Over recent years, there has been exciting growth in collaboration between academia and industry in the life sciences to make data more Findable, Accessible, Interoperable and Reusable (FAIR) to achieve greater value. Despite considerable progress, the transformative shift from an application-centric to a data-centric perspective, enabled by FAIR implementation, remains very much a work in progress on the 'FAIR journey'. In this review, we consider use cases for FAIR implementation. These can be deployed alongside…

Nowadays, the FAIR Principles guide data policy actions and professional practices in the public and private sectors. However, despite such global endorsements, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an online resource of hands-on recipes for “FAIR doers” in the Life Sciences. Launched in 2020, and created by researchers and data managers professionals in ac…

Nowadays, the FAIR Principles guide data policy actions and professional practices in the public and private sectors. However, despite such global endorsements, the FAIR Principles are aspirational, remaining elusive at best, and intimidating at worst. To address the lack of practical guidance, and help with capability gaps, we developed the FAIR Cookbook, an online resource of hands-on recipes for “FAIR doers” in the Life Sciences. Launched in 2020, and created by researchers and data managers professionals in ac…

An extremely powerful and efficient use for Knowledge Graphs is to unite well-understood domains of knowledge alongside novel and specific business/scientific questions. Using small ontologies that embed large reference taxonomies, we are able to go from tactical scientific questions (bottom-up) to common taxonomies and reference datasets (middle-out) approach to model scientific questions, aligning with enterprise master data strategies on the way up. If building blocks follow FAIR (Findable, Accessible, Interope…

Biopharmaceutical industry R&D, and indeed other life sciences R&D such as biomedical, environmental, agricultural and food production, is becoming increasingly data-driven and can significantly improve its efficiency and effectiveness by implementing the FAIR (findable, accessible, interoperable, reusable) guiding principles for scientific data management and stewardship. By so doing, the plethora of new and powerful analytical tools such as artificial intelligence and machine learning will be able, automatically…