Abstract: There is an emerging demand on efficiently archiving and (temporal) querying different versions of evolving semantic Web data. As novel archiving systems are starting to address this challenge, foundations/standards for benchmarking RDF archives are needed to evaluate its storage space efficiency and the performance of different retrieval operations. To this end, we provide theoretical foundations on the design of data and queries to evaluate emerging RDF archiving systems. Then, we instantiate these foundations along a concrete set of queries on the basis of a real-world evolving datasets. Finally, we perform an extensive empirical evaluation of current archiving techniques and querying strategies, which is meant to serve as a baseline of future developments on querying archives of evolving RDF data.
Keywords: RDF archiving, Semantic Data Versioning, Evolving Web data, SPARQL Benchmark
Journal: Semantic Web, vol. Pre-press, no. Pre-press, pp. 1-45, 2018