Presenting and Preserving the Change in Taxonomic Knowledge for Linked Data (Extended Abstract)

dc.contributor.authorRathachai Chawuthai
dc.contributor.authorHideaki Takeda
dc.contributor.authorVilas Wuwongse
dc.contributor.authorUtsugi Jinbo
dc.date.accessioned2025-07-21T05:59:25Z
dc.date.issued2018-01-01
dc.description.abstractLinked Open Data (LOD) technology enables web of data and exchangeable knowledge graphs through the Internet. However, the change in knowledge is happened everywhere and every time, and it becomes a challenging issue of linking data precisely because the misinterpretation and misunderstanding of some terms and concepts may be dissimilar under different context of time and different community knowledge. To solve this issue, we introduce an approach to the preservation of knowledge graph, and we select the biodiversity domain to be our case studies because knowledge of this domain is commonly changed and all changes are clearly documented. Our work produces an ontology, transformation rules, and an application to demonstrate that it is feasible to present and preserve knowledge graphs and provides open and accurate access to linked data. It covers changes in names and their relationships from different time and communities as can be seen in the cases of taxonomic knowledge.
dc.identifier.doi10.1145/3184558.3186234
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/7158
dc.subjectKnowledge graph
dc.subjectLinked Data
dc.subject.classificationSemantic Web and Ontologies
dc.titlePresenting and Preserving the Change in Taxonomic Knowledge for Linked Data (Extended Abstract)
dc.typeArticle

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