Automated interpretability of linked data ontologies: : an evaluation within the cultural heritage domain

Publication and usage of linked data has been highly pursued by cultural heritage institutions and service providers in this domain. Much research and cooperation are taking place in adapting and improving cultural heritage data models for linked data and in defining ontologies and vocabularies, as well as the setting up of services based on linked data. This article presents an evaluation of ontologies and vocabularies published as liked data, which originate from the cultural heritage domain, or are frequently used and linked to in this domain. Our study aims to evaluate their usability by crawlers operating on the web of data, according to specifications and practices of linked data, the Semantic Web and ontology reasoning. We evaluate having in mind the use case of general data consumption applications based on RDF, RDF Schema, OWL, SKOS and linked data’s guidelines. We have evaluated twelve ontologies and vocabularies and identified that four were not fully compliant, and that alignments between ontologies are not included in the definitions of the ontologies. This study contributes to the research of novel services consuming linked data. It also allows to better assess the automation that can be achieved to handle the variety and large volume of linked data, when assessing the viability of new services based on linked data in cultural heritage.

[1]  Stefan Schlobach,et al.  LOD Lab: Scalable Linked Data Processing , 2016, Reasoning Web.

[2]  Ruben Verborgh,et al.  Discovering Data Sources in a Distributed Network of Heritage Information , 2019, SEMANTiCS.

[3]  Eero Hyvönen,et al.  Publishing and Using Cultural Heritage Linked Data on the Semantic Web , 2012, Synthesis Lectures on the Semantic Web.

[4]  Stefanos D. Kollias,et al.  Enriching and Publishing Cultural Heritage as Linked Open Data , 2017, Mixed Reality and Gamification for Cultural Heritage.

[5]  Laurens Rietveld Publishing and Consuming Linked Data - Optimizing for the Unknown , 2016, Studies on the Semantic Web.

[6]  Ruben Verborgh,et al.  Linked Data-as-a-Service: The Semantic Web Redeployed , 2015, ESWC.

[7]  Robert J. Vander Hart Linked Data for Cultural Heritage , 2017 .

[8]  Claus Zinn,et al.  A Web-Based Repository Service for Vocabularies and Alignments in the Cultural Heritage Domain , 2010, ESWC.

[9]  Antoine Isaac,et al.  Web Technologies: A Survey of Their Applicability to Metadata Aggregation in Cultural Heritage , 2017, ELPUB.

[10]  Antoine Isaac,et al.  Metadata Aggregation: Assessing the Application of IIIF and Sitemaps Within Cultural Heritage , 2017, TPDL.

[11]  Antoine Isaac,et al.  Aggregation of Linked Data : A case study in the cultural heritage domain , 2018, 2018 IEEE International Conference on Big Data (Big Data).

[12]  Antoine Isaac,et al.  Evaluation of Schema.org for Aggregation of Cultural Heritage Metadata , 2018, ESWC.

[13]  Nandana Mihindukulasooriya,et al.  A comprehensive quality model for Linked Data , 2018, Semantic Web.

[14]  Aidan Hogan Reasoning Techniques for the Web of Data , 2014, Studies on the Semantic Web.