FAIRClinical aims to improve the reuse of published clinical case report forms (CRFs) and enhance the FAIR-ness (Findability, Accessibility, Interoperability, Reuse) of supplementary data files in the biomedical literature.

Case report forms (CRFs) collect patient data in clinical research studies and trials, and represent an information-rich subset of clinical research literature. However, it is difficult to compare across many different CRFs which all use their own structures. We will use text mining approaches to find important clinical concepts in published CRFs. These concepts will be used to create a unique open-access dataset that can be used to support biomedical research.

Supplementary files linked to biomedical publications are rich sources of data, but they are almost impossible to search and find. We will overcome this gap in biomedical data accessibility by using text mining approaches to provide descriptive metadata for supplementary files. The metadata will be searchable using SIBiLS, the SIB Literature Services.