Ontology merging is important, but not always effective. The main reason, why ontology merging is not effective, is that ontology merging is perform ed without considering goals. Goals define the way, in which ontologies to be merg ed more effectively. The paper illustrates ontology m erging by means of rules, which are generate d from these ontologies. This is necessary for further use in expert systems.
Each individual participant can potentially use his own format to represent the products in his product catalog. Complicated products require knowledge-intensive descriptions, or ontologies. Thus, catalog integration requires integration of product ontologies. If a marketplace mediates between n suppliers and m buyers, then it must be able to map each of the n suppliers' catalogs into m buyers' formats performing nxm mappings. The numbers n and m can be high enough to make the problem of creation and maintenance of these catalog integration rules nontrivial. Management of product ontologies and product catalogs occur as a subtask of knowledge management done by the companies. In consequence, it becomes an important part of the ontology-based knowledge management tools, which are now under development within the OntoKnowledge project (www.ontoknowledge.org). The three types of e-commerce mediation: Business-to- Business (B2B), Business-to-Customer (B2C), Customer-to-Customer (C2C) differ in terms of number catalogs, speed requirements, and integration quality.
For my thesis work I am developing a method for evaluating and standardizing ontologies based on an integration of the Basic Formal Ontology (BFO) and OntoClean. BFO serves as the upper ontology for the domain ontologies of the Open Biomedical Ontologies (OBO) Foundry. The OBO Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. OntoClean is an approach for the quality assurance of ontologies, and helps a modeler detect when the subsumption relation is used improperly. Ontologies developed for OBO use include some that have been ratified, and others holding the status of "candidate". To maintain consistency between ontologies, it is important to establish formal principled criteria that a candidate ontology must meet for ratification. The formalisms that result from our integration will serve as criteria an OBO Foundry candidate ontology must satisfy in order to be ratified. The formalisms will also serve as a constraints within a prototype of an ontology editor that interactively asks a modeler questions that helps alleviate constraint violations.
Ontology management and maintenance are considered cornerstone issues in current Semantic Web applications in which semantic integration and ontological reasoning play a fundamental role. The ability to deal with inconsistency and to accommodate change is of utmost importance in realworld applications of ontological reasoning and management, wherein the need for expressing negated assertions also arises naturally. For this purpose, precise, formal definitions of the the different types of inconsistency and negation in ontologies are required. Unfortunately, ontology languages based on Description Logics (DLs) do not provide enough expressive power to represent axiom negations. Furthermore, there is no single, well-accepted notion of inconsistency and negation in the Semantic Web community, due to the lack of a common and solid foundational framework. In this paper, we propose a general framework accounting for inconsistency, negation and change in ontologies. Different levels of negation and inconsistency in DLbased ontologies are distinguished. We demonstrate how this framework can provide a foundation for reasoning with and management of dynamic ontologies.
We discuss the problems associated with managing ontologies in distributed environments such as the Web. The Web poses unique problems for the use of ontologies because of the rapid evolution and autonomy of web sites. We present SHOE, a web-based knowledge representation language that supports multiple versions of ontologies. We describe SHOE in the terms of a logic that separates data from ontologies and allows ontologies to provide different perspectives on the data. We then discuss the features of SHOE that address ontology versioning, the effects of ontology revision on SHOE web pages, and methods for implementing ontology integration using SHOE's extension and version mechanisms.