Linked open data publishing linked open data from a disease ontology toward a knowledge infrastructure

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Abstract

Publishing open data as linked data is a significant trend in not only the Semantic Web community but also other domains such as life science, government, media, geographic research and publication. One feature of linked data is the instance-centric approach, which assumes that considerable linked instances can result in valuable knowledge. In the context of linked data, ontologies offer a common vocabulary and schema for RDF graphs. However, from an ontological engineering viewpoint, some ontologies offer systematized knowledge, developed under close cooperation between domain experts and ontology engineers. Such ontologies could be a valuable knowledge base for advanced information systems. Although ontologies in RDF formats using OWL or RDF(S) can be published as linked data, it is not always convenient to use other applications because of the complicated graph structures. Consequently, this paper discusses RDF data models for publishing ontologies as linked data. As a case study, we focus on a disease ontology in which diseases are defined as causal chains.

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APA

Kozaki, K., Yamagata, Y., Kou, H., Imai, T., Ohe, K., & Mizoguchi, R. (2014). Linked open data publishing linked open data from a disease ontology toward a knowledge infrastructure. Transactions of the Japanese Society for Artificial Intelligence, 29(4), 396–405. https://doi.org/10.1527/tjsai.29.396

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