Ralph Schäfermeier

Jamal Al Qundus, Ralph Schäfermeier, Naouel Karam et al.

The ROC ontology for country responses to COVID-19 provides a model for collecting, linking and sharing data on the COVID-19 pandemic. It follows semantic standardization (W3C standards RDF, OWL, SPARQL) for the representation of concepts and creation of vocabularies. ROC focuses on country measures and enables the integration of data from heterogeneous data sources. The proposed ontology is intended to facilitate statistical analysis to study and evaluate the effectiveness and side effects of government responses to COVID-19 in different countries. The ontology contains data collected by OxCGRT from publicly available information. This data has been compiled from information provided by ECDC for most countries, as well as from various repositories used to collect data on COVID-19.

Haytham Al-Feel, Ralph Schafermeier, Adrian Paschke

Ontologies are considered as the backbone of the Semantic Web. With the rising success of the Semantic Web, the number of participating communities from different countries is constantly increasing. The growing number of ontologies available in different natural languages leads to an interoperability problem. In this paper, we discuss several approaches for ontology matching; examine similarities and differences, identify weaknesses, and compare the existing automated approaches with the manual approaches for integrating multilingual ontologies. In addition to that, we propose a new architecture for a multilingual ontology matching service. As a case study we used an example of two multilingual enterprise ontologies - the university ontology of Freie Universitaet Berlin and the ontology for Fayoum University in Egypt.