Biomedical databases often have restricted access policies and governance rules. Thus, an adequate description of their content is essential for researchers who wish to use them for medical research. A strategy for publishing information without disclosing patient-level data is through database fingerprinting and aggregate characterisations. However, this information is still presented in a format that makes it challenging to search, analyse, and decide on the best databases for a domain of study. Several strategies allow one to visualise and compare the characteristics of multiple biomedical databases. Our study focused on a European platform for sharing and disseminating biomedical data. We use semantic data visualisation techniques to assist in comparing descriptive metadata from several databases. The great advantage lies in streamlining the database selection process, ensuring that sensitive details are not shared. To address this goal, we have considered two levels of data visualisation, one characterising a single database and the other involving multiple databases in network-level visualisations. This study revealed the impact of the proposed visualisations and some open challenges in representing semantically annotated biomedical datasets. Identifying future directions in this scope was one of the outcomes of this work.
Keywords: biomedical data; data visualisation; evidence-based medicine; semantic data; temporal data; visualisation techniques.