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
Find out more >

Learn 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
Find out more >

How to unlock the value of RNA sequencing (RNA-Seq) and microarray data from a public repository Gene Expression Omnibus (GEO)

  • Using machine-learning assisted curation, guided by the FAIR principles
  • Leverage ontologies and controlled vocabularies for annotation
Find out more >

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.
Find out more >

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
Find out more >

Discover how these interactive events, guided by experts in data management, can provide a learning experience to improve the FAIRness of data brought by the participants.

  • Practical “hands-on” training to evaluate and make data more FAIR
Find out more >

CREATED BY LEADING LIFE SCIENCE ORGANISATIONS