Implementing an Inference Engine for RDFS/OWL Constructs and User-Defined Rules in Oracle

Wu, Zhe; Eadon, George; Das, Shantanu; Chong, Eugene Inseok; Kolovski, Vladimir; Annamalai, Melliyal; Srinivasan, Jagannathan

doi:10.1109/icde.2008.4497533

Cited by 90 publications

(63 citation statements)

References 8 publications

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“…Several rule expressible non-standard OWL fragments; namely OWL-DLP [11], OWL − [7] (which is a slight extension of OWL-DLP), OWLPrime [25] and pD* [24]; have been defined in the literature and enable incomplete but sound RDFS and OWL Full inferences.…”

Section: Related Workmentioning

confidence: 99%

On the Ostensibly Silent ‘W’ in OWL 2 RL

Hogan

Decker

2009

Web Reasoning and Rule Systems

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Abstract. In this paper, we discuss the draft OWL 2 RL profile from the perspective of applying the constituent rules over Web data. In particular, borrowing from previous work, we discuss (i) optimisations based on a separation of terminological data from assertional data and (ii) the application of authoritative analysis to constrain third party interference with popular ontology terms. We also provide discussion relating to the applicability of new OWL 2 constructs for two popular Semantic Web ontologies -namely FOAF and SIOC -and provide some evaluation of the proposed use-cases based on reasoning over a representative Web dataset of approx. 12 million statements.

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Section: Related Workmentioning

confidence: 99%

On the Ostensibly Silent ‘W’ in OWL 2 RL

Hogan

Decker

2009

Web Reasoning and Rule Systems

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“…Consequently, for many of these languages there already exist highly scalable systems which have been applied successfully to industrial-strength applications, like OWLim [1] and Oracle's RDF Semantic Graph [7]. The attractive properties of these systems have led application developers to use them even in cases where the input ontology is expressed in the far more expressive OWL 2 DL language.…”

Section: Introductionmentioning

confidence: 99%

Hydrowl: A Hybrid Query Answering System for OWL 2 DL Ontologies

Stoilos

2014

Web Reasoning and Rule Systems

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Abstract. This system description paper introduces the OWL 2 query answering system Hydrowl. Hydrowl is based on novel hybrid techniques which in order to compute the query answers combine at run-time a reasoner ans1 supporting a (tractable) fragment of OWL 2 (e.g., OWL 2 QL and OWL 2 RL) with a fully-fledged OWL 2 DL reasoner ans2. The motivation is that if most of the (query answering) work is delegated to the (usually) very scalable system ans1 while the interaction with ans2 is kept to a bare minimum, then we can possibly provide with scalable query answering even over expressive fragments of OWL 2 DL. We discuss the system's architecture and we present an overview of the techniques used. Finally, we present some first encouraging experimental results.

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“…Prominent examples include OWLim [7], Oracle's Semantic Graph [19], Apache Jena, 1 and many more. Such systems can load any OWL ontology but they will ignore all its parts that do not fall within the fragment they support.…”

Section: Introductionmentioning

confidence: 99%

Ontology-Based Data Access Using Rewriting, OWL 2 RL Systems and Repairing

Stoilos

2014

Lecture Notes in Computer Science

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Abstract. In previous work it has been shown how an OWL 2 DL ontology O can be 'repaired' for an OWL 2 RL system ans-that is, how we can compute a set of axioms R that is independent from the data and such that ans that is generally incomplete for O becomes complete for all SPARQL queries when used with O ∪ R. However, the initial implementation and experiments were very preliminary and hence it is currently unclear whether the approach can be applied to large and complex ontologies. Moreover, the approach so far can only support instance queries. In the current paper we thoroughly investigate repairing as an approach to scalable (and complete) ontology-based data access. First, we present several non-trivial optimisations to the first prototype. Second, we show how (arbitrary) conjunctive queries can be supported by integrating well-known query rewriting techniques with OWL 2 RL systems via repairing. Third, we perform an extensive experimental evaluation obtaining encouraging results. In more detail, our results show that we can compute repairs even for very large real-world ontologies in a reasonable amount of time, that the performance overhead introduced by repairing is negligible in small to medium sized ontologies and noticeable but manageable in large and complex one, and that the hybrid reasoning approach can very efficiently compute the correct answers for real-world challenging scenarios.

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Implementing an Inference Engine for RDFS/OWL Constructs and User-Defined Rules in Oracle

Cited by 90 publications

References 8 publications

On the Ostensibly Silent ‘W’ in OWL 2 RL

On the Ostensibly Silent ‘W’ in OWL 2 RL

Hydrowl: A Hybrid Query Answering System for OWL 2 DL Ontologies

Ontology-Based Data Access Using Rewriting, OWL 2 RL Systems and Repairing

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