Trustworthiness assessment of knowledge on the semantic sensor web by provenance integration

Umuhoza, D; Braun, R

Trustworthiness assessment of knowledge on the semantic sensor web by provenance integration

Umuhoza, D Braun, R

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 26th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012, 2012, pp. 387 - 392
Issue Date:: 2012-05-14

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Field	Value	Language
dc.contributor.author	Umuhoza, D	en_US
dc.contributor.author	Braun, R https://orcid.org/0000-0002-4153-8769	en_US
dc.date.issued	2012-05-14	en_US
dc.identifier.citation	Proceedings - 26th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012, 2012, pp. 387 - 392	en_US
dc.identifier.isbn	9780769546520	en_US
dc.identifier.uri	http://hdl.handle.net/10453/23002
dc.description.abstract	Knowledge represented on the Semantic Sensor Web originates from different datasets which are often a collection or aggregation of other sources. The SSW is dynamic, open and distributed, so the datasets are of varying quality and completeness. Consumers need to be provided with a level of trustworthiness of this knowledge to determine its relevance and usefulness. Interpretation of provenance (detailed information about the origin of data - held in metadata) is necessary in order to analyse how knowledge came into existence and measure its trustworthiness. However there are challenges in interpreting the provenance in a uniform way, because different data providers use different processes to manipulate the data and different annotation techniques to provide metadata. Although there are methods for retrieving provenance, knowledge consumers are left with the responsibility of assessing the trustworthiness of discovered knowledge dependent on how they see it fitting their application. This paper proposes a meta-knowledge ontology to align the concepts and properties of existing provenance schemas and ontologies. The meta-provenance ontology enables common interpretation of different provenances, and hence their integration. This paper also presents a trustworthiness assessment model based on integrating provenance. This model provides a function for the knowledge consumer to choose the relevant provenance attributes and allows for ranking of their importance. This provides a reliable mechanism for measuring trustworthiness, as only attributes relevant to the consumer are used. © 2012 IEEE.	en_US
dc.relation.ispartof	Proceedings - 26th IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2012	en_US
dc.relation.isbasedon	10.1109/WAINA.2012.197	en_US
dc.title	Trustworthiness assessment of knowledge on the semantic sensor web by provenance integration	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
dc.location.activity	Japan	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Knowledge represented on the Semantic Sensor Web originates from different datasets which are often a collection or aggregation of other sources. The SSW is dynamic, open and distributed, so the datasets are of varying quality and completeness. Consumers need to be provided with a level of trustworthiness of this knowledge to determine its relevance and usefulness. Interpretation of provenance (detailed information about the origin of data - held in metadata) is necessary in order to analyse how knowledge came into existence and measure its trustworthiness. However there are challenges in interpreting the provenance in a uniform way, because different data providers use different processes to manipulate the data and different annotation techniques to provide metadata. Although there are methods for retrieving provenance, knowledge consumers are left with the responsibility of assessing the trustworthiness of discovered knowledge dependent on how they see it fitting their application. This paper proposes a meta-knowledge ontology to align the concepts and properties of existing provenance schemas and ontologies. The meta-provenance ontology enables common interpretation of different provenances, and hence their integration. This paper also presents a trustworthiness assessment model based on integrating provenance. This model provides a function for the knowledge consumer to choose the relevant provenance attributes and allows for ranking of their importance. This provides a reliable mechanism for measuring trustworthiness, as only attributes relevant to the consumer are used. © 2012 IEEE.

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http://hdl.handle.net/10453/23002