturity Indicators to measure the FINDABILITY of the data and metadata.

  • Findability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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A Data Management Plan documents the specific attributes expected for your FAIR objectives.

  • Prepare the Data Management Plan as early as possible

 

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Consider how the granularity and context of data and associated metadata to help to inform your FAIR objectives.

  • Understand the granularity and context of the data as early as possible
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CREATED BY LEADING LIFE SCIENCE ORGANISATIONS