Ontology Based Integration of Distributed and Heterogeneous Data Sources in ACGT.

In this work, we describe the set of tools comprising the Data Access Infrastructure within Advancing Clinic-genomic Trials on Cancer (ACGT), a R&D Project funded in part by the European. This infrastructure aims at improving Post-genomic clinical trials by providing seamless access to integrated clinical, genetic, and image databases. A data access layer, based on OGSA-DAI, has been developed in order to cope with syntactic heterogeneities in databases. The semantic problems present in data sources with different nature are tackled by two core tools, namely the Semantic Mediator and the Master Ontology on Cancer. The ontology is used as a common framework for semantics, modeling the domain and acting as giving support to homogenization. SPARQL has been selected as query language for the Data Access Services and the Mediator. Two experiments have been carried out in order to test the suitability of the selected approach, integrating clinical and DICOM image databases

Application of ESE Data and Tools to Air Quality Management: Services for Helping the Air Quality Community use ESE Data (SHAirED)

The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. Its scope falls within the domain of air quality management and aims to develop a federated air quality information sharing network that includes data from NASA, EPA, US States and others. Project goals were achieved through a access of satellite and ground observation data, web services information technology, interoperability standards, and air quality community collaboration. In contributing to a network of NASA ESE data in support of particulate air quality management, the project will develop access to distributed data, build Web infrastructure, and create tools for data processing and analysis. The key technologies used in the project include emerging web services for developing self describing and modular data access and processing tools, and service oriented architecture for chaining web services together to assemble customized air quality management applications. The technology and tools required for this project were developed within DataFed.net, a shared infrastructure that supports collaborative atmospheric data sharing and processing web services. Much of the collaboration was facilitated through community interactions through the Federation of Earth Science Information Partners (ESIP) Air Quality Workgroup. The main activities during the project that successfully advanced DataFed, enabled air quality applications and established community-oriented infrastructures were: develop access to distributed data (surface and satellite), build Web infrastructure to support data access, processing and analysis create tools for data processing and analysis foster air quality community collaboration and interoperability

Database Integration: the Key to Data Interoperability

Most of new databases are no more built from scratch, but re-use existing data from several autonomous data stores. To facilitate application development, the data to be re-used should preferably be redefined as a virtual database, providing for the logical unification of the underlying data sets. This unification process is called database integration. This chapter provides a global picture of the issues raised and the approaches that have been proposed to tackle the problem

The mediated data integration (MeDInt) : An approach to the integration of database and legacy systems

The information required for decision making by executives in organizations is normally scattered across disparate data sources including databases and legacy systems. To gain a competitive advantage, it is extremely important for executives to be able to obtain one unique view of information in an accurate and timely manner. To do this, it is necessary to interoperate multiple data sources, which differ structurally and semantically. Particular problems occur when applying traditional integration approaches, for example, the global schema needs to be recreated when the component schema has been modified. This research investigates the following heterogeneities between heterogeneous data sources: Data Model Heterogeneities, Schematic Heterogeneities and Semantic Heterogeneities. The problems of existing integration approaches are reviewed and solved by introducing and designing a new integration approach to logically interoperate heterogeneous data sources and to resolve three previously classified heterogeneities. The research attempts to reduce the complexity of the integration process by maximising the degree of automation. Mediation and wrapping techniques are employed in this research. The Mediated Data Integration (MeDint) architecture has been introduced to integrate heterogeneous data sources. Three major elements, the MeDint Mediator, wrappers, and the Mediated Data Model (MDM) play important roles in the integration of heterogeneous data sources. The MeDint Mediator acts as an intermediate layer transforming queries to sub-queries, resolving conflicts, and consolidating conflict-resolved results. Wrappers serve as translators between the MeDint Mediator and data sources. Both the mediator and wrappers arc well-supported by MDM, a semantically-rich data model which can describe or represent heterogeneous data schematically and semantically. Some organisational information systems have been tested and evaluated using the MeDint architecture. The results have addressed all the research questions regarding the interoperability of heterogeneous data sources. In addition, the results also confirm that the Me Dint architecture is able to provide integration that is transparent to users and that the schema evolution does not affect the integration

An Object-Oriented Heterogeneous Database Architecture

Many data management environments face a critical need to integrate heterogeneous data-data that are stored in varying locations using various data management systems with diverse data formats and schemas. To address this problem, the database research community has developed the concept of a heterogeneous database system (HDB) that provides users with the illusion of a single unified database. However, HDBs rely on the implicit assumption that all data to be integrated into the HDB are stored in full-fledged database management systems (DBMS). This assumption leaves environments that need to integrate non-DBMS data unserved by HDB systems. Furthermore, HDBs are complex software solutions that are not easily lmplementable by database developers wrestling with heterogeneous data. This thesis presents a new, easily implemented HDB architecture that is suitable for integrating non-DBMS data. The key to our architecture is using an object-oriented database management system (OODBMS) as an implementation tool. Rather than developing an HDB from scratch, we leverage the power and facilities of the underlying OODBMS to provide a query language, application programmer interface, interactive query interface, concurrency control, etc. Using object-oriented technology gives us an additional benefit-our HDB becomes an object-oriented HDB (OOHDB) providing users with greater data model expressivity along with a powerful behavioral component. The OOHDB architecture we present is independent of a particular OODBMS and can be implemented using a number of commercial OODBMSs for a variety of data management environments. We describe one implementation of our architecture using the GemStone OODBMS for accessing heterogeneous materials science data. This implementation demonstrates how easily the architecture can be implemented. We use this implementation to analyze the performance of the architecture and examine the effectiveness of strategies for enhancing performance. We conclude that for many environments with heterogeneous non-DBMS data, our OOHDB architecture provides a good solution that is easy to implement using commercial OODBMS technology

MONIL Language, an Alternative for Data Integration El Lenguaje MONIL, una Alternativa para la Integración de Datos

Abstract Data integration is a process of retrieving, merging and storing of data originated in heterogeneous sources of data. The main problem facing the data integration is the structural and semantic heterogeneity of participating data. A concern of research communities in computer sciences is the development of semi-automatic tools to assist the user in an effective way in the data integration processes. This paper introduces a programming language called MONIL, as an alternative to integrate data by means of design, storage and program execution. MONIL is based on the use of meta-data, conversion functions, a meta-model of integration and a scheme of integration suggestions. MONIL offers to the user a dedicated work environment with built-in semi-automatic tools supporting the integration process in three stages. Keywords: data integration, integration language, databases, metadata. Resumen La integración de datos es el proceso de extracción, mezcla y almacenamiento de datos provenientes de fuentes de datos heterogéneas. El problema principal que enfrenta la integración de datos es la heterogeneidad estructural y semántica de los datos que participan. Una preocupación en las comunidades de investigación de las ciencias computacionales, es el desarrollo de herramientas semiautomáticas que asistan a los usuarios de forma efectiva en los procesos de integración de datos. Este artículo presenta un lenguaje de programación llamado MONIL, como una alternativa para integrar datos mediante el diseño, almacenamiento y ejecución de programas. MONIL está basado en el uso de metadatos, funciones de conversión, un metamodelo de integración y un esquema de sugerencias de integración. MONIL ofrece al usuario un ambiente de trabajo dedicado con herramientas semiautomáticas integradas y que soportan un proceso de integración en tres etapas. Palabras claves: integración de datos, lenguaje de integración, bases de datos, bodegas de datos, metadatos

Dagstuhl News January - December 1999

"Dagstuhl News" is a publication edited especially for the members of the Foundation "Informatikzentrum Schloss Dagstuhl" to thank them for their support. The News give a summary of the scientific work being done in Dagstuhl. Each Dagstuhl Seminar is presented by a small abstract describing the contents and scientific highlights of the seminar as well as the perspectives or challenges of the research topic

The impact of globalization on Maasai culture : with special focus on the Ilmuran age-group

Master's thesis in global studies. School of Mission and Theology, May 201