Instance level analysis on linked open data connectivity for cultural heritage entity linking and data integration

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Abstract

In cultural heritage, many projects execute Named Entity Linking (NEL) through global Linked Open Data (LOD) references in order to identify and disambiguate entities in their local datasets. It allows users to obtain extra information and contextualise the data with it. Thus, the aggregation and integration of heterogeneous LOD are expected. However, such development is still limited partly due to data quality issues. In addition, analysis on the LOD quality has not sufficiently been conducted for cultural heritage. Moreover, most research on data quality concentrates on ontology and corpus level observations. This paper examines the quality of the eleven major LOD sources used for NEL in cultural heritage with an emphasis on instance-level connectivity and graph traversals. Standardised linking properties are inspected for 100 instances/entities in order to create traversal route maps. Other properties are also assessed for quantity and quality. The outcomes suggest that the LOD is not fully interconnected and centrally condensed; the quantity and quality are unbalanced. Therefore, they cast doubt on the possibility of automatically identifying, accessing, and integrating known and unknown datasets. This implies the need for LOD improvement, as well as the NEL strategies to maximise the data integration.

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APA

Sugimoto, G. (2022). Instance level analysis on linked open data connectivity for cultural heritage entity linking and data integration. Semantic Web, 14(1), 55–100. https://doi.org/10.3233/SW-223026

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