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
Learn out 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
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
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
Learn how to apply the FAIR Maturity Indicators to measure the ACCESSIBILITY of the data and metadata.
- Accessibility of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
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