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
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
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
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.
Find out more >
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.
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
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
