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
Discover how Bayer builds a harmonised FAIR data asset based on Health Care Professional partners.
- A knowledge graph from federated data integration
- Enables reuse by different consumers
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
Discover how Bayer empowers scientists by providing seamless access to Real-World Data (RWD) that supports their research inquiries using FAIR data products:
· Datasets are registered and discoverable in a FAIR data catalog
· We use a community standard to represent Terms of Use.
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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
Find out how the data stakeholders can prepare for the changes necessary to make data FAIR.
- Readiness for change provides the means to engage a wider group of staff throughout an organisation.
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.
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
