Pellet: A practical OWL-DL reasoner (original) (raw)

A rule-based object-oriented OWL reasoner

Knowledge and Data …, 2008

In this paper we describe O-DEVICE, a memory-based knowledge base system for reasoning and querying OWL ontologies by implementing RDF/OWL entailments in the form of production rules in order to apply the formal semantics of the language. Our approach is based on a transformation procedure of OWL ontologies into an Object-Oriented schema and the application of inference production rules over the generated objects in order to implement the various semantics of OWL. In order to enhance the performance of the system, we introduce a dynamic approach of generating production rules for ABOX reasoning and an incremental approach of loading ontologies. O-DEVICE is built over the CLIPS production rule system, using the object-oriented language COOL to model and handle ontology concepts and RDF resources. One of the contributions of our work is that we enable a well-known and efficient production rule system to handle OWL ontologies. We argue that although native OWL rule reasoners may process ontology information faster, they lack some of the key features that rule systems offer, such as the efficient manipulation of the information through complex rule programs. We present a comparison of our system with other OWL reasoners, showing that O-DEVICE can constitute a practical rule environment for ontology manipulation.

A Survey of Current, Stand-alone OWL Reasoners

2015

We present a survey of the current OWL reasoner landscape. Through literature and web search we have identified 35 OWL reasoners that are, at least to some degree, actively maintained. We conducted a survey directly addressing the respective developers, and collected 33 responses. We present an analysis of the survey, characterising all reasoners across a wide range of categories such as supported expressiveness and reasoning services. We will also provide some insight about ongoing research efforts and a rough categorisation of reasoner calculi.

DLEJena: A practical forward-chaining OWL 2 RL reasoner combining Jena and Pellet

… Semantics: Science, Services and Agents on …, 2010

This paper describes DLEJena, a practical reasoner for the OWL 2 RL profile that combines the forward-chaining rule engine of Jena and the Pellet DL reasoner. This combination is based on rule templates, instantiating at run-time a set of ABox OWL 2 RL/RDF Jena rules dedicated to a particular TBox that is handled by Pellet. The goal of DLEJena is to handle efficiently, through instantiated rules, the OWL 2 RL ontologies under direct semantics, where classes and properties cannot be at the same time individuals. The TBox semantics are treated by Pellet, reusing in that way efficient and sophisticated TBox DL reasoning algorithms. The experimental evaluation shows that DLEJena achieves more scalable ABox reasoning than the direct implementation of the OWL 2 RL/RDF rule set in the Jena's production rule engine, which is the main target of the system. DLEJena can be also used as a generic framework for applying an arbitrary number of entailments beyond the OWL 2 RL profile.

RESP: A Computer Aided OWL REasoner Selection Process

2011 IEEE Fifth International Conference on Semantic Computing, 2011

Existing approaches for selecting the most appropriate reasoner for different semantic applications mainly relies on discussions between application developers and reasoner experts. However this approach will become inadequate with the increasing adoption of Semantic Web technologies in applications from different domains and the rapid development of OWL reasoning technologies. This work proposes RESP, a computer aided reasoner selection process designed to perform reasoner selection for different applications and so reduce the effort and communication overhead required to select the most appropriate reasoner. Preliminary evaluation results show that RESP successfully helps application developers to select the most appropriate reasoner, or at least narrow down the number of candidate reasoners to consider. Contributions of this work are two folds: (1) the design of a (relatively simple but useful) computer aided OWL reasoner selection process, and (2) the identification and discussion of a set of example application characteristics that can affect the OWL reasoner selection.

Comparation of OWL Ontologies Reasoners - Testing Cases with Pellet and Jena

This article describes the results of an evaluation process of four OWL reasoners: Pellet and other three included in Jena framework (OWL Default, OWL Mini, and OWL Micro). A simple ontology about programming languages has been used for the validation process carried out by reasoners and a Java program has been developed for testing different cases: reasoning over the original ontology model and testing different possible inference situations.

Combining a DL reasoner and a rule engine for improving entailment-based OWL reasoning

The Semantic Web-ISWC 2008, 2008

We introduce the notion of the mixed DL and entailment-based (DLE) OWL reasoning, defining a framework inspired from the hybrid and homogeneous paradigms for integration of rules and ontologies. The idea is to combine the TBox inferencing capabilities of the DL algorithms and the scalability of the rule paradigm over large ABoxes. Towards this end, we define a framework that uses a DL reasoner to reason over the TBox of the ontology (hybrid-like) and a rule engine to apply a domain-specific version of ABoxrelated entailments (homogeneous-like) that are generated by TBox queries to the DL reasoner. The DLE framework enhances the entailment-based OWL reasoning paradigm in two directions. Firstly, it disengages the manipulation of the TBox semantics from any incomplete entailment-based approach, using the efficient DL algorithms. Secondly, it achieves faster application of the ABoxrelated entailments and efficient memory usage, comparing it to the conventional entailment-based approaches, due to the low complexity and the domainspecific nature of the entailments.

OWL Reasoner Evaluation (ORE) Workshop 2013 Results: Short Report

The OWL reasoner evaluation (ORE) workshop brings together reasoner developers and ontology engineers in order to discuss and evaluate the performance and robustness of modern reasoners on OWL ontologies. In addition to paper submissions, the workshop featured a live and offline reasoner competition where standard reasoning tasks were tested: classification, consistency, and concept satisfiability. The reasoner competition is performed on several large corpora of reallife OWL ontologies obtained from the web, as well as user-submitted ontologies which were found to be challenging for reasoners. Overall there were 14 reasoner submissions for the competition, some of which dedicated to certain subsets or profiles of OWL 2, and implementing different algorithms and optimisations. In this report, we give an overview of the competition methodology and present a summary of its results, divided into the respective categories based on OWL 2 profiles and test corpora.

Quest, an OWL 2 QL reasoner for ontology-based data access

2012

Abstract. Ontology Based Data Access (OBDA) has drawn considerable attention from the OWL and RDF communities. In OBDA, instance data is accessed by means of mappings, which state the relationship between the data in a data source (eg, an RDBMSs) and the vocabulary of an ontology. In this paper we present Quest, a new system for OBDA focused on fast and efficient reasoning with large ontologies and large volumes of data.

Reintroducing CEL as an OWL 2 EL Reasoner

2009

The CEL system is known for its scalability of reasoning in the lightweight DL EL ++ which has been proved suitable for several ontology applications, most notably from the life science domain. Recently, the DL EL ++ has been adopted as the logical underpinning of the OWL 2 EL profile of the new Web Ontology Language which potentially attracts new folks of CEL's users. To seamlessly integrate the reasoner to the OWL user community, we have implemented the OWL API for CEL. This paper describes the challenges, design decision and architecture of this implementation. Additionally, we present experimental results which highlight the scalability of the reasoner, as well as demonstrate a low overhead of our OWL API implementation. ⋆ Funded by the German Research Foundation (DFG) under grant BA 1122/11-1. 1 CEL's sources are now open and obtainable at