Facilitating Study and Item Level Browsing for Clinical and Epidemiological COVID-19 Studies
| Autor: | Christian R. Bauer, Dagmar Waltemath, Atinkut Alamirrew Zeleke, Vivien Junker, Iris Pigeot, Bastian Seifert, Aliaksandra Shutsko, Ulrich Sax, Rajini Nagrani, Matthias Löbe, Johannes Darms, Martin Golebiewski, Theresa Bender, Carsten Oliver Schmidt, Juliane Fluck, Xiaoming Hu, Birte Lindstädt, Michael Lieser, Sophie Anne Ines Klopfenstein, Sofiya Koleva |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Coronavirus disease 2019 (COVID-19) Computer science Relational database Public health Metadata modeling 030210 environmental & occupational health 3. Good health Metadata Clinical trial World Wide Web 03 medical and health sciences 0302 clinical medicine Epidemiology medicine 030212 general & internal medicine User needs |
| Zdroj: | MIE |
| DOI: | 10.3233/shti210284 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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