A Method of Policy Conflict Detection Based on SWRL Rules

2012 ◽  
Vol 546-547 ◽  
pp. 955-960
Author(s):  
Jie Zhou ◽  
Qing Guo Shen ◽  
Yu Dong Xu ◽  
Zhen Wei Yu
Keyword(s):  
Distributed Systems ◽  
Conflict Detection ◽  
Web Ontology Language ◽  
Policy Conflict ◽  
Ontology Language ◽  
Ontology Model ◽  
Management Technology ◽  
Policy Based Management ◽  
Novel Method

Policy-based management technology which is used for managing enterprise-wide networks and distributed systems is getting more and more attention. Policy conflict detection and solution is a difficulty in this field. In this paper, we present a novel method of policy conflict detection based on SWRL rules. First, we construct a policy ontology model, and represent the policies with Web Ontology Language (OWL). Then the SWRL rules used to detect conflict is presented. Finally, an example is shown to illustrate how to use our method to detection the conflicts in the managed system, the feasibility and the validity of our proposed method are proved out.

Design and Implement of Dynamic Context-Aware Monitoring System Based on OWL

2012 ◽  
Vol 532-533 ◽  
pp. 601-605
Author(s):  
Dong Juan Xue ◽  
Wen Xiao Zhang
Keyword(s):  
Monitoring System ◽  
Context Aware ◽  
Web Ontology Language ◽  
Intelligent Monitoring ◽  
Local Coordination ◽  
Dynamic Coordination ◽  
Ontology Language ◽  
Ontology Model ◽  
Multi Level ◽  
Global Coordination

Context-aware applications can sense and explore the context of production processes to provide proper and useful services to managers in workshop. The monitoring levels are partitioned and designed in this article. And the multi-level ontology model of materials is found which is expressed in the Web Ontology Language (i.e. OWL) as a ontology collection of describing places ages and events and associated properties among them. Within an intelligent monitoring system, dynamic adjusting algorithm of linking local coordination with global coordination for lacking parts is brought forward and dynamic coordination structure is put up based on event-driven architecture. Context-aware reactive behaviors can be expressed by using rules written in OWL Language, especially developed for context-aware applications.

A Visual Ontological Language for Technical Standards (VOLTS)

2016 ◽  
Author(s):  
Sean Whitsitt ◽  
Sonia Vohnout ◽  
Timothy Wilmering ◽  
Disha Mathad ◽  
Eric Smith
Keyword(s):  
Markup Language ◽  
Web Ontology Language ◽  
Technical Standards ◽  
Organizational Issues ◽  
Ontology Language ◽  
Development Tools ◽  
Standardization Process ◽  
Novel Method ◽  
Social Interfaces ◽  
Future Work

Research shows that failures in the standardization process often result from communication and organizational issues between those involved in the committee and the user community. This is mainly caused by two issues: first, a lack of integration of available standards development tools with communication and social interfaces; and second, to the difficulties inherent in organizing and collating information in a semantically meaningful manner. To this effect, the authors present a Visual Ontological Language for Technical Standards (VOLTS). VOLTS is a prototype environment that seeks to address the latter problem introduced above. In VOLTS, standards developers visually create standards within a network of information. VOLTS builds upon a tool developed by the National Institute of Standards and Technology (NIST) called the NIST Ontological Visualization Interface for Standards (NOVIS), which presented a novel method for visualizing the content and connections of standards, but lacked the ability to allow users to alter that information. VOLTS focuses on providing users with a process that allows for verification and validation at all stages of development. To that effect, VOLTS incorporates research done by NIST on building a Framework for Analysis Comparison, and Test of Standards (FACTS). The examples presented herein use the openly available standards World Wide Web Consortium’s (W3C) Web Ontology Language (OWL) 2 and the Data Mining Group’s (DMG) Predictive Model Markup Language (PMML) to demonstrate the VOLTS process and methodology. Future work discussed will seek to address the former problem introduced above.

tOWL: A Temporal Web Ontology Language

2012 ◽  
Vol 42 (1) ◽  
pp. 268-281 ◽  
Author(s):  
V. Milea ◽  
F. Frasincar ◽  
U. Kaymak
Keyword(s):  
Web Ontology Language ◽  
Ontology Language

scholarly journals Representing SimModel in the Web Ontology Language

2014 ◽  
Author(s):  
P. Pauwels ◽  
E. Corry ◽  
J. O'Donnell
Keyword(s):  
Web Ontology Language ◽  
Ontology Language ◽  
The Web

OWL: Web Ontology Language

2016 ◽  
pp. 1-2 ◽  
Author(s):  
Sean Bechhofer
Keyword(s):  
Web Ontology Language ◽  
Ontology Language

Web Ontology Language

2007 ◽  
pp. 95-130
Author(s):  
Liyang Yu
Keyword(s):  
Web Ontology Language ◽  
Ontology Language

scholarly journals From SHIQ and RDF to OWL: The Making of a Web Ontology Language

2003 ◽  
Author(s):  
Ian Horrocks ◽  
Peter Patel-Schneider ◽  
Frank van Harmelen
Keyword(s):  
Web Ontology Language ◽  
Ontology Language

scholarly journals Development of ontology-based model to support learning process in LMS

2021 ◽  
Vol 24 (1) ◽  
pp. 507
Author(s):  
Hussein Ali Ahmed Ghanim ◽  
László Kovács
Keyword(s):  
Learning Process ◽  
Time Management ◽  
Application Programming Interface ◽  
Domain Ontology ◽  
Actual Process ◽  
Process Ontology ◽  
Support Mechanism ◽  
Ontology Language ◽  
Ontology Model ◽  
E Learning

<p>E-Learning is an important support mechanism for educational systems to increase the efficiency of the education process including students and teachers. The current e-learning systems typically lack the level of metacognitive awareness, adaptive tutoring, and time management skills and have not always met the expectations of the learners as required. In this study, we introduce a novel ontological model for the learning process in the e-learning domain. In the framework, we have built a domain ontology that represents knowledge of the learning, the outcome domain ontology covers the whole learning process. We focused on the learning process ontology model conceptualizing knowledge constructions, such as learning courses, and we present the created course and learning process ontology in detail. In this work, we considered three layers of learning process. The top layer defines a general framework of learning process, conceptual model layer, defines the framework of the actual process of the learning process and course ontology model contains the knowledge unit of the learning process. The prototype ontology is constructed in protégé and managed by Java web ontology language-application programming interface (OWL-API). As a result, our model can solve the problems of current e-tutor systems. Also, it can be used for different domain in e-tutor systems. It can reach the characteristics of standardization, reusability, flexibility, and open knowledge. By applying this model, we can avoid applying isolated databases. The constructed ontology can be used in the future to control adaptive intelligent e-tutor frameworks.</p>

OWL: Web Ontology Language

2014 ◽  
pp. 169-263 ◽  
Author(s):  
Liyang Yu
Keyword(s):  
Web Ontology Language ◽  
Ontology Language

scholarly journals Web Ontology Language: OWL

2009 ◽  
pp. 91-110 ◽  
Author(s):  
Grigoris Antoniou ◽  
Frank van Harmelen
Keyword(s):  
Web Ontology Language ◽  
Ontology Language
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