Covid-19 Case Study

Project Description

The main purpose of this study is to transform data into knowledge. In the context of the current pandemic, an immense amount of data, for instance on global pandemic cases, patient information including the travel, treatment, available and required infrastructural resources, treatment facilities, etc. are available on the Web in various formats (e.g., spreadsheet, HTML). The data is the fuel that is necessary to perform any kind of research, and for any decision and policymaking purposes. Our initial analysis reveals that the available datasets are inconsistent and lack meaningful representation, which hinders their effective use by both humans and machines. The data becomes hard to interchange, integrate, reuse, process and interpret automatically by machines, which eventually prevents the derivation of insights from the data and doing analytics. We aim to investigate in depth the existing issues related to data description, interoperability, data representation, and so forth with the ultimate goal of transforming data into useful knowledge.

Funding Information: This project is funded by Indian Statistical Institute (ISI) (36 months)

Communications

Publications

Dutta, B. and DeBellis, M. (2020). CODO:an ontology for collection and analysis of COVID-19 data. In Proc. of 12th Int. Conf. on Knowledge Engineering and Ontology Development (KEOD), Lisbon, Portugal, 2-4 November 2020, vol.2, pp. 76-85 (DOI: https://doi.org/10.5220/0010112500760085)

DeBellis, M. and Dutta, B. (2021). Developing the Covid-19 CODO Knowledge Graph: An Agile Approach From Ontology to Knowledge Graph. In: Villazón-Terrazas B., Ortiz-Rodríguez F., Tiwari S., Goyal A., Jabbar M. (eds) Knowledge Graphs and Semantic Web. KGSWC 2021. Communications in Computer and Information Science (CCIS), Springer, Cham, vol. 1459, pp. 153-168. (DOI: https://doi.org/10.1007/978-3-030-91305-2_12)

Asiyah Lin, Yuki Yamagata, William D. Duncan, Leigh Carmody, Tatsuya Kushida, Hiroshi Masuya, John Beverley, Biswanath Dutta, Michael DeBellis, Zoë May Pendlington, Paola Roncaglia and Yongqun He. A community effort for COVID-19 Ontology Harmonization. In Proc. of Int. Conf. on Biomedical Ontologies 2021 (ICBO-2021), co-located with the Workshop on Ontologies for the Behavioural and Social Sciences (OntoBess 2021). Bolzano (Italy), September 16-18, 2021, pp. 122-127 (available from http://ceur-ws.org/Vol-3073/paper17.pdf)