Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontologies. This paper provides a brief survey of the approaches to semantic integration developed by researchers in the ontology community. We focus on the approaches that differentiate the ontology research from other related areas. The goal of the paper is to provide a reader who may not be very familiar with ontology research with introduction to major themes in this research and with pointers to different research projects. We discuss techniques for finding correspondences between ontologies, declarative ways of representing these correspondences, and use of these correspondences in various semantic-integration tasks 1. ONTOLOGIES AND SEMANTIC INTE-

Ontology mapping, alignment, and translation has been an active research component of the general research on semantic integration and interoperability. In our talk, we gave our own classification of different topics in this research. We talked about types of heterogeneity between ontologies, various mapping representations, classified methods for discovering methods both between ontology concepts and data, and talked about various tasks where mappings are used. In this extended abstract of our talk, we provide an annotated bibliography for this area of research, giving readers brief pointers on representative papers in each of the topics mentioned above. We did not attempt to compile a comprehensive bibliography and hence the list in this abstract is necessarily incomplete. Rather, we tried to sketch a map of the field, with some specific reference to help interested readers in their exploration of the work to-date. 1 Survey Articles For more detailed descriptions and bibliography of the field we refer the readers to several recently published surveys:

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Work performed partly while visiting LADSEB-CNR; Corso Stati Uniti, 4; Padova, Italia, Information systems ontology is intended to facilitate interoperability among the many applications which are now becoming available on the Internet. In particular, it is intended to facilitate the development of intelligent agents which can automate a large part of the task of a user achieving some end employing multiple autonomous applications. A large number of ontologies exist supporting specific kinds of interoperation among selected, generally mutually description of what there is in the world, in an application-independent form, which can be used both to help build specific ontologies and to help in finding common ground among them. This paper argues that for the purposes of information systems interoperation and the semantic web there is a distinction in upper ontologies between formal and material ontologies, based on analogies with concepts in Kant’s synthetic a priori, and that formal ontologies whose focus is on how we see the world are more likely to be successfully developed in the absence of applications than are material ontologies, which attempt to catalog the world a priori. 2

This paper presents an innovative, complex approach to semantic verb classification that relies on selectional preferences as verb properties. The probabilistic verb class model underlying the semantic classes is trained by a combination of the EM algorithm and the MDL principle, providing soft clusters with two dimensions (verb senses and subcategorisation frames with selectional preferences) as a result. A language-model-based evaluation shows that after 10 training iterations the verb class model results are above the baseline results. 1

If the word ontology is more and more used in a number of domain, the capabilities and benefits of ontology for Information Systems management are still unclear. Therefore, the usage of ontology-based Information Systems in industry and services is not widespread. This paper analyses the concept of a domain ontology from a database perspective. As a result, firstly, we provide three criteria that distinguish domain ontology from other existing domain modeling approach which lead us to propose a new definition of domain ontologies. Secondly, based on the various approaches of ontology modeling followed by different communities, we propose a taxonomy of domain ontology. We show how they may be organized into a layered model, called the onion model, allowing to design and to use the capabilities of each category of ontology in anintegrated environment. Finally, this paper presents several information systems based on ontology technologies and describe the kinds of services that should be provided to allow a powerful usage of ontology in data management.

Abstract — One of the main strength of the web is that it realizes the goal of allowing any party of its global community to share information with any other party. This has been achieved by making use of a unique and uniform mechanism of identification, the URI (Universal Resource Identifiers). Web applications such as search engines have been built up on this mechanism. Although URIs succeed when used for retrieving resources on the web, their suitability as a way for identifying any kind of things, for example resources that are not on the web, is not guaranteed. We investigate the meaning of identity of a web resource and how it can be modeled in order to be implemented on the web. In particular, we propose an ontology that models the problem, and discuss some possible solutions. We describe the concept of resource from the web domain point of view, using an ontology of Information Objects, built on top of DOLCE and of some of its modular extensions. In particular, we formalize some concepts of a web resource, and distinguish them from the concept of a generic entity. We finally propose a formal pattern for resource modelling. I.

Consistent ontologies are vital for the growth of the Semantic Web. We describe and appraise the OntoClean methodology and the di#erent implementations available to evaluate taxonomic relationships in ontologies. We propose a new system, CleanONTO, which uses definitions to describe each concept, where definitions are paths from the concept to the root node of the ontology. In the current study, these definitions (paths) have been extracted from WordNet.

Abstract. During the last few years, a number of works aiming at interfacing ontologies and lexical resources have been initiated. This paper aims at clarifying the current picture of this domain. It compares ontologies built following different methodologies and analyses their combination with lexical resources. A point defended in the paper is that different methodologies lead to very different characteristics for the resulting systems. We classify these methodologies and show how actual projects fit into this classification. We also take a more applicative viewpoint by presenting a PROTÉGÉ-based platform that can be exploited in the general task of interfacing ontologies and lexical resources along the different methodological lines. 1

There are a number of genuinely open questions concerning the use of domain models in nlp. It would be great if contributors to Applied Ontology could help addressing them rather than adding to an already long polemical literature... 1 Empiricists vs. Formalists All Over Again? In virtually every workshop on ontologies, terminology, or lexical acquisition I attended in the last years at nlp events I found myself watching (or getting involved in) fierce debates as to which approach to domain categorization is ‘best’: designing a clean, elegant ontology with a clear semantics and based on sound philosophical principles and / or scientific evidence; or relying on evidence from psychology and corpora, and on machine learning techniques, to acquire (automatically, as far as possible) a domain structure that in most cases will be rather messy. (The opposite sides of the argument are presented in (Wilks, 2002) and (Smith, 2004).) Are we back to the bad old days of the ‘neat’