The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVI-4/W5-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 299–305, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-299-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4/W5-2021, 299–305, 2021
https://doi.org/10.5194/isprs-archives-XLVI-4-W5-2021-299-2021

  23 Dec 2021

23 Dec 2021

CODCA – COVID-19 ONTOLOGY FOR DATA COLLECTION AND ANALYSIS IN E-HEALTH

A. Ismail and M. Sah A. Ismail and M. Sah
  • Computer Engineering Department, Near East University, North Cyprus, via Mersin 10, Turkey

Keywords: Covid-19, Ontology, SPARQL, SWRL, Semantic Web, E-Health

Abstract. Coronavirus (Covid-19) pandemic is one of the most deadly diseases that cause the death of millions around the world. Automatic collection and analysis of Covid-19 patient data will help medical practitioners in containing the virus. For this purpose, Semantic Web technologies can be utilized, which allows machine-processable data and enables data sharing, and reuse across machines. In this paper, we propose a Covid-19 ontology (named CODCA) that helps in collecting, analysing, and sharing medical information about people in the e-health domain. In particular, the proposed ontology uses information about medical history, drug history, vaccination history, and symptoms in order to analyse Covid-19 risk factors of people and their treatment plans. In this way, information about Covid-19 patients can be automatically processed and can be re-usable by other applications. We also demonstrate extensive semantic queries (i.e. SPARQL queries) to search the created metadata. Furthermore, we illustrate the usage of semantic rules (i.e. SWRL) so that treatment plans for individual patients can be inferred from the available knowledge.