Building a Biomedical Onthology on COVID-19

Abstract

The purpose of this thesis research work is to cater the requirements, techniques, and findings of implementing an ontology for the domain of COVID-19. This task is achieved by using a data source named UMLS in order to ease the access of biomedical data for the end users and clinical researchers. The literature available in the form of research articles is unorganized and unstructured therefore it is difficult for the seeker to find the right data. COVID-19 being a deadly viral disease has affected almost the entire population of the world in one way or another. The data related to COVID-19 pandemic is so vast and much research are being conducted on a daily basis in order to find the causes and cure of this viral infection. Keeping in mind this information, the accessibility of the data while keeping its semantic meanings intact is a tricky job. Therefore, a knowledge base must be designed in order to depict information and data related to the desired domain in such a manner that its semantic meaning is intact and the data is available in machine readable format. Hence, the major purpose of this research is to create an ontology on the primary concepts and their relationships as well as the knowledge related to the domain of COVID-19 or Corona Virus. This research is conducted by conducting a thorough literature survey on the existing ontologies and their implementation methodologies. The interfaces for the facility of end users and researchers are also reviewed. The ontology for the domain of COVID-19 is developed using UMLS as a data source. Furthermore, the data extraction techniques along with the ontology development are also catered. The major concepts, attributes and relationships among them are mapped on a live portal (https://ontologycovid.000webhostapp.com/) consisting of other domain related knowledge for the facilitation of end users and clinical researchers.