Data Integration in Distributed Databases

Information Systems Technology and Its Applications, 2001

Nowadays, a central topic in database science is the need of an integrated access to large amounts of data provided by various information sources whose contents are strictly related. Often information sources have been designed independently for autonomous applications, so they may present several kinds of heterogeneity. Particularly hard to manage is the semantic heterogeneity, which is due to schema and value inconsistencies. In this paper, we focus our attention mainly on the inconsistency which arises when conflicting instances related to the same concept and possibly coming from different sources are integrated. First, we introduce an operator, called Merge Operator, which allows us to combine data coming from different sources, preserving the information contained in each of them. Then, we present a variant of this operator, the Extended Merge Operator, which associates the integrated data with some information about the process by which they have been obtained. Finally, in order to manage conflicts among integrated data, we briefly present a technique for computing consistent answers over inconsistent databases.

2009

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.

2017

In the frame of an extensible canonical data model a formalization of data integration concept is proposed. We provide virtual and materialized integration of data as well as the possibility to support data cubes with hierarchical dimensions. The considered approach of formalization of data integration concept is based on the so-called content dictionaries. Namely, by means of these dictionaries we are formally defining basic concepts of database theory, metadata about these concepts, and the data integration concept. A computationally complete language is used to extract data from several sources, to create the materialized view, and to effectively organize queries on the multidimensional data. In memory of Garush Manukyan, my father. This work was supported by the RA MES State Committee of Science, in the frames of the research project N 15T-18350.

1996

This paper presents a framework for data integration currently under development in the Squirrel project. The framework is based on a special class of mediators, called Squirrel integration mediators. These mediators can support the traditional virtual and materialized approaches, and also hybrids of them. This permits considerable exibility when adapting to diverse data integration environments.

International Congress on Data Mining and Information Systems, ICDIS 2007, 2007

There is an abundance of information spread across the world, usually stored in databases or published as web pages. These data is not structured in a common way, because the sources were built to fill different purposes or they were made by different persons. Presently, if a user wants to exploit data coming simultaneously from diverse data sources and obtain useful results, he must combine all disperse pieces of relevant data and check the correspondence between them, regularly by hand. In this research we propose the development of a database integration system (DaBIS) with the following features: 1) it allows many connections with remote and heterogeneous databases to extract their constitutive schemas; 2) it makes inferences about the data of each database, using matching algorithms to produce useful correspondences; and 3) it solves a user’s global queries by means of a graphical interface, when the query involves diverse information sources. Our main idea is to combine in a semiautomatic way partial results obtained from distinct databases, and get relevant results, while, at the same time, simplify the formulation of difficult queries. """

2007

Proceedings of the tenth international conference on Information and knowledge management, 2001

The need for interoperability among databases has increased dramatically with the proliferation of readily available DBMS and application software. Even within a single organization, data from disparate relational databases must be integrated. A framework for interoperability in a federated system of relational databases should be inherently relational, so that it can use existing techniques for query evaluation and optimization where possible and retain the key features of SQL, such as a modest complexity and ease of query formulation. Our contribution is a LOGSPACE relational algebra, the Meta-Algebra (MA), for data/metadata integration among relational databases containing semantically similar information in schematically disparate formats. The MA is a simple yet powerful extension of the classical relational algebra (RA). The MA has a natural declarative counterpart, the Meta-Query Language (MQL), which we briefly describe. We state a result showing MQL and the MA are computationally equivalent, which enables us to algebratize MQL queries in fundamentally the same way as ordinary SQL queries. This algebratization in turn enables us to use MA equivalences to facilitate the application of known query optimization techniques to MQL query evaluation.

Open Computer Science, 2015

Integrating heterogeneous data in distributed databases has been a research issue for many years. In this paper, we discuss some of these problems and propose a solution using a semantic model. This semantic model is built upon the semantic relationships between existing data. Applying these semantics enables us to take into account different dimensions of user queries and find the best possible answer for them. The proposed approach leads us to introducing…

Proceedings of the …, 1999

Integration is one of the most important aspects of a Data Warehouse. When data passes from the sources of the application-oriented operational environment to the Data Warehouse, possible inconsistencies and redundancies should be resolved, so that the warehouse is able to provide an integrated and reconciled view of data of the organization. We describe a novel approach to data integration and reconciliation, based on a conceptual representation of the Data Warehouse application domain. The main idea is to declaratively specify suitable matching, conversion, and reconciliation operations to be used in order to solve possibile conflicts among data in different sources. Such a specification is provided in terms of the conceptual model of the application, and is effectively used during the design of the software modules that load the data from the sources into the Data Warehouse.