Use this URL to cite or link to this record in EThOS:
Title: Engineering a Semantic Web trust infrastructure
Author: Cobden, Marcus
ISNI:       0000 0004 5347 6280
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
The ability to judge the trustworthiness of information is an important and challenging problem in the field of Semantic Web research. In this thesis, we take an end-to-end look at the challenges posed by trust on the Semantic Web, and present contributions in three areas: a Semantic Web identity vocabulary, a system for bootstrapping trust environments, and a framework for trust aware information management. Typically Semantic Web agents, which consume and produce information, are not described with sufficient information to permit those interacting with them to make good judgements of trustworthiness. A descriptive vocabulary for agent identity is required to enable effective inter agent discourse, and the growth of trust and reputation within the Semantic Web; we therefore present such a foundational identity ontology for describing web-based agents. It is anticipated that the Semantic Web will suffer from a trust network bootstrapping problem. In this thesis, we propose a novel approach which harnesses open data to bootstrap trust in new trust environments. This approach brings together public records published by a range of trusted institutions in order to encourage trust in identities within new environments. Information integrity and provenance are both critical prerequisites for well-founded judgements of information trustworthiness. We propose a modification to the RDF Named Graph data model in order to address serious representational limitations with the named graph proposal, which affect the ability to cleanly represent claims and provenance records. Next, we propose a novel graph based approach for recording the provenance of derived information. This approach offers computational and memory savings while maintaining the ability to answer graph-level provenance questions. In addition, it allows new optimisations such as strategies to avoid needless repeat computation, and a delta-based storage strategy which avoids data duplication.
Supervisor: Gibbins, Nicholas Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QA76 Computer software