Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We shall use the generic term information systems, in its broadest sense, to collectively refer to these application perspectives. We argue in this paper that so-called ontologies present their own methodological and architectural peculiarities: on the methodological side, their main peculiarity is the adoption of a highly interdisciplinary approach, while on the architectural side the most interesting aspect is the centrality of the role they can play in an information system, leading to the perspective of ontology-driven information systems.

This paper introduces a geographic information system architecture based on ontologies. Ontology plays a central role in the definition of all aspects and components of an information system in the so-called ontology-driven information systems. The system presented here uses a container of interoperable geographic objects. The objects are extracted from multiple independent data sources and are derived from a strongly typed mapping of classes from multiple ontologies. This approach provides a great level of interoperability and allows partial integration of information when completeness is impossible.

The purpose of this paper is to explore some semantic problems related to the use of linguistic ontologies in information systems, and to suggest some organizing principles aimed t o solve such problems. The taxonomic structure of current ontologies is unfortunately quite complicated and hard to understand, especially for what concerns the upper levels. I will focus here on the problem of ISA overloading, which I believe is the main responsible of these difficulties. To this purpose, I will carefully analyze the ontological nature of the categories used in current upper-level structures, considering the necessity of splitting them according to more subtle distinctions or the opportunity of excluding them because of their limited organizational role.

A model is a formal description of a complex application artifact, such as a database schema, an application interface, a UML model, an ontology, or a message format. The problem of merging such models lies at the core of many meta data applications, such as view integration, mediated schema creation for data integration, and ontology merging. This paper examines the problem of merging two models given correspondences between them. It presents requirements for conducting a merge and a specific algorithm that subsumes previous work.

The word integration has been used with different meanings in the ontology field. This article aims at clarifying the meaning of the word "integration" and presenting some of the relevant work done in integration. We identify three meanings of ontology "integration": when building a new ontology reusing (by assembling, extending, specializing or adapting) other ontologies already available; when building an ontology by merging several ontologies into a single one that unifies all of them; when building an application using one or more ontologies. We discuss the different meanings of "integration", identify the main characteristics of the three different processes and propose three words to distinguish among those meanings: integration, merge and use.

Introduction The web explosion, both at internet and intranet level, has transformed the electronic information system from single isolated node to an entry points into a worldwide network of information exchange and business transactions. Business and commerce has taken the opportunity of the new technologies to define the e-commerce activity. An electronic marketplace represents a virtual place where buyers and sellers meet to exchange goods and services, by sharing information that is often obtained as hypertext catalogs from different companies. Companies have equipped themselves with data storing systems building up informative systems containing data which are related one another, but which are often redundant, heterogeneous and not always substantial. The problems that have to be faced in this field are mainly due to both structural and application heterogeneity, as well as to the lack of a common ontology, causing semantic differences between information sources. Moreo

The assessment of semantic similarity among objects is a basic requirement for semantic interoperability. This paper presents an innovative approach to semantic similarity assessment by combining the advantages of two different strategies: featurematching process and semantic distance calculation. The model involves a knowledge base of spatial concepts that consists of semantic relations (is-a and part-whole) and distinguishing features (functions, parts, and attributes). By taking into consideration cognitive properties of similarity assessments, this model expects to represent a cognitively plausible and computationally achievable method for measuring the degree of interoperability.

Geographical context is required of many information retrieval tasks in which the target of the search may be documents, images or records which are referenced to geographical space only by means of place names. Often there may be an imprecise match between the query name and the names associated with candidate sources of information.

We propose a new catalog based on a formal ontological model of bibliographic relations. A hierarchy of five central concepts describes the creation of work. Each kind of relation between works occurs at a particular level in the hierarchy. Related works share data at some level of the hierarchy, yielding a tree structure that reduces redundant representation of shared attributes. To show that ontology-based metadata is practical, we generated a knowledge base of metadata from a sample of MARC records. We implemented the ontology in description logic (Loom), mapped Machine Readable Cataloging (MARC) attributes and values to the ontology, and loaded the data into Loom with all values treated as separate instances. We then unified matching instances, and deduced relations between works. This process thus converts relationships implicit in MARC into explicit relations that are easy to utilize with computers. Our web interface permits browsing by navigating relations between works. Ontolog...

The integration of information of different kinds, such as spatial and alphanumeric at different levels of detail, is a challenge. While a solution is not reached, it is widely recognized that the need to integrate information is so pressing that it does not matter if detail is lost, as long as integration is achieved. This paper shows the potential for information retrieval at different levels of granularity inside the framework of information systems based on ontologies. Ontologies are theories that use a specific vocabulary to describe entities, classes, properties and functions related to a certain view of the world. The use of an ontology, translated into an active information system component, leads to Ontology-Driven Information Systems and, in the specific case of GIS, leads to what we call Ontology-Driven Geographic Information Systems.