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 Pistoia Alliance Bioassay FAIR Annotation project develops digital standards for bioassay metadata, provides annotations of bioassay method descriptions according to these standards, and makes them available publicly.
- Proposed a minimal information model for assay metadata. It is now used by the FDA IVP project.
- Annotated close to 2,800 previously published assay methods.
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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
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
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
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
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
