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
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 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
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.
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
Discover how to apply the FAIR Maturity Indicators to measure the REUSABILITY of the data and metadata.
- Reusability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
Read how to apply the FAIR Maturity Indicators to measure the INTEROPERABILITY of the data and metadata.
- Interoperability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
