In this chapter, the authors discuss the challenges of performing reasoning on large scale RDF datasets from the Web. Using ter-Horst's pD* fragment of OWL as a base, the authors compose a rule-based framework for application to Web data: they argue their decisions using observations of undesirable examples taken directly from the Web. The authors further temper their OWL fragment through consideration of "authoritative sources'' which counter-acts an observed behaviour which they term "ontology hijackin'': new ontologies published on the Web re-defining the semantics of existing entities resident in other ontologies. They then present their system for performing rule-based forward-chaining reasoning which they call SAOR: Scalable Authoritative OWL Reasoner. Based upon observed characteristics of Web data and reasoning in general, they design their system to scale: the system is based upon a separation of terminological data from assertional data and comprises of a lightweight in-memory index, on-disk sorts and file-scans. The authors evaluate their methods on a dataset in the order of a hundred million statements collected from real-world Web sources and present scale-up experiments on a dataset in the order of a billion statements collected from the Web. In this republished version, the authors also present extended discussion reflecting upon recent developments in the area of scalable RDFS/OWL reasoning, some of which has drawn inspiration from the original publication (Hogan, et al., 2009).
Towards Expressive Stream Reasoning.Stuckenschmidt, H.; Ceri, S.; Valle, E. D.; Harmelen, F.; Aberer, K.; Gal, A.; Hauswirth, M.; Sattler, K. U.; and Sheth, A.2010.In Semantic Challenges in Sensor Networks. Towards Expressive Stream ReasoningBibtex
Linked Sensor Data.Patni, H.; Henson, C.; and Sheth, A.2010.In 2010 International Symposium on Collaborative Technologies and Systems, (CTS 2010), 362--370. Linked Sensor DataBibtex
Janus: from Workflows to Semantic Provenance and Linked Open Data.Missier, P.; Sahoo, S. S.; Zhao, J.; Sheth, A.; and Goble, C.2010.In Procs. IPAW 2010. Bibtex
Ontology Alignment for Linked Open Data.Jain, P.; Hitzler, P.; Sheth, A.; Verma, K.; and Yeh, P. Z.2010.In 9th International Semantic Web Conference (ISWC2010), November. Ontology Alignment for Linked Open DataBibtexAbstract:
The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the idea of bootstrapping information already present on the LOD cloud. We also present a comprehensive evaluation which shows that BLOOMS outperforms state-of-the-art ontology alignment systems on LOD datasets. At the same time, BLOOMS is also competitive compared with these other systems on the Ontology Evaluation Alignment Initiative Benchmark datasets.
Provenance Aware Linked Sensor Data.Patni, H.; Sahoo, S. S.; Henson, C.; and Sheth, A.2010.In 2nd Workshop on Trust and Privacy on the Social and Semantic Web Colocated with ESWC2010 Heraklion Greece, Volume 5. Provenance Aware Linked Sensor DataBibtex
A Survey of the Semantic Specification of Sensors.Compton, M.; Henson, C.; Neuhaus, H.; Lefort, L.; Sheth, A.; Taylor, K.; Ayyagari, A.; and Roure, D. D.2009.In Proceedings of the 2nd International Workshop on Semantic Sensor Networks (SSN09) at ISWC 2009, Volume 522, 17--32, November, CEUR Workshop Proceedings. A Survey of the Semantic Specification of SensorsBibtex