Copyright Clearance Center (CCC) has announced its collaboration with key industry stakeholders to launch the Leiden Institute for FAIR and Equitable Science (LIFES). In recognition of the challenges that exist with data reuse within the global research community, LIFES is a joint effort by an international public-private partnership of eleven academic and private organisations to build a wide and diverse network of public and private members that want to incorporate FAIR data principles (Findable, Accessible, Interoperable, Reusable) and equitable data reuse within their organisations.
Along with CCC, the founding partners of LIFES include the GO FAIR Foundation, FAIRscholar, HINQ, Leiden University Medical Center (LUMC), Leiden Academic Centre for Drug Research (LACDR), Naturalis Biodiversity Center, Roche Nederland B.V., Sage, TNO, and the University of Twente (UT).
With the creation of this ecosystem, LIFES will facilitate access to FAIR-compliant applications and services that support efficient data sharing, improve research reproducibility, and enhance collaboration across different domains and disciplines. LIFES will foster collaborations to bridge the deficiencies in current technical capabilities and research methodologies that present unnecessary barriers to equitable data visiting. It will also take the lead in securing public and private funding for developing strategic capabilities.
By laying the foundation for a FAIR and equitable data ecosystem that can be replicated throughout the world, LIFES is responding to the immediate needs of the global research community and meeting the growing demand for solutions that address the evolving challenges of a world that increasingly relies on data-driven decision-making.
“Data accessibility is becoming increasingly central to research, and a quantifiable sense of data reproducibility is crucial for research-intensive organizations, especially in this era of generative AI,” said Babis Marmanis, Executive Vice President and CTO, CCC. “The mission of LIFES is to advance scientific research and innovation, which is important to CCC, our partners, and customers. Datasets that follow the FAIR data principles can spur innovation, promote inclusivity, and support sustainability.”
As more organisations adopt machine learning and AI, FAIR data becomes vital to enabling the use of data for machines. These principles emphasise machine-actionability, enabling AI systems to access an increasing volume and complexity of data automatically, at scale. The interoperability aspect of FAIR data also ensures appropriate semantic mapping of metadata to enhance the discovery, retrieval, usability, and analysis of data for legitimate research questions that meet legal, ethical, and consent requirements.