CAMDIT: A Toolkit for Integrating Heteregeneous Data for Enhanced Service Provisioning

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dc.contributor.authorIpadeola, A
dc.contributor.authorIpadeola, O
dc.contributor.authorAmeen, Ahmed O
dc.contributor.authorSadiku, Joseph S
dc.date.accessioned2018-08-14T09:09:17Z
dc.date.available2018-08-14T09:09:17Z
dc.date.issued2014-11-03
dc.descriptionData Integration refers to the problem of combining data residing at different sources, and providing the user with a unified view of these data. Data Integration dates back to 1960 when a need arose to achieve data morphing from disparate sources otherwise called unified central data view. In essence, the rapid adoption of databases after the 1960s naturally led to the need to share or merge existing repositories. This merging can take place at several levels in the database architecture. Data morphing or integration is a rising pursuit amongst researchers and industrialist as the need to share data explodes by the day. Another source mentioned that the ambition of integrating disparate data sources is an essential focus of extensive theoretical work, and numerous open problems still appearing unsolved [3]. Moreen_US
dc.description.abstractData Integration is classified as an Open and Lingering (OL) problem which must be sufficiently addressed due to its myriad benefits and significances, especially in the health sector where collaborative medicine is vital. Data integration problem evolved from the disparity in semantics and syntactic representations of medical data. It is a challenge, which must be solved to realize effective collaboration in the health sector and paramount for efficient health care service provisioning. In recent times, different approaches and software artifacts such as services, components and tools have been proposed for resolving data integration problem. However, existing approaches are faced with data inaccuracy, data unreliability, increased query response time, network bottleneck and poor system performance. The focus of this paper is to present our technique and the CAMDIT toolkit which efficiently achieves data integration, data accuracy, reliability and reduced query-response time and impacts of network bottleneck on systems performances.Data Integration is classified as an Open and Lingering (OL) problem which must be sufficiently addressed due to its myriad benefits and significances, especially in the health sector where collaborative medicine is vital. Data integration problem evolved from the disparity in semantics and syntactic representations of medical data. It is a challenge, which must be solved to realize effective collaboration in the health sector and paramount for efficient health care service provisioning. In recent times, different approaches and software artifacts such as services, components and tools have been proposed for resolving data integration problem. However, existing approaches are faced with data inaccuracy, data unreliability, increased query response time, network bottleneck and poor system performance. The focus of this paper is to present our technique and the CAMDIT toolkit which efficiently achieves data integration, data accuracy, reliability and reduced query-response time and impacts of network bottleneck on systems performances.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1124
dc.language.isoenen_US
dc.publisherIEEE Internationalen_US
dc.subjectHeteregeneousen_US
dc.subjectData Integrationen_US
dc.subjectData Warehouseen_US
dc.titleCAMDIT: A Toolkit for Integrating Heteregeneous Data for Enhanced Service Provisioningen_US
dc.typeArticleen_US

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Three (3) prevailing approaches are adopted for integrating heterogeneous databases, and they include the Data-warehouse approach, Middleware approach and the Federated approach . All of these approaches have sets of unique advantages and disadvantages in data integration and morphing.
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