Showing papers on "Ontology-based data integration published in 1995"

Issues in the structuring and acquisition of an ontology for medical language understanding.

Abstract: Issues in the structuring and acquisition of an ontology for medical language understanding. -

A linguistic ontology

Abstract: This paper defends the choice of a linguistically-based content ontology for natural language processing and demonstrates that a single common-sense ontology produces plausible interpretations at all levels from parsing through reasoning. The paper explores some of the problems and tradeoffs for a method which has just one content ontology. A linguistically-based content ontology represents the "world view" encoded in natural language. The content ontology (as opposed to the formal semantic ontology which distinguishes events from propositions, and so on) is best grounded in the culture, rather than in the world itself, or in the mind. By "world view" we mean naive assumptions about "what there is" in the world, and how it should be classified. These assumptions are time-worn and reflected in language at several levels: morphology, syntax and lexical semantics. The content ontology presented in the paper is part of a Naive Semantic lexicon, Naive Semantics is a lexical theory in which associated with each word sense is a naive theory (or set of beliefs) about the objects or events of reference. While naive semantic representations are not combinations of a closed set of primitives, they are also limited by a shallowness assumption. Included is just the information required to form a semantic interpretation incrementally, not all of the information known about objects. The Naive Semantic ontology is based upon a particular language, its syntax and its word senses. To the extent that other languages codify similar world views, we predict that their ontologies are similar. Applied in a computational natural language understanding system, this linguistically-motivated ontology (along with other native semantic information) is sufficient to disambiguate words, disambiguate syntactic structure, disambiguate formal semantic representations, resolve anaphoric expressions and perform reasoning tasks with text.

The PhysSys Ontology for Physical Systems

Abstract: We give an outline of a formal ontology for physical systems. It is based upon system dynamics theory as practiced in engineering modelling, simulation and design . We introduce multiple engineering ontologies-system layout, physical processes underlying behaviour, descriptive mathematical relations that express different conceptual viewpoints upon a physical system . These three views combine the QR device, process and constraint approaches . It is discussed how these viewpoints can be formally specified in terms of separate generic ontologies, which are relatively loosely coupled through ontology mapping rules. These ontologies provide a formal conceptual foundation for the structure of the OLMECO library of reusable models for engineering design in mechatronics currently under development .

Agent organization and communication with multiple ontologies

Abstract: In this paper, we discuss how ontology plays roles in building a distributed and heterogeneous knowledge-base system. First, we discuss relationship between ontology and agents in the which is a framework of knowledge sharing and reuse based on a multi-agent architecture. Ontology is a minimum requirement for each agent to join the . Second, we explain mediation by ontology to show how ontology is used in the . A special agent called mediator analyzes undirected messages and infer candidates of recipient agents by consulting ontology and relationship between ontology and agents. Third, we model ontology as combination of aspects each of which can represent a way of conceptualization. Aspects are combined either as combination aspect which means integration of aspects or category aspect which means choice of aspects. Since ontology by aspect allows heterogeneous and multiple descriptions for phenomenon in the world, it is appropriate for heterogeneous knowledge-base systems. We also show translation of messages as a way of interpreting multiple aspects. A translation agent can translate a message with some aspect to one with another aspect by analyzing dependency of aspects. Mediation and translation of messages are important to build agents easily and naturally because less knowledge on other agents is requested for each agent.

Semint: a system prototype for semantic integration in heterogeneous databases

Abstract: N

An Event-Based Software Integration Framework

Abstract: Although event-based software integration is one of the most prevalent approaches to loose integration, no consistent model for describing it exists. As a result, there is no uniform way to discuss event-based integration, compare approaches and implementations, specify new event-based approaches, or match user requirements with the capabilities of event-based integration products. We attempt to address these shortcomings by specifying a generic framework for event-based integration, the EBI framework, that provides a flexible, object-oriented model for discussing and comparing event-based integration approaches. The EBI framework can model dynamic and static specification, composition and decomposition, and can be instantiated to describe the features of most common event-based integration approaches. We demonstrate how to use the framework as a reference model by comparing and contrasting three popular integration mechanisms: FIELD, Polylith, and CORBA.

Semantic Integration of Conceptual Schemes.

Abstract: Abstract Our goal is to work out an integration process which makes it possible to give a global design schema obtained from several schemas, each of them describing the same reality viewed in different ways, in order to obtain the fullest view. Problems and conflicts arise during the schema integration. They are due to the several ways of representing the semantic knowledge and of structuring knowledge (using the same design model). When the detection and solution of structural problems are model dependent, the detection and solution of semantic problems are not model dependent. To represent the semantic of the words which are used in a schema, we have defined a model of a thesaurus drawn from the domain dealing with the meaning of words: linguistics. In this paper, we will show the interest in using this fuzzy thesaurus when design schema are being integrated.

An object-oriented model for the integration of knowledge-based systems.

Abstract: This paper discusses functional integration, data integration, and knowledge integration as basic problems concerning the integration of knowledge-based systems into a hospital information system. A system model for an integrated knowledge-based system is introduced. Object-oriented models for the systems meta-database, patient database, and knowledge-base are presented. It is expected that the reader is familiar with the basic concepts of the object-oriented approach.