Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.

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A survey of approaches to automatic schema matching

An Introduction to MultiAgent Systems.

From the Publisher:
An agent is an entity with domain knowledge, goals and actions. Multi-agent systems are a set of agents which
interact in a common environment. Multi-agent systems deal with the construction of complex systems involving multiple agents and their coordination. A multi-agent system (MAS) is a distributed computing system with
autonomous interacting intelligent agents that coordinate their actions so as to achieve its goal(s) jointly or competitively.

Introduction to Multiagent Systems

Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. The problem of designing data integration systems is important in current real world applications, and is characterized by a number of issues that are interesting from a theoretical point of view. This document presents on overview of the material to be presented in a tutorial on data integration. The tutorial is focused on some of the theoretical issues that are relevant for data integration. Special attention will be devoted to the following aspects: modeling a data integration application, processing queries in data integration, dealing with inconsistent data sources, and reasoning on queries.

/pdf/data-integration-a-theoretical-perspective-58aesjvhuk.pdf

Data integration: a theoretical perspective

Ontologies tend to be found everywhere. They are viewed as the silver bullet for many applications, such as database integration, peer-to-peer systems, e-commerce, semantic web services, or social networks. However, in open or evolving systems, such as the semantic web, different parties would, in general, adopt different ontologies. Thus, merely using ontologies, like using XML, does not reduce heterogeneity: it just raises heterogeneity problems to a higher level. Euzenat and Shvaikos book is devoted to ontology matching as a solution to the semantic heterogeneity problem faced by computer systems. Ontology matching aims at finding correspondences between semantically related entities of different ontologies. These correspondences may stand for equivalence as well as other relations, such as consequence, subsumption, or disjointness, between ontology entities. Many different matching solutions have been proposed so far from various viewpoints, e.g., databases, information systems, and artificial intelligence. The second edition of Ontology Matching has been thoroughly revised and updated to reflect the most recent advances in this quickly developing area, which resulted in more than 150 pages of new content. In particular, the book includes a new chapter dedicated to the methodology for performing ontology matching. It also covers emerging topics, such as data interlinking, ontology partitioning and pruning, context-based matching, matcher tuning, alignment debugging, and user involvement in matching, to mention a few. More than 100 state-of-the-art matching systems and frameworks were reviewed. With Ontology Matching, researchers and practitioners will find a reference book that presents currently available work in a uniform framework. In particular, the work and the techniques presented in this book can be equally applied to database schema matching, catalog integration, XML schema matching and other related problems. The objectives of the book include presenting (i) the state of the art and (ii) the latest research results in ontology matching by providing a systematic and detailed account of matching techniques and matching systems from theoretical, practical and application perspectives.

Ontology Matching

Providing an integrated access to multiple heterogeneous sources is a challenging issue in global information systems for cooperation and interoperability. In this context, two fundamental problems arise. First, how to determine if the sources contain semantically related information, that is, information related to the same or similar real-world concept(s). Second, how to handle semantic heterogeneity to support integration and uniform query interfaces. Complicating factors with respect to conventional view integration techniques are related to the fact that the sources to be integrated already exist and that semantic heterogeneity occurs on the large-scale, involving terminology, structure, and context of the involved sources, with respect to geographical, organizational, and functional aspects related to information use. Moreover, to meet the requirements of global, Internet-based information systems, it is important that tools developed for supporting these activities are semi-automatic and scalable as much as possible.The goal of this paper is to describe the MOMIS [4, 5] (Mediator envirOnment for Multiple Information Sources) approach to the integration and query of multiple, heterogeneous information sources, containing structured and semistructured data. MOMIS has been conceived as a joint collaboration between University of Milano and Modena in the framework of the INTERDATA national research project, aiming at providing methods and tools for data management in Internet-based information systems. Like other integration projects [1, 10, 14], MOMIS follows a “semantic approach” to information integration based on the conceptual schema, or metadata, of the information sources, and on the following architectural elements: i) a common object-oriented data model, defined according to the ODLI3 language, to describe source schemas for integration purposes. The data model and ODLI3 have been defined in MOMIS as subset of the ODMG-93 ones, following the proposal for a standard mediator language developed by the I3/POB working group [7]. In addition, ODLI3 introduces new constructors to support the semantic integration process [4, 5]; ii) one or more wrappers, to translate schema descriptions into the common ODLI3 representation; iii) a mediator and a query-processing component, based on two pre-existing tools, namely ARTEMIS [8] and ODB-Tools [3] (available on Internet at http://sparc20.dsi.unimo.it/), to provide an I3 architecture for integration and query optimization. In this paper, we focus on capturing and reasoning about semantic aspects of schema descriptions of heterogeneous information sources for supporting integration and query optimization. Both semistructured and structured data sources are taken into account [5]. A Common Thesaurus is constructed, which has the role of a shared ontology for the information sources. The Common Thesaurus is built by analyzing ODLI3 descriptions of the sources, by exploiting the Description Logics OLCD (Object Language with Complements allowing Descriptive cycles) [2, 6], derived from KL-ONE family [17]. The knowledge in the Common Thesaurus is then exploited for the identification of semantically related information in ODLI3 descriptions of different sources and for their integration at the global level. Mapping rules and integrity constraints are defined at the global level to express the relationships holding between the integrated description and the sources descriptions. ODB-Tools, supporting OLCD and description logic inference techniques, allows the analysis of sources descriptions for generating a consistent Common Thesaurus and provides support for semantic optimization of queries at the global level, based on defined mapping rules and integrity constraints.

Semantic integration of semistructured and structured data sources

Developing intelligent tools for the integration of information extracted from multiple heterogeneous sources is a challenging issue to effectively exploit the numerous sources available on-line in global information systems. In this paper, we propose intelligent, tool-supported techniques to information extraction and integration from both structured and semistructured data sources. An object-oriented language, with an underlying Description Logic, called ODLI3, derived from the standard ODMG is introduced for information extraction. ODLI3 descriptions of the source schemas are exploited first to set a Common Thesaurus for the sources. Information integration is then performed in a semiautomatic way by exploiting the knowledge in the Common Thesaurus and ODLI3 descriptions of source schemas with a combination of clustering techniques and Description Logics. This integration process gives rise to a virtual integrated view of the underlying sources for which mapping rules and integrity constraints are specified to handle heterogeneity. Integration techniques described in the paper are provided in the framework of the MOMIS system based on a conventional wrapper/mediator architecture.

Semantic integration of heterogeneous information sources

Intelligent Information Agents

Taxonomic reasoning is a typical task performed by many AI knowledge representation systems In this paper, the effectiveness of taxonomic reasoning techniques as an active support to knowledge acquisition and conceptual schema design is shown The idea developed is that by extending conceptual models with defined concepts and giving them rigorous logic semantics, it is possible to infer isa relationships between concepts on the basis of their descriptions From a theoretical point of view, this approach makes it possible to give a formal definition for consistency and minimality of a conceptual schema From a pragmatic point of view it is possible to develop an active environment that allows automatic classification of a new concept in the right position of a given taxonomy, ensuring the consistency and minimality of a conceptual schema A formalism that includes the data semantics of models giving prominence to type constructors (E/R, TAXIS, GALILEO) and algorithms for taxonomic inferences are presented: their soundness, completeness, and tractability properties are proved Finally, an extended formalism and taxonomic inference algorithms for models giving prominence to attributes (FDM, IFO) are given

On taxonomic reasoning in conceptual design

Invited Paper.- Information Flow Analysis in Autonomous Agent and Peer-to-Peer Systems for Self-organizing Electronic Health Records.- P2P Infrastructure.- Hybrid DHT Design for Mobile Environments.- DANTE: A Self-adapting Peer-to-Peer System.- The Exclusion of Malicious Routing Peers in Structured P2P Systems.- Agents in P2P.- Cooperative CBR System for Peer Agent Committee Formation.- Mobile Agent-Based Approach for Resource Discovery in Peer-to-Peer Networks.- P2P Search.- Chora: Expert-Based P2P Web Search.- K-link: A Peer-to-Peer Solution for Organizational Knowledge Management.- An Analysis of Interest-Community Facilitated Peer-to-Peer Search.- Applications.- Mitigating the Impact of Liars by Reflecting Peer's Credibility on P2P File Reputation Systems.- A Comparative Study of Reasoning Techniques for Service Selection.- PROSA: P2P Resource Organisation by Social Acquaintances.- Reliable P2P File Sharing Service.- Studying Viable Free Markets in Peer-to-Peer File Exchange Applications without Altruistic Agents.- Distributed Multi-layered Network Management for NEC Using Multi-Agent Systems.- Facilitating Collaboration in a Distributed Software Development Environment Using P2P Architecture.- A Peer to Peer Grid Computing System Based on Mobile Agents.

Sonia Bergamaschi

Papers

Semantic integration of semistructured and structured data sources

Semantic integration of heterogeneous information sources

Intelligent Information Agents

On taxonomic reasoning in conceptual design

Agents and Peer-to-Peer Computing