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
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.
How to unlock the value of RNA sequencing (RNA-Seq) and microarray data from a public repository Gene Expression Omnibus (GEO)
- Using machine-learning assisted curation, guided by the FAIR principles
- Leverage ontologies and controlled vocabularies for annotation
Hear more about Roche’s ‘learning-by-doing’ FAIRification efforts
- Lessons learned from FAIRification of clinical data for Ophthalmology, Autism, Asthma and COPD
- Set up integrated end-to-end process for curation workflows for prospective studies
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.
Capability Maturity Model applied to data helps an organisation to determine the capability for making data assets FAIR.
- The method defines five levels of maturity for how an organisation makes and maintains FAIR data.
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
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS
