Back to results

London Metropolitan University

Mapping relational databases to semantic web using domain-specific knowledge

Abstract

dc:description.abstract

Semantic Web is a framework which allows information to be represented not only syntactically using suitable structural definitions ("data schema"), specific instances of them ("data") and their use ("access rights"), but also semantically using a logical model which allows formal interpretation and sound logical inferencing about the information ("knowledge"). Relational models are limited to the interpretation of purely relational data and do not provide sufficiently rich means for interpreting the knowledge associated with the use of the data. Relational languages lack the expressiveness to represent imprecise, uncertain, partially true and approximate knowledge (Sheth, Ramakrishnan, & Thomas, Semantics for the Semantic Web: The Implicit, the Formal and the Powerful , 2005). This lack of capability to represent and process knowledge while it is still in a relational model is the trigger for this research project's initiative. This research project focuses on the mapping of the relational data stored in a database to an ontological repository as a step towards representing and processing the knowledge on the Web. (Introduction, pages 10-11).

Degree

thesis:*
Name dc:type.qualificationname
phd
Level dc:type.qualificationlevel
doctoral
Grantor dc:publisher.institution
London Metropolitan University
Year dc:date.issued
2014

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Mallede, Wondimagegn Yalew

Subjects

dc:subject × 1

Identifiers

dc:identifier.*
Dc Identifier Grantnumber
N/A
OAI identifier oai:identifier
oai:repository.londonmet.ac.uk:7370

Chain of custody

source
Harvested from
London Metropolitan University
Base URL
repository.londonmet.ac.uk/cgi/oai2
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Mallede, Wondimagegn Yalew. Mapping relational databases to semantic web using domain-specific knowledge. doctoral thesis, London Metropolitan University, 2014.