On Graph Features of Semantic Web Schemas
IEEE Transactions on Knowledge and Data Engineering
Column-store support for RDF data management: not all swans are white
Proceedings of the VLDB Endowment
An Experimental Comparison of RDF Data Management Approaches in a SPARQL Benchmark Scenario
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Simple and Efficient Minimal RDFS
Web Semantics: Science, Services and Agents on the World Wide Web
Scalable indexing of RDF graphs for efficient join processing
Proceedings of the 18th ACM conference on Information and knowledge management
Power-Law Distributions in Empirical Data
SIAM Review
Marvin: Distributed reasoning over large-scale Semantic Web data
Web Semantics: Science, Services and Agents on the World Wide Web
Dynamic Querying of Mass-Storage RDF Data with Rule-Based Entailment Regimes
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Scalable Distributed Reasoning Using MapReduce
ISWC '09 Proceedings of the 8th International Semantic Web Conference
The RDF-3X engine for scalable management of RDF data
The VLDB Journal — The International Journal on Very Large Data Bases
Web Semantics: Science, Services and Agents on the World Wide Web
Relational processing of RDF queries: a survey
ACM SIGMOD Record
Invited paper: Scalable reduction of large datasets to interesting subsets
Web Semantics: Science, Services and Agents on the World Wide Web
The design and implementation of minimal RDFS backward reasoning in 4store
ESWC'11 Proceedings of the 8th extended semantic web conference on The semanic web: research and applications - Volume Part II
Database research challenges and opportunities of big graph data
BNCOD'13 Proceedings of the 29th British National conference on Big Data
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The entailment of an RDF graph under the RDF Schema standard can easily become too costly to compute and maintain. It is often more desirable to compute on-demand whether a triple exists in the entailment. This is a non-trivial task likely to incur I/O costs, since RDF graphs are often too large to fit in internal memory. As disk I/O is expensive in terms of time, I/O costs should be minimized to achieve better performance. We investigate three physical indexing methods for RDF storage on disk, comparing them using the state of the art RDF Schema entailment algorithm of Muñoz et al. In particular, the I/O behavior during entailment checking over these graph representations is studied. Extensive empirical analysis shows that an enhanced version of the state of the art indexing method, which we propose here, yields in general the best I/O performance.