IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Using the Semantic Web Rule Language in the Development of Ontology-Driven Applications

Using the Semantic Web Rule Language in the Development of Ontology-Driven Applications
View Sample PDF
Author(s): Martin O’Connor (Stanford University, USA), Mark Musen (Stanford University, USA)and Amar Das (Stanford University, USA)
Copyright: 2009
Pages: 15
Source title: Handbook of Research on Emerging Rule-Based Languages and Technologies: Open Solutions and Approaches
Source Author(s)/Editor(s): Adrian Giurca (Brandenburg Technology University at Cottbus, Germany), Dragan Gasevic (Athabasca University, Canada)and Kuldar Taveter (University of Melbourne, Australia)
DOI: 10.4018/978-1-60566-402-6.ch022

Purchase

View Using the Semantic Web Rule Language in the Development of Ontology-Driven Applications on the publisher's website for pricing and purchasing information.

Abstract

The Semantic Web Rule Language (SWRL) is an expressive OWL-based rule language. SWRL allows users to write Horn-like rules that can be expressed in terms of OWL concepts to provide more powerful deductive reasoning capabilities than OWL alone. Semantically, SWRL is built on the same description logic foundation as OWL and provides similar strong formal guarantees when performing inference. Due to its description logics foundation, rule-based applications developed using SWRL have a number of relatively novel characteristics. For example, SWRL shares OWL’s open world assumption so certain types of rules that assume a closed world may be difficult or impossible to write in SWRL. In addition, all inference in SWRL is monotonic so deductions cannot be updated or retracted. These formal characteristic have a strong influence on the development and use of SWRL rules in ontology-driven applications. In this chapter, we describe the primary features of SWRL and outline how, despite some limitations, SWRL can be used to dramatically increase amount of knowledge that be represented in OWL ontologies.

Related Content

Ruizhe Ma, Azim Ahmadzadeh, Soukaina Filali Boubrahimi, Rafal A Angryk. © 2019. 19 pages.
Zhen Hua Liu. © 2019. 25 pages.
Lubna Irshad, Zongmin Ma, Li Yan. © 2019. 25 pages.
Hao Jiang, Ahmed Bouabdallah. © 2019. 22 pages.
Gbéboumé Crédo Charles Adjallah-Kondo, Zongmin Ma. © 2019. 22 pages.
Safa Brahmia, Zouhaier Brahmia, Fabio Grandi, Rafik Bouaziz. © 2019. 20 pages.
Zhangbing Hu, Li Yan. © 2019. 20 pages.
Body Bottom