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
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
Enabling transformationless data integration and automated FAIR Assessment
- Provision of a FAIR data catalog for data discovery and data access.
- Implementation of a FAIR end-2-end data management value chain for data sets offering transformation-less data integration.
- Application of FAIR principles not only to data but also application and API development.
Roche embeds data standards and quality checks to harmonize, automate and integrate very heterogeneous and complex processes.
- Self-contained micro services deliver performance and scalability
- Scalable and flexible for data models in clinical and non-clinical
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
Read how to apply the FAIR Maturity Indicators to measure the INTEROPERABILITY of the data and metadata.
- Interoperability of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
Learn how the responsibilities and competencies for data stewardship provides important expert advice and suport for FAIR data management.
- A growing need for data stewardship competences in life science industry
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
