MaSQue: An Approach for Flexible Metadata Storage and Querying in RDF
J. Frey, and S. Hellmann. 13th International Conference on Semantic Systems Proceedings (SEMANTiCS 2017) - Posters & Demonstrations Track, (September 2017)
The maintenance and use of metadata, such as provenance and time-related information (when was a data entity created or retrieved), is of increasing importance in the Semantic Web, especially for Big Data applications, that work on heterogeneous data from multiple sources and which require high data quality. In an RDF dataset it is possible to store metadata alongside the actual RDF data and several possible Metadata Representation Models (e.g. Singleton Property and n-ary relation) have been proposed. However, studies investigating the performance of these models show that choosing the appropriate metadata representation depends on the used data and metadata, queries and RDF store. To allow a flexible storage and querying of data and its metadata independent of the applied Metadata Representation Model, we propose MaSQue (Metadata Storage and Querying). The approach introduces an intermediate (meta)data serialization format and query annotations as metadata layer on top of RDF and SPARQL.