A Rule-Based Object-Oriented OWL Reasoner

Meditskos, Georgios; Bassiliades, Nick

doi:10.1109/tkde.2007.190699

Cited by 47 publications

(22 citation statements)

References 25 publications

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“…Alternatively, we could enable developers to model the hierarchical semantics of events explicitly using ontologies expressed in a standard semantic language such as OWL. There is already a significant body of work on incorporating OWL in Rete-based inference engines (e.g., [8,21]). …”

Section: Limitations and Future Workmentioning

confidence: 99%

CrimeSPOT : A language and runtime for developing active wireless sensor network applications

Roover

Scholliers

Amerijckx

et al. 2013

Science of Computer Programming

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Advances in wireless sensing and actuation technology allow embedding significant amounts of application logic inside wireless sensor networks. Such active WSN applications are more autonomous, but are significantly more complex to implement. Event-based middleware lends itself to implementing these applications. It offers developers fine-grained control over how an individual node interacts with the other nodes of the network. However, this control comes at the cost of event handlers which lack composability and violate software engineering principles such as separation of concerns. In this paper, we present CrimeSPOT as a domain-specific language for programing WSN applications on top of event-driven middleware. Its node-centric features enable programming a node's interactions through declarative rules rather than event handlers. Its network-centric features support reusing code within and among WSN applications. Unique to CrimeSPOT is its support for associating application-specific semantics with events that carry sensor readings. These preclude transposing existing approaches that address the shortcomings of event-based middleware to the domain of wireless sensor networks. We provide a comprehensive overview of the language and the implementation of its accompanying runtime. The latter comprises several extensions to the Rete forward chaining algorithm. We evaluate the expressiveness of the language and the overhead of its runtime using small, but representative active WSN applications.

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Section: Limitations and Future Workmentioning

confidence: 99%

CrimeSPOT : A language and runtime for developing active wireless sensor network applications

Roover

Scholliers

Amerijckx

et al. 2013

Science of Computer Programming

View full text Add to dashboard Cite

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“…The first popular approach to emulate a reasoner using CLIPS is described in [13]. Here the object oriented extension of CLIPS, called COOL, was used to build a reasoner for the OWL1 Lite [23] sub-language.…”

Section: Related Workmentioning

confidence: 99%

Rule-Based OWL Reasoning for Specific Embedded Devices

Seitz

Schönfelder

2011

The Semantic Web – ISWC 2011

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Abstract. Ontologies have been used for formal representation of knowledge for many years now. One possible knowledge representation language for ontologies is the OWL 2 Web Ontology Language, informally OWL 2. The OWL specification includes the definition of variants of OWL, with different levels of expressiveness. OWL DL and OWL Lite are based on Description Logics, for which sound and complete reasoners exits. Unfortunately, all these reasoners are too complex for embedded systems. But since evaluation of ontologies on these resource constrained devices becomes more and more necessary (e.g. for diagnostics) we developed an OWL reasoner for embedded devices. We use the OWL 2 sub language OWL 2 RL, which can be implemented using rule-based reasoning engines. In this paper we present our used embedded hardware, the implemented reasoning component, and results regarding performance and memory consumption.

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“…O-DEVICE [11] translates OWL rules into an in-memory representation, and can process all of. It can process all of OWL-DL except oneOf, complementOf or data ranges.…”

Section: Related Workmentioning

confidence: 99%

SQOWL: Type Inference in an RDBMS

McBrien

Rizopoulos

Smith

2010

Conceptual Modeling – ER 2010

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Abstract. In this paper we describe a method to perform type inference over data stored in an RDBMS, where rules over the data are specified using OWL-DL. Since OWL-DL is an implementation of the Description Logic (DL) called SHOIN (D), we are in effect implementing a method for SHOIN (D) reasoning in relational databases. Reasoning may be broken down into two processes of classification and type inference. Classification may be performed efficiently by a number of existing reasoners, and since classification alters the schema, it need only be performed once for any given relational schema as a preprocessor of the schema before creation of a database schema. However, type inference needs to be performed for each data value added to the database, and hence needs to be more tightly coupled with the database system. We propose a technique to meet this requirement based on the use of triggers, which is the first technique to fully implement SHOIN (D) as part of normal transaction processing.

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A Rule-Based Object-Oriented OWL Reasoner

Cited by 47 publications

References 25 publications

CrimeSPOT : A language and runtime for developing active wireless sensor network applications

CrimeSPOT : A language and runtime for developing active wireless sensor network applications

Rule-Based OWL Reasoning for Specific Embedded Devices

SQOWL: Type Inference in an RDBMS

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