Why is this important?
Implementation of the FAIR guiding principles is important for the Life Science industry, as described in our published review in Drug Discovery Today. FAIR Implementation releases far greater value from data and associated metadata over a much longer period of time, making secondary reuse much more likely.
As the life science industry continues to transform digitally, this project will help foster greater collaboration and more effective industry partnerships.
What will the project achieve?
- Growth and sustainability of the FAIR Toolkit through relevant collaborations, especially for at least two additional use cases by the end of 2021
- The FAIR4Clin Guide is being developed, first as a closed and prototype wiki by mid-2021 and then, published to a public wiki by the end of 2021
- Collaborative opportunities to improve existing clinical vocabularies/ontologies are being sought during 2021
- High visibility and impact through publications and workshop or conference events are important ongoing activities for the FAIR project
How will the project do this?
A major deliverable from this project is the release of a freely accessible toolkit to help life science companies to implement the FAIR (Findable, Accessible, Interoperable, Reusable) guiding principles for data management and stewardship (DOI:10.1038/sdata.2016.18).
The project team collected candidate content in a simple wiki and selected the most relevant content to support the implementation of FAIR by scientists in the life science industry. This enabled the specification, design, and development of a FAIR Toolkit website serving as a “one-stop-shop” to start the journey to support the FAIR data management life cycle.
The Pistoia FAIR Toolkit can be accessed at fairtoolkit.pistoiaalliance.org which was developed with reference to the related Pistoia Alliance User Experience for Life Science (UXLS) Toolkit: uxls.org.
Next, we are turning our attention to the application of the toolkit methods to clinical trial FAIR data management. This will be driven by a use case that involves two co-morbid disease indications, type 2 diabetes, and breast cancer.