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-

As ontology development becomes a more ubiquitous and collaborative process, ontology versioning and evolution becomes an important area of ontology research. The many similarities between database-schema evolution and ontology evolution will allow us to build on the extensive research in schema evolution. However, there are also important di#erences between database schemas and ontologies. The di#erences stem from di#erent usage paradigms, the presence of explicit semantics, and di#erent knowledge models. A lot of problems that existed only in theory in database research come to the forefront as practical problems in ontology evolution. These di#erences have important implications for the development of ontology-evolution frameworks: The traditional distinction between versioning and evolution is not applicable to ontologies. There are several dimensions along which compatibility between versions must be considered. The set of change operations for ontologies is di#erent. We must develop automatic techniques for finding similarities and di#erences between versions.

The World Wide Web is emerging not only as an infrastructure for data, but also for a broader variety of resources that are increasingly being made available as Web services. Relevant current standards like UDDI, WSDL, and SOAP are in their fledgling years and form the basis of making Web services a workable and broadly adopted technology. However, realizing the fuller scope of the promise of Web services and associated service oriented architecture will requite further technological advances in the areas of service interoperation, service discovery, service composition, and process orchestration. Semantics, especially as supported by the use of ontologies, and related Semantic Web technologies, are likely to provide better qualitative and scalable solutions to these requirements. Just as semantic annotation of data in the Semantic Web is the first critical step to better search, integration and analytics over heterogeneous data, semantic annotation of Web services is an equally critical first step to achieving the above promise. Our approach is to work with existing Web services technologies and combine them with ideas from the Semantic Web to create a better framework for Web service discovery and composition. In this paper we present MWSAF (METEOR-S Web Service Annotation Framework), a framework for semi-automatically marking up Web service descriptions with ontologies. We have developed algorithms to match and annotate WSDL files with relevant ontologies. We use domain ontologies to categorize Web services into domains. An empirical study of our approach is presented to help evaluate its performance.

Due to the availability on the Internet of a wide variety of sources of information on closely related topics, the problem of providing seamless, integrated access to such sources has become (again) a major research challenge. Although this problem has been studied for several decades, especially in the database community, there is a need for a more refined approach in those cases where the original sources maintain their own independent view of the world. In particular, we motivate with examples the utility of directed non-injective mappings between the individuals in the domains of multiple Information Sources.

Ontologies are often seen as basic building blocks for the Semantic Web, as they provide a reusable piece of knowledge about a specific domain. However, those pieces of knowledge are not static, but evolve over time. Domain changes, adaptations to different tasks, or changes in the conceptualization require modifications of the ontology. The evolution of ontologies causes operability problems, which will hamper their effective reuse. A versioning mechanism might help to reduce those problems, as it will make the relations between different revisions of an ontology explicit. This paper will discuss the problem of ontology versioning. Inspired by the work done in database schema versioning and program interface versioning, it will also propose building blocks for the most important aspects of a versioning mechanism, i.e., ontology identification and change specification.

this paper requires training examples. The assistance in their creation is necessary as in a typical ontology alignment setting there are only a small number of really plausible alignments available compared to the large number of candidates, which might be possible a priori

. Electronic B2B marketplaces bring together many online suppliers and buyers, each of which can potentially use his own format to represent the products in his product catalog. The marketplaces have to perform non-trivial mappings of these catalogs. In this paper, we analyze the problems which occur during the integration, taking several leading XML-based standards as an example. We advocate a three-layer product integration framework to resolve the difficulties in overcoming these problems with a direct one-layer integration. In this paper, we focus on the first two layers: the XML-based syntax layer and the data models layer expressed in RDF. The approach operates in three main steps. First, we create an RDF data model from the XML catalog, which eliminates all syntactical peculiarities of the catalog. Second, the catalog is translated from the source model to the RDF model of the target catalog. Finally, the transformation from RDF to XML restores all syntactical regulations required by the target catalog format. The approach is suitable for inter-operation with higher-level document and workflow ontologies. 1

Personalized access and content syndication involving diverse conceptual representations of information resources are two of the key challenges of real-scale Semantic Web (SW) applications, such as eCommerce, e-Learning or e-Science portals. RDF/S represents nowadays the core SW language for creating and exchanging resource descriptions worldwide. Unfortunately, full-fledged view definition languages for the RDF/S data model are still missing. We propose RVL, a view definition language capable of creating not only virtual resource descriptions, but also virtual RDF/S schemas from (meta)classes, properties, as well as, resource descriptions available on the Semantic Web. RVL exploits the functional nature and type system of the RQL query language in order to navigate, filter and restructure complex RDF/S schema and resource description graphs.

Currently, computers are changing from single, isolated devices into entry points to a worldwide network of information exchange and business transactions called the World Wide Web (WWW). For this reason, support in data, information, and knowledge exchange has become a key issue in current computer technology. The success of the WWW has made it increasingly difficult to find, access, present, and maintain the information required by a wide variety of users. In response to this problem, many new research initiatives and commercial enterprises have been set up to enrich available information with machine processable semantics. This semantic web will provide intelligent access to heterogeneous, distributed information, enabling software products (agents) to mediate between user needs and the information sources available. This paper summarizes ongoing research in the area of the semantic web, focusing especially on ontology technology.

The appearance of a large number of ontology tools may leave a user looking for an appropriate tool overwhelmed and uncertain on which tool to choose. Thus evaluation and comparison of these tools is important to help users determine which tool is best suited for their tasks. However, there is no "one size fits all" comparison framework for ontology tools: di#erent classes of tools require very di#erent comparison frameworks. For example, ontology-development tools can easily be compared to one another since they all serve the same task: define concepts, instances, and relations in a domain. Tools for ontology merging, mapping, and alignment however are so di#erent from one another that direct comparison may not be possible. They di#er in the type of input they require (e.g., instance data or no instance data), the type of output they produce (e.g., one merged ontology, pairs of related terms, articulation rules), modes of interaction and so on. This diversity makes comparing the performance of mapping tools to one another largely meaningless.