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
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
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
Find out how to apply the FAIR Maturity Indicators to measure the FINDABILITY of the data and metadata.
- Findability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
A Data Management Plan documents the specific attributes expected for your FAIR objectives.
- Prepare the Data Management Plan as early as possible
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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