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
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
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
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
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
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 >