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 Pistoia Alliance Bioassay FAIR Annotation project develops digital standards for bioassay metadata, provides annotations of bioassay method descriptions according to these standards, and makes them available publicly.
- Proposed a minimal information model for assay metadata. It is now used by the FDA IVP project.
- Annotated close to 2,800 previously published assay methods.
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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 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
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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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
Find out how a generic workflow can be deployed by workshops or action team to make important datasets FAIR.
- FAIRification as a retroactive workflow is common at this time
- FAIRification by design (data “born” FAIR) is far more desirable for the future
CREATED BY LEADING LIFE SCIENCE ORGANISATIONS













