Large IS shops often work with three or more generations of database technology. It is very common to find some pilot projects, using object technology while the mass of software is still being produced using 3GL technologies and relational databases. Parallel to this application portfolio, older applications have to be maintained. These applications often use hierarchical or even older databas...

The BioDA project is investigating how Bioinformatics GRIDs, a data and compute intensive domain, could benefit from using a standard framework, such as OGSA-DAI, to manage access to, and integration of, distributed heterogeneous data resources. In this paper, we outline the common data access and integration requirements from the bioinformatics community. We then highlight some specific issues...

Many bioinformatics applications require data from different sources to answer complex research questions. Integrating such highly diverse data is a major challenge in bioinformatics and often much too laborious and error-prone for scientists. Traditional integration approaches like data warehousing and mediators are often applicable but also time consuming to develop, to deploy and hard to mai...

Pharmaceutical R&D organizations have no shortage of experimental data or annotation information. However, the sheer volume and complexity of this information results in a paralyzing inability to make effective use of it for predicting drug efficacy and safety. Data integration efforts are legion, but even in the rare instances where they succeed, they are found to be insufficient to advance pr...

abstract this study investigates casual relationship between co2 emission and gross domestic product per capita in five different country groups, using cross- country data for the period 1960-2007. to achieve the purpose, the co- integration test and error correction models are applied. results confirm casual relationships between the two variables. a unilateral relationship between gdp and co2...

The fact that many decisions need a combination of information sources makes easy integration of geospatial data an important data usability issue. Our vision is to achieve automated just-in-time integration. As a foundation, we present a system architecture with distributed data and services. Existing and evolving standards and technologies fitting into this architecture are presented along wi...

Various XML instances from different data sources can model the same object of the real world. Query processing or view definition over these sources demands instance integration. In this context, integration means to identify which data instances represent the same object of the real world, as well as to solve ambiguities of representation of this object. The entity identification problem in X...

Today’s fast and continuous growth of large business organizations enforces an increasing need in integrating and sharing large amounts of data, coming from a number of heterogeneous and distributed data sources. Thus, during the last decade, research and business community interest has migrated from DataBase Management Systems (DBMS) to data integration systems. Whereas the former make a uniqu...

Data integration systems harmonize data from multiple sources into a single coherent representation. The goal is to provide an integrated view over all the data sources of interest and to provide a uniform interface to access all of these data. The access to the integrated data is usually in the form of querying rather than updating the data. The data sources to be integrated may belong to the ...