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

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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Learn out how SciBite unlock the value of bioassay data through semantic enrichment of metadata to create FAIR annotation.

  • Unified annotation from ontologies across an area of business
  • Standardized metadata for any application
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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 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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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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A Data Management Plan documents the specific attributes expected for your FAIR objectives.

  • Prepare the Data Management Plan as early as possible

 

Find out more >

CREATED BY LEADING LIFE SCIENCE ORGANISATIONS