AbstractInformation technology plays an increasingly important part in representing, managing, and driving the field of sustainable energy. However, current paradigms for representing much of this information can be fragmented, singular, and extremely domain focused. Linkage with wider concepts, for example between energy supply and demand data, can be minimal. This
dissertation investigates ways in which such data linkages can be expanded upon, applying the latest concepts of Semantic Web technology to the area. This dissertation examines the role of the Semantic Web in representing information relevant to sustainable energy, with a particular focus on energy policy, energy supply, and the demands of the built environment.
An approach for representing such information is outlined in the dissertation, which introduces new ontologies for representing energy policy and building information data and methodologies for modelling such data. Existing ontologies for representing energy supply are discussed, as are common connections between these areas and a server platform for knowledge storage and presentation. Additionally, some focus is directed towards the
usability and accessibility of such data and the implementation of proof of concept applications targeted at specific areas within sustainable energy are presented.
Using the outlined approach, energy information can be interlinked to allow multi-level data navigation from international policy data, through energy infrastructure, to individual energy demands, and ultimately to extremely detailed building component levels of granularity. Such data can be interlinked into wider linked data initiatives, increasing usefulness and expanding
the scope for increased analysis. The implications of the outlined approach are discussed and evaluated with regard to various identified use cases requiring different levels of data granularity, in addition to impact on the wider domain of information management. This dissertation demonstrates, at a proof of concept level, that Semantic Web technology can be of significant benefit across the domain of sustainable energy.
|Date of Award||20 Mar 2012|
|Sponsors||ERDF & SUSPLAN|
|Supervisor||Neil Finlayson (Supervisor), Frank Rennie (Supervisor), Michael Kummert (Supervisor) & Sinclair Gair (Supervisor)|
- Semantic Web
- Sustainable Energy
- Information Technology
- Linked Data
- Built Environment
Murray, M. C. (Author). 20 Mar 2012
Student thesis: Doctoral Thesis › Doctor of Philosophy (awarded by OU/Aberdeen)