Trusted and Auditable Decision Aids over Data Streams

Dominic Duxbury, Norman Paton, John Keane

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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Data stream management systems exist to support dynamic analysis of streaming data, often to inform decision-making. Decision support systems exist to enable decisions to be made that take into account user priorities. However, although these categories of system are now quite mature, there has been little work investigating their use together. In this paper we bring together a well established streaming platform (Storm) and a widely used decision-support methodology (Analytic Hierarchy Process) to provide dynamic decision support over data streams. In so doing, we also investigate approaches making recommendations auditable (using provenance) and trustable (using explanations). The resulting stream decision support system is illustrated using an application that supports train journey planning.
Original languageEnglish
Title of host publicationProceedings of the Workshops of the EDBT/ICDT 2019 Joint Conference
Publication statusPublished - 2019


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