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
The Hyve present an approach to making new collaborative scientific research data FAIR in a real time manner on the internet.
- Rapid development of a semantic model expressed as subset of schema.org
- Reusable static web site generator code
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
Hear more about Roche’s ‘learning-by-doing’ FAIRification efforts
- Lessons learned from FAIRification of clinical data for Ophthalmology, Autism, Asthma and COPD
- Set up integrated end-to-end process for curation workflows for prospective studies
Learn how change agents, such as data stewards, play an important role to support FAIR data management and application.
- A network of change agents coordinate data management across the organisation to support the necessary changes.
Learn how to apply the FAIR Maturity Indicators to measure the ACCESSIBILITY of the data and metadata.
- Accessibility of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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.
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
