A similarity based approach to omission finding in ontologies

2007

Ontology evaluation is one of the most important phases of Ontology Engineering. Researchers have identified different types of errors that should be catered in ontology evaluation process and classified them in error's taxonomy. We have found that some important errors are missing in the error's taxonomy. We have identified and defined two new incompleteness errors i.e. Functional Property Omission (FPO) for single valued property and Inverse-Functional Property Omission (IFPO) for a unique valued property. We have demonstrated the importance of such errors by giving different scenarios where appropriate. We have evaluated different ontologies and presented empirical results..

Procedia Computer Science, 2011

The last decade has seen researchers developing efficient algorithms for the mapping and merging of ontologies to meet the demands of interoperability between heterogeneous and distributed information systems. But, still state-of-the-art ontology mapping and merging systems is semi-automatic that reduces the burden of manual creation and maintenance of mappings, and need human intervention for their validation. The contribution presented in this paper makes human intervention one step more down by automatically identifying semantic inconsistencies in the early stages of ontology merging. Our methodology detects inconsistencies based on structural mismatches that occur due to conflicts among the set of Generalized Concept Inclusions, and Disjoint Relations due to the differences between disjoint partitions in the local heterogeneous ontologies. We present novel methodologies to detect and repair semantic inconsistencies from the list of initial mappings. This results in global merged ontology free from 'circulatory error in class/property hierarchy', 'common class/instance between disjoint classes error', 'redundancy of subclass/subproperty relations', 'redundancy of disjoint relations' and other types of 'semantic inconsistency' errors. In this way, our methodology saves time and cost of traversing local ontologies for the validation of mappings, improves performance by producing only consistent accurate mappings, and reduces the user dependability for ensuring the satisfiability and consistency of merged ontology. The experiments show that the newer approach with automatic inconsistency detection yields a significantly higher precision.

2011

Abstract. The canonical standard description logic reasoning service is classification, that is, the generation of the set of atomic subsumptions which are entailed by some ontology. While this consequence relation is well defined and finite, there is significant variance in the composition of that set. For example, it is common (in tools and in discussion) to exclude some tautologies (eg, A⊑, A⊑ A).

2006

ABSTRACT Populated ontologies continue to be an important component in techniques and applications in semantic technologies. Thus, it is necessary to evaluate their quality. Our focus is the detection of conflicting information (within an ontology) as a criterion to improve the quality of an ontology. We describe different types of conflicts and propose a rule-based approach by which human experts can define conditions that signal a conflict in data.

Advances in intelligent web …, 2007

Ontology evaluation is as important as its designing and application. Researchers have identified different errors which should be catered in ontology evaluation process and classified them in error's taxonomy. We have found that some important errors are missing in the error's taxonomy. We have identified and defined new errors i.e. sufficient knowledge omis-sion error (SKO) and redundancy disjoint relation error (RDR) and catego-rized them in appropriate category of error's taxonomy.

cs.ox.ac.uk

To achieve scalability of query answering, the developers of Semantic Web applications are often forced to use incomplete OWL 2 reasoners, which fail to derive all answers for at least one query, ontology, and data set. The lack of completeness guarantees, however, may be unacceptable for applications in areas such as health care and defence, where missing answers can adversely affect the application's functionality. Furthermore, even if an application can tolerate some level of incompleteness, it is often advantageous to estimate how many and what kind of answers are being lost.

International Journal of Digital Content Technology and its Applications, 2011

Rules play a primary role in reasoning process to retrieve implicit and potentially useful knowledge in the Semantic Web. SWRL rules are increasingly being used to represent knowledge on the Semantic Web by using horn-like form to reason among ontologies. It is one of the key issues to keep the rule set consistent and efficient for maintaining rules in Semantic Web. In this paper, we present an approach to dealing with redundant rules among SWRL rule set. An algorithm is proposed based on the conception of literal set closure to detect and eliminate implication redundancy. Experiment results show that the proposed approach deals with the redundancy in the sample rule set efficiently and effectively. Besides, we study the consistency check of the rule set and propose algorithms to eliminate the dead-end rules, conflictions, rules with redundant antecedents, and circular rules.

2006

EU-IST Integrated Project (IP) IST-2003-506826 SEKT Deliverable D3.4.1(WP3.4) In this document we propose a general framework for reasoning with inconsistent ontologies. We present formal definitions of soundness, meaningfulness, local completeness, and maximal completeness of an inconsistency reasoner. We propose and investigate a pre-processing algorithm and discuss the strategies of inconsistency reasoning based on pre-defined selection functions dealing with concept relevance. In this document, we also present a prototype of a reasoner for Processing Inconsistent ONtologies (PION), which is implemented in XDIG, an extended DIG Description Logic Interface for Prolog. We also discuss how the syntactic relevance can be used in the implementation of the prototype.

Lecture Notes in Computer Science, 2011

Ontologies may contain redundancy in terms of axioms that logically follow from other axioms and that could be removed for the sake of consolidation and conciseness without changing the overall meaning. In this paper, we investigate methods for removing such redundancy from ontologies. We define notions around redundancy and discuss typical cases of redundancy and their relation to ontology engineering and evolution. We provide methods to compute irredundant ontologies both indirectly by calculating justifications, and directly by utilising a hitting set tree algorithm and module extraction techniques for optimization. Moreover, we report on experimental results on removing redundancy from existing ontologies available on the Web.

Web Semantics: Science, Services and Agents on the World Wide Web, 2010

For the development of practical semantic applications, ontologies are commonly used with rule extensions. Prominent examples of semantic applications are Semantic Wikis, Semantic Desktops, but also advanced Web Services and agents. The application of rules increases the expressiveness of the underlying knowledge in many ways. Likewise, the integration creates new challenges for the design process of such ontologies, but also existing evaluation methods have to cope with the extension of ontologies by rules. Since the verification of OWL ontologies with rule extensions is not tractable in general, we propose to verify ontologies at the symbolic level by using a declarative approach: With the new language DATALOG , known anomalies can be easily specified and tested in a compact manner. We introduce supplements to existing verification techniques to support the design of ontologies with rule enhancements, and we focus on the detection of anomalies that especially occur due to the combined use of rules and ontological definitions.