Increasing FAIRness and value of data through semantic models and knowledge graphs
The problem
Data has always been a key element of scientific research. Today, it is also a key asset for companies and organizations. The time that data was just an obscure topic for the IT department is long gone. It is now a boardroom topic, with many organizations having appointed a Chief Digital Officer.
So you would expect that for life science organizations − which are both heavily oriented on science and have a strong focus on digital − ensuring that their data are well organized, integrated and governed is a top priority. And it is!
But making sure that biomedical data are Findable, Accessible, Interoperable and Reusable (FAIR) is easier said than done. It requires expert knowledge of the scientific domain, business processes, rules and regulations, data standards and computational frameworks − all of which are prone to change.
How The Hyve can help
The complexity of the biomedical data landscape was a reason for The Hyve to create a Biomedical Data Services team. Our company has been engaged in the FAIR movement since its inception in 2014, and we have worked with all top 10 pharma companies, dozens of academic hospitals, patient organizations, and government and science agencies to advocate and implement a FAIR data strategy.
Our experience and expert knowledge of data standards cover all aspects of biomedical research data − from knowledge graphs in drug discovery to clinical trial data standards, and from antibody manufacturing data to real world healthcare data. Whether you are leading a multi-year global digital transformation project or a biomedical startup looking for ways to improve data management, The Hyve’s consultants can help you identify areas for improvement and which steps to take to reach your FAIR data targets.
Research Data Management
