Facilitating Study and Item Level Browsing for Clinical and Epidemiological COVID-19 Studies

Stud Health Technol Inform. 2021 May 27;281:794-798. doi: 10.3233/SHTI210284.


COVID-19 poses a major challenge to individuals and societies around the world. Yet, it is difficult to obtain a good overview of studies across different medical fields of research such as clinical trials, epidemiology, and public health. Here, we describe a consensus metadata model to facilitate structured searches of COVID-19 studies and resources along with its implementation in three linked complementary web-based platforms. A relational database serves as central study metadata hub that secures compatibilities with common trials registries (e.g. ICTRP and standards like HL7 FHIR, CDISC ODM, and DataCite). The Central Search Hub was developed as a single-page application, the other two components with additional frontends are based on the SEEK platform and MICA, respectively. These platforms have different features concerning cohort browsing, item browsing, and access to documents and other study resources to meet divergent user needs. By this we want to promote transparent and harmonized COVID-19 research.

Keywords: Browsing metadata; COVID-19; FAIR data; metadata standards.

MeSH terms

  • COVID-19*
  • Epidemiologic Studies
  • Humans
  • Metadata
  • Registries
  • SARS-CoV-2