Only with tools that support and assist researchers we will achieve a widespread adoption of FAIR data practices.
What are the FAIR Data Principles?
- The FAIR Data Principles are a set of guidelines for curating and sharing research data such that they are optimaly reusable by both humans and machines.
Why are FAIR data practices important?
- FAIR data practices are crucial for ensuring reproducibility of scientific findings, promoting reuse of data, and enabling AI/ML-driven analysis to ultimately increase the pace of new discoveries. They also ensure proper credits to data generators.
What are the challenges?
- Despite effort from funding agencies, industry, and researchers, FAIR data practices are not widely adopted due to their complex nature, insufficient support for researchers, and lack of awareness.
What do we do?
- We develop open source tools that enhance and streamline FAIR data practices for biomedical researchers through automation and intuitive user interfaces.
These are the projects we are working on at the moment:
Where do our tools make a difference?