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.

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 semantic Web Services vision requires that each service be annotated with semantic metadata. Manually creating such metadata is tedious and error-prone, and many software engineers, accustomed to tools that automatically generate WSDL, might not want to invest the additional e#ort. We therefore propose ASSAM, a tool that assists a user in creating semantic metadata for Web Services. ASSAM is intended for service consumers who want to integrate a number of services and therefore must annotate them according to some shared ontology. ASSAM is also relevant for service producers who have deployed a Web Service and want to make it compatible with an existing ontology. ASSAM's capabilities to automatically create semantic metadata are supported by two machine learning algorithms. First, we have developed an iterative relational classification algorithm for semantically classifying Web Services, their operations, and input and output messages. Second, to aggregate the data returned by multiple semantically related Web Services, we have developed a schema mapping algorithm that is based on an ensemble of string distance metrics.

Electronic commerce lets people purchase goods and exchange information on business transactions on-line. Therefore one of the main challenges for the designers of the e-commerce infrastructures is the information sharing, retrieving data located in different sources thus obtaining an integrated view to overcome any contradiction or redundancy. Virtual Catalogs synthesize this approach as they are conceived as instruments to dynamically retrieve information from multiple catalogs and present product data in a unified manner, without directly storing product data from catalogs. In this paper we propose SI-Designer, a support tool for the integration of data from structured and semi-structured data sources, developed within the

A Data Integration System is constituted by three main components: source schemas, a global schema and a mapping between the two. There exist two main approaches for specifying the mapping: in the local-as-view (LAV) approach the source structures are de ned as views over the global schema; on the contrary in the global-as-view (GAV) approach each global concept is de ned in terms of a view over the source schemas. The problem of query processing is to nd ecient methods for answering queries posed to the global schema on the basis of the data stored at sources. In LAV there exist two approaches to query processing: by query rewriting, in which one tries to compute a rewriting of the query in terms of the views and then evaluates such a rewriting, and by query answering, in which one aims at directly answering the query based on the view extensions. In GAV, existing systems deal with query processing by simply unfolding each global concept in the query with its de nition in terms of the sources. In this paper, we survey the most important query processing algorithms proposed in the literature for LAV, and we describe the principal GAV data integration systems and the form of query processing they adopt.

Abstract. With new standards like RDF or OWL paving the way for the much anticipated Semantic Web, a new breed of very large scale semantic systems is about to appear. Traditional semantic reconciliation techniques, dependent upon shared vocabularies or global ontologies, cannot be used in such open and dynamic environments. Instead, new heuristics based on emerging properties and local consensuses have to be exploited in order to foster semantic interoperability in the large. In this paper, we outline the main differences between traditional semantic reconciliation methods and these new heuristics. Also, we characterize the resulting emergent semantics systems and provide a couple of hints vis-à-vis their potential applications. 1

alk, I will discuss the advantages and the challenges of using rich knowledge representation formalisms for modeling the semantic relationships between source schemas through a mediated schema. I will outline the impact of the choice of the knowledge representation formalism on the query reformulation problem, which is the core algorithmic problem for answering queries in an information integration system. Clearly, as the languages for describing data sources, the mediated schema, or the users' queries become more expressive, the query reformulation problem becomes harder. The key challenge is then to identify formalisms offering a reasonable tradeoff between expressive power and good computational properties for the accompanying reformulation algorithm. I will survey different tradeoffs made in several existing information integration sys- tems (e.g., TSIMMIS[3], Information Manifold[7], Infomaster[a], SIMS[l], OBSERVER [8],MOMIS[2]). I will mention in more details the approaches chos

Abstract. Providing an integrated access to multiple heterogeneous sources is a challenging issue in global information systems for cooperation and interoperability. In the past, companies have equipped themselves with data storing systems building up informative systems containing data that are related one another, but which are often redundant, not homogeneous and not always semantically consistent. Moreover, to meet the requirements of global, Internet-based information systems, it is important that the tools developed for supporting these activities are semi-automatic and scalable as much as possible. To face the issues related to scalability in the large-scale, in this paper we propose the exploitation of mobile agents in the information integration area, and, in particular, their integration in the MOMIS infrastructure. MOMIS (Mediator EnvirOnment for Multiple Information Sources) is a system that has been conceived as a pool of tools to provide an integrated access to heterogeneous information stored in traditional databases (for example relational, object oriented databases) or in file systems, as well as in semi-structured data sources (XML-file). This proposal has been implemented within the MIKS (Mediator agent for Integration of Knowledge Sources) system and it is completely described in this paper. 1

We discuss the issue of dealing with integrity constraints over the global schema in data integration. On the one hand, integrity constraints can be used to extract more information from incomplete sources, similarly to the case of databases with incomplete information. On the other hand, integrity constraints raise the problem of dealing with the inconsistency of the whole system, due to contradictory data at the sources. We also present a data integration system developed by taking into account such issues. 1

Abstract. The SEWASIE (SEmantic Webs and AgentS in Integrated