Personalised Provenance Reasoning Models and Risk Assessment in Business Systems: A Case Study

Paul Townend, David Webster, Colin C. Venters, Vania Dimitrova, Karim Djemame, Lydia Lau, Jie Xu, Sarah Fores, Valentina Viduto, Charlie Dibsdale, Nick Taylor, Jim Austin, John McAvoy, Stephen Hobson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

As modern information systems become increasingly business- And safety-critical, it is extremely important to improve both the trust that a user places in a system and their understanding of the risks associated with making a decision. This paper presents the STRAPP framework, a generic framework that supports both of these goals through the use of personalised provenance reasoning engines and state-of-art risk assessment techniques. We present the high-level architecture of the framework, and describe the process of systematically modelling system provenance with the W3C PROV provenance data model. We discuss the business drivers behind the concept of personalizing provenance information, and describe an approach to enabling this through a user-adaptive system style. We discuss using data provenance for risk management and treatment in order to evaluate risk levels, and discuss the use of CORAS to develop a risk reasoning engine representing core classes and relationships. Finally, we demonstrate the initial implementation of our personalised provenance system in the context of the Rolls-Royce Equipment Health Management, and discuss its operation, the lessons we have learnt through our research and implementation (both technical and in business), and our future plans for this project.

Original languageEnglish
Title of host publicationProceedings of IEEE Seventh International Symposium on Service-Oriented System Engineering (SOSE 2013)
EditorsJuan E. Guerrero
PublisherIEEE
Pages329-334
Number of pages6
ISBN (Electronic)9780769549446
ISBN (Print)9781467356596
DOIs
Publication statusPublished - 10 Jun 2013
Externally publishedYes
Event2013 IEEE 7th International Symposium on Service-Oriented System Engineering - Redwood City, San Francisco Bay, United States
Duration: 25 Mar 201328 Mar 2013
Conference number: 7
http://sei.pku.edu.cn/conference/sose2013/index.htm

Conference

Conference2013 IEEE 7th International Symposium on Service-Oriented System Engineering
Abbreviated titleSOSE 2013
CountryUnited States
CitySan Francisco Bay
Period25/03/1328/03/13
Internet address

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    Townend, P., Webster, D., Venters, C. C., Dimitrova, V., Djemame, K., Lau, L., Xu, J., Fores, S., Viduto, V., Dibsdale, C., Taylor, N., Austin, J., McAvoy, J., & Hobson, S. (2013). Personalised Provenance Reasoning Models and Risk Assessment in Business Systems: A Case Study . In J. E. Guerrero (Ed.), Proceedings of IEEE Seventh International Symposium on Service-Oriented System Engineering (SOSE 2013) (pp. 329-334). [6525541] IEEE. https://doi.org/10.1109/SOSE.2013.53