Model Theoretic Semantics for Information Integration

During the last years a lot of projects and lines of research have emerged from different proposals trying to find the best way to reach data integration. Two powerful techniques have appeared separately -ontology and contextual information -in order to help solve semantic heterogeneity problems. In our proposal we combine both techniques exploiting the advantages of each of them. We propose a new approach, in which three main components work together in order to achieve a consistent integration. Each component contains some type of semantic information modeled by ontologies and contexts. Our approach helps the building of each of the components and address other types of heterogeneity such as ontological heterogeneity.

PRINCIPLES OF …, 1998

Information Integration is one of the core problems in distributed databases, cooperative information systems, and data warehousing, which are key areas in the software development industry. Two critical factors for the design and maintenance of applications requiring Information Integration are conceptual modeling of the domain, and reasoning support over the conceptual representation. We demonstrate that Knowledge Representation and Reasoning techniques can play an important role for both of these factors, by proposing a Description Logic based framework for Information Integration. We show that the development of successful Information Integration solutions requires not only to resort to very expressive Description Logics, but also to signi cantly extend them. We present a novel approach to conceptual modeling for Information Integration, which allows for suitably modeling the global concepts of the application, the individual information sources, and the constraints among di erent sources. Moreover, we devise inference procedures for the fundamental reasoning services, namely relation and concept subsumption, and query containment. Finally, we present a methodological framework for Information Integration, which can be applied in several contexts, and highlights the role of reasoning services within the design process.

2007 International Conference on Computing: Theory and Applications (ICCTA'07), 2007

The Web is replete with databases, many of which are modeled on the relational paradigm. Currently, for the purpose of simultaneous querying data from multiple databases, the federated database technique is used extensively. However, the effectiveness of such a technique is suspect when it comes to querying heterogeneous databases. Therefore, it becomes imperative to develop an efficient methodology for the semantic integration of heterogeneous online databases. This may be realized by defining a mapping from a relational database to a description that utilises the Resource Description Framework (RDF). Such a representation would be machine processable and would make the semantics as expressed by databases more explicit and, thereby, facilitate their integration.

2002

Information integration is the problem of combining the data residing at different, heterogeneous sources, and providing the user with a unified view of these data, called mediated schema. The mediated schema is therefore a reconciled view of the information, which can be queried by the user. It is the task of the system to free the user from the knowledge on where data are, and how data are structured at the sources.

This paper describes an approach to knowledge representation which combines the use of partial models in model-theoretic semantics with that of structured collections of data bases. The approach is described in detail for a very simple case, viz. where a data base is viewed as consisting of atomic, unstructured facts, as in the modeltheoretic interpretation of propositional logic. This logic is enriched with propositional attitude operators for dealing with the knowledge of two agents in intelligent communication. The attitudes are interpreted formally in terms of relations between partial submodels, corresponding in an implementation to the topology of a network of small data bases. Contents 1 Knowledge representation and data bases 2 Difíiculties with a multi-data base approach 3 Nonlocal evaluation and interactions between data modules 2 4 7 4 Multiple data bases as partial models 10

Journal of Computer Science and Technology - JCST

The term "Federated Databases" refers to the data integration of distributed, autonomous and heterogeneous databases. However, a federation can also include information systems, not only databases. At integrating data, several issues must be addressed. Here, we focus on the problem of heterogeneity, more specifically on semantic heterogeneity - that is, problems rela ted to semantically equivalent concepts or semantically related/unrelated concepts. In order to address this problem, we apply the idea of ontologies as a tool for data integration. In this paper, we explain this concept and we briefly describe a method for constructing an ontology by using a hybrid ontology approach.

Lecture Notes in Computer Science, 2009

The goal of data integration is to provide a uniform access to a set of heterogeneous data sources, freeing the user from the knowledge about where the data are, how they are stored, and how they can be accessed. One of the outcomes of the research work carried out on data integration in the last years is a clear architecture, comprising a global schema, the source schema, and the mapping between the source and the global schema. Although in many research works and commercial tools the global schema is simply a data structure integrating the data at the sources, we argue that the global schema should represent, instead, the conceptual model of the domain. However, to fully pursue such an approach, several challenging issues are to be addressed. The main goal of this paper is to analyze one of them, namely, how to express the conceptual model representing the global schema. We start our analysis with the case where such a schema is expressed in terms of a UML class diagram, and we end up with a proposal of a particular Description Logic, called DL-Lite A,id. We show that the data integration framework based on such a logic has several interesting properties, including the fact that both reasoning at design time, and answering queries at run time can be done efficiently.

Integrating data from a Federated System is a very complex process that involves a series of tasks. Characteristics such as autonomy of the information sources, their geographical distribution and heterogeneity are some of the main problems we face to perform the integration. In this paper we focus on the problem of heterogeneity, more specifically on semantic heterogeneity. The semantic heterogeneity makes the integration difficult because of its bearing problems on synonymous, generalization/specialization, etc. Here, we briefly explain our three level approach to solve these problems. Then we show the structure of software components used to implement our supporting tool.

ACM SIGMOD Record

Semantic heterogeneity is one of the key challenges in integrating and sharing data across disparate sources, data exchange and migration, data warehous- ing, model management, the Semantic Web and peer- to-peer databases. Semantic heterogeneity can arise at the schema level ...