A semantic data federation engine : design, implementation & applications in educational information management

Abstract

With the advent of the World Wide Web, the amount of digital information in the world has increased exponentially. The ability to organize this deluge of data, retrieve it, and combine it with other data would bring numerous benefits to organizations that rely on the analysis of this data for their operations. The Semantic Web encompasses various technologies that support better information organization and access. This thesis proposes a data federation engine that facilitates integration of data across distributed Semantic Web data sources while maintaining appropriate access policies. After discussing existing literature in the field, the design and implementation of the system including its capabilities and limitations are thoroughly described. Moreover, a possible application of the system at the Massachusetts Department of Education is explored in detail, including an investigation of the technical and nontechnical challenges associated with its adoption at a government agency. By using the federation engine, users would be able to exploit the expressivity of the Semantic Web by querying for disparate data at a single location without having to know how it is distributed or where it is stored. Among this research's contributions to the fledgling Semantic Web are: an integrated system for executing SPARQL queries; and, an optimizer that faciliates efficient querying by exploiting statistical information about the data sources.