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
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
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
Learn how SciBite unlock the value of bioassay data through semantic enrichment of metadata to create FAIR annotation.
- Unified annotation from ontologies across an area of business
- Standardized metadata for any application
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.
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
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
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
