Towards a unified methodology for supporting the integration of data sources for use in web applications

Abstract

Organisations are making increasing use of web applications and web-based systems as an integral part of providing services. Examples include personalised dynamic user content on a website, social media plug-ins or web-based mapping tools. For these types of applications to have maximum use for the user where the applications are fully functional, they require the integration of data from multiple sources. The focus of this thesis is in improving this integration process with a focus on web applications with multiple sources of data. Integration of data from multiple sources is problematic for many reasons. Current integration methods tend to be domain specific and application specific. They are often complex, have compatibility issues with different technologies, lack maturity, are difficult to re-use, and do not accommodate new and emerging models and integration technologies. Technologies to achieve integration, such as brokers and translators do exist, but they cannot be used as a generic solution for developing web-applications achieving the integration outcomes required for successful web application development due to their domain specificity. It is because of these difficulties with integration, and the wide variety of integration approaches that there is a need to provide assistance to the developer in selecting the integration approach most appropriate to their needs. This thesis proposes GIWeb, a unified top-down data integration methodology instantiated with a framework that will aid developers in their integration process. It will act as a conceptual structure to support the chosen technical approach. The framework will assist in the integration of data sources to support web application builders. The thesis presents the rationale for the need for the framework based on an examination of the range of applications, associated data sources and the range of potential solutions. The framework is evaluated using four case studies

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