Property cardinality analysis to extract truly tabular query results from Wikidata
Wolfgang Fahl, Tim Holzheim, Andrea Westerinen, Christoph Lange, Stefan Decker · Zenodo (CERN European Organization for Nuclear Research) · 2022
Tabular views of data with tables, columns and rows as the key concepts are still a popular basis for data analysis and storage, used in relational database management systems and spreadsheet software. Graph based approaches are a superset of the tabular view and use vertices and edges/properties as the key concepts to manage the data. A common way to store graph data is using subject, predicate and object triples in a “triple store”. For quite a few use cases, transforming the triple store data to a tabular view is needed since tabular systems are still widespread. The straightforward approach to generating such data using a “naive” query will, however, create unexpected results or even fail because of conceptual differences between the relational and the graph approaches regarding the handling of the cardinality/multiplicity of properties. This work shows a systematic approach to analyze the property cardinalities of the graph data in an RDF/SPARQL triple store and to extract “truly tabular” data (with cardinalities of 1 in each column) by automatically generating appropriate queries. We propose a SPARQL query builder that simplifies the generation of queries that limit the result set to such “truly tabular” data.