Title
Towards a Symptom Ontology for Semantic Web Applications
Abstract
As the use of Semantic Web ontologies continues to expand there is a growing need for tools that can validate ontological consistency and provide guidance in the correction of detected defects and errors. A number of tools already exist as evidenced by the ten systems participating in the W3C's evaluation of the OWL Test Cases. For the most part, these first generation tools focus on experimental approaches to consistency checking, while minimal attention is paid to how the results will be used or how the systems might interoperate. For this reason very few of these systems produce results in a machine-readable format (for example as OWL annotations) and there is no shared notion across the tools of how to identify and describe what it is that makes a specific ontology or annotation inconsistent. In this paper we propose the development of a Symptom Ontology for the Semantic Web that would serve as a common language for identifying and describing semantic errors and warnings that may be indicative of inconsistencies in ontologies and annotations; we refer to such errors and warnings as symptoms. We offer the symptom ontology currently used by the ConsVISor consistency-checking tool, as the starting point for a discussion on the desirable characteristics of such an ontology. Included among these characteristics are 1) a hierarchy of common symptoms, 2) clear associations between specific symptoms and the axioms of the languages they violate and 3) a means for relating individual symptoms back to the specific constructs in the input file(s) through which they were implicated. We conclude with aa number of suggestions for future directions of this work including its extension to syntactic symptoms.
Year
DOI
Venue
2004
10.1007/978-3-540-30475-3_45
LECTURE NOTES IN COMPUTER SCIENCE
Keywords
Field
DocType
semantic web
Ontology (information science),Ontology alignment,Ontology-based data integration,Data mining,Information retrieval,Process ontology,Semantic Web Stack,Computer science,OWL-S,Social Semantic Web,Upper ontology,Database
Conference
Volume
ISSN
Citations 
3298
0302-9743
11
PageRank 
References 
Authors
1.61
2
5
Name
Order
Citations
PageRank
Kenneth Baclawski158474.71
Christopher J. Matheus21071333.53
Mieczyslaw M. Kokar3498148.01
Jerzy Letkowski412812.83
Paul A. Kogut518718.37