Alignment-based modules for encapsulating ontologies

2009

Ontology merging/alignment is one of the most important tasks in ontology engineering. It is imposed by the decentralized nature of both the WWW and the Semantic Web, where heterogeneous and incompatible ontologies can be developed by different communities. Usually, ontology merging/alignment is based on an ontology mapping that has been established in a previous phase. In this paper, we define a new problem within the alignment process: the problem of detecting and then updating only interesting parts of an ontology, based on the knowledge included in another one. To this end, we define and evaluate a number of different measures of interestingness of parts of ontologies. We also present experimental results for their evaluation on test ontologies.

HAL (Le Centre pour la Communication Scientifique Directe), 2009

Ontology modularization could help overcome the problem of defining a fragment of an existing ontology to be reused, in order to enable ontology developers to include only those concepts and relations that are relevant for the application they are modeling an ontology for. This paper presents a concrete tool that incorporates an approach to ontology modularization that inherits some of the main principles from object-oriented software engineering, which are encapsulation and information hiding. What motivated us to track that direction is the fact that most ontology approaches to the problem focus on linking ontologies rather than building modules that can encapsulate foreign parts of ontologies(or other modules) that can be managed more easily.

2008

Relating ontologies is very important for many ontology-based applications and more important in open environments like the Semantic Web. The relations between ontology entities can be obtained by ontology matching and represented as alignments. Hence, alignments must be taken into account in ontology management. This chapter establishes the requirements for alignment management.

2008

In today's semantic web, ontology fragmentation and mo-dularization are considered as important tasks due to the size and co-mplexity of prime ontologies. At the same time, the ontology alignment community thrives with solutions for discovering and producing align-ments between semantically related concepts. However, these are seldom used in bulk and their subsequent re-use is somewhat problematic. In this paper we set to explore these issues from a practical viewpoint: use ontology alignments to inform an ontology ...

2005

Ontologies are becoming increasingly common in the World Wide Web as the building block for a future Semantic Web. In this Web, ontologies will be responsible for making the semantics of pages and applications explicit, thus allowing electronic agents to process and integrate resources automatically. The ability to integrate different ontologies meaningfully is thus critical to assure coordinated action in multi agent systems. In this paper, we propose a strategy and tool, CATO, that allow for totally automatic ontology alignment for the Semantic Web.

Proc. of the 20th Int. Joint Conf …, 2007

Modularity is a key requirement for collaborative ontology engineering and for distributed ontology reuse on the Web. Modern ontology languages, such as OWL, are logic-based, and thus a useful notion of modularity needs to take the semantics of ontologies and their implications into account. We propose a logic-based notion of modularity that allows the modeler to specify the external signature of their ontology, whose symbols are assumed to be defined in some other ontology. We define two restrictions on the usage of the external signature, a syntactic and a slightly less restrictive, semantic one, each of which is decidable and guarantees a certain kind of "black-box" behavior, which enables the controlled merging of ontologies. Analysis of real-world ontologies suggests that these restrictions are not too onerous.

Journal of Information Science, 2015

Semantic web is dependent on extensive knowledge management by inter linking resources on the web using matching techniques. This role is played by the progressing domain of ontology matching, by introducing ontology matching tools. The focus of these matching tools is limited to matching techniques and automation only, rather than expressive formal representation of alignments. We propose Mediation Bridge Ontology (MBO), an expressive alignment representation ontology used to store correspondences between matching ontologies matched by our ontology matching tool, System for Parallel Heterogeneity Resolution (SPHeRe). The MBO utilizes object oriented design patterns and the proposed ontology alignment design patterns to provide extendibility and reusability factors to SPHeRe system. We compared our proposed system with existing systems using Coupling Factor (COF), Number of Polymorphic methods (NOP), and Rate of Change (RoC) metrics to support extendibility and reusability. These factors contributes in the overall objective of interoperability for knowledge management in the semantic web.

IEEE Expert / IEEE Intelligent Systems, 2008

2007

Modularity is a key requirement for collaborative ontology engineering and for distributed ontology reuse on the Web. Modern ontology languages, such as OWL, are logic-based, and thus a useful notion of modularity needs to take the semantics of ontologies and their implications into account. We propose a logic-based notion of modularity that allows the modeler to specify the external signature of their ontology, whose symbols are assumed to be defined in some other ontology. We define two restrictions on the usage of the external signature, a syntactic and a slightly less restrictive, semantic one, each of which is decidable and guarantees a certain kind of "black-box" behavior, which enables the controlled merging of ontologies. Analysis of real-world ontologies suggests that these restrictions are not too onerous.

1999

As researchers in the ontology-design field develop the content of a growing number of ontologies, the need for sharing and reusing this body of knowledge becomes increasingly critical. Aligning and merging existing ontologies, which is usually handled manually, often constitutes a large and tedious portion of the sharing process. We have developed SMART, an algorithm that provides a semi-automatic approach to ontology merging and alignment. SMART assists the ontology developer by performing certain tasks automatically and by guiding the developer to other tasks for which his intervention is required. SMART also determines possible inconsistencies in the state of the ontology that may result from the user's actions, and suggests ways to remedy these inconsistencies. We define the set of basic operations that are performed during merging and alignment of ontologies, and determine the effects that invocation of each of these operations has on the process. SMART is based on an extremely general knowledge model and, therefore, can be applied across various platforms.