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The Knowledge Organization of DBpedia: A Case Study
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(2013)

Purpose - This paper investigates the semantic structure underlying DBpedia, one of the largest and most heavily used datasets in the current Linked Open Data (LOD) landscape. Our analysis attempts to shed light on this new type of knowledge organization tool. Design/methodology/approach - The research followed a case study methodology to analyze DBpedia using the domain of jazz as the application scenario. Findings - The study reveals an evolving knowledge organization tool where different descriptive and classification approaches are employed concurrently. The semantic constructs employed in the DBpedia knowledge base vary significantly in terms of their degree of formalization, stability, cohesiveness and consistency. As such, they challenge our tolerance threshold for data quality and our traditional notion of authority control. Research limitations/implications - The analysis is conducted on a limited portion of a large knowledge base. Initial findings provide a basis for further research and study. Practical implications - Revealing the knowledge organization underlying DBpedia increases our understanding of its power, its limitations and its implications for the new semantic context provided by LOD. Having an understanding of the range of entities and properties available enables LOD users to formulate queries with higher precision.
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