Abstract
The Resource Description Framework is well-established as a lingua franca for data modeling and is designed to integrate heterogeneous data at instance and schema level using statements. While RDF is conceptually simple, data models nevertheless get complex, when complex data needs to be represented. Additional levels of indirection with intermediate resources instead of simple properties lead to higher barriers for prospective users of the data. Based on three patterns, we argue that shifting information to a meta-level can not only be used to (1) provide provenance information, but can also help to (2) maintain backwards compatibility for existing models, and to (3) reduce the complexity of a data model. There are, however, multiple ways in RDF to use a meta-level, i.e., to provide additional statements about statements. With Named Graphs, there exists a well-established mechanism to describe groups of statements. Since its inception, however, it has been hard to make statements about single statements. With the introduction of RDF-star, a new way to provide data about single statements is now available. We show that the combination of RDF-star and Named Graphs is a viable solution to express data on a meta-level and propose that this meta-level should be used as first class citizen in data modeling.
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Notes
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While it depends on the perspective, we consider data complex that uses several layers of properties and dependent classes to describe a resource.
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Throughout this paper, we use TriG-star syntax in the examples. For reference this is a list of the implied namespaces, ex is the default or empty namespace: rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#; owl: http://www.w3.org/2002/07/owl#; ex: http://example.org/; dcat: http://www.w3.org/ns/dcat#; dct: http://purl.org/dc/terms/; foaf: http://xmlns.com/foaf/0.1/; prov: http://www.w3.org/ns/prov#; dbp: http://dbpedia.org/property/; dbo: http://dbpedia.org/ontology/; gn: http://www.geonames.org/ontology#; gndo: http://d-nb.info/standards/elementset/gnd#.
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To get evidence of reification usage in real world application we checked a given list of SPARQL endpoints. In favor we use the Wikidata SPARQL endpoint list at https://www.wikidata.org/wiki/Wikidata:Lists/SPARQL_endpoints. This examination was done automatically with a suitable SPARQL query. The list, however, contains 139 entries and can be, according to its small size, considered as a sample only. Merely 78 endpoints were reachable via GET or POST requests (on July 20th 2022). 7 out of 78 remaining endpoints were not suitable for this study, being no actual SPARQL endpoint or the domain has been sold. Out of 72 endpoints 5 are using reification. At just 7,7% that’s a small percentage. This supports the thesis that reification is rarely used.
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https://graphdb.ontotext.com/documentation/free/devhub/rdf-sparql-star.html, Singleton Properties.
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According to the DBpedia ontology, this should actually be modeled with an n-ary entity, but at least in the current version of DBpedia, the described problem exists.
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Acknowledgements
This research was partially supported by the Volkswagen Foundation (Project: Consequences of Artificial Intelligence on Urban Societies, Grant 98555) and the German Research Foundation (Project: Specialized Subject Service for Jewish Studies, Grant 286004564). We thank Magnus Pfeffer for his valuable feedback.
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Rupp, F., Schnabel, B., Eckert, K. (2022). Easy and Complex: New Perspectives for Metadata Modeling Using RDF-Star and Named Graphs. In: Villazón-Terrazas, B., Ortiz-Rodriguez, F., Tiwari, S., Sicilia, MA., Martín-Moncunill, D. (eds) Knowledge Graphs and Semantic Web . KGSWC 2022. Communications in Computer and Information Science, vol 1686. Springer, Cham. https://doi.org/10.1007/978-3-031-21422-6_18
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