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
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
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.
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 >
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.
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
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
