Modelling Provenance of Sensor Data for Food Safety Compliance Checking

Milan Markovic, Peter Edwards, Martin Kollingbaum, Alan Rowe

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

12 Citations (Scopus)
24 Downloads (Pure)


The Internet of Things (IoT) is resulting in ever greater volumes of low level sensor data. However, such data is meaningless without higher level context that describes why such data is needed and what useful information can be derived from it. Provenance records should play a pivotal role in supporting a range of automated processes acting on the data streams emerging from an IoT-enabled infrastructure. In this paper we discuss how such provenance can be modelled by extending an existing suite of provenance ontologies. Furthermore, we demonstrate how provenance abstractions can be inferred from sensor data annotated using the SSN ontology. A real-world application from food-safety compliance monitoring will be used throughout to illustrate our achievements
to date, and the challenges that remain.
Original languageEnglish
Title of host publicationProvenance and Annotation of Data and Processes
Subtitle of host publication6th International Provenance and Annotation Workshop, IPAW 2016, McLean, VA, USA, June 7-8, 2016, Proceedings
EditorsMarta Mattoso, Boris Glavic
Number of pages12
ISBN (Electronic)9783319405933
ISBN (Print)9783319405926
Publication statusPublished - 4 Jun 2016
Event6th International Provenance and Annotation Workshop: IPAW 2016 - Virginia, United States
Duration: 7 Jun 20168 Jun 2016

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743


Conference6th International Provenance and Annotation Workshop
Country/TerritoryUnited States

Bibliographical note

The research described here was funded by an award made by the RCUK IT as a Utility Network+ (EP/K003569/1) and the UK Food Standards Agency. We thank the owner and staff of Rye & Soda restaurant, Aberdeen for their support throughout the project.


Dive into the research topics of 'Modelling Provenance of Sensor Data for Food Safety Compliance Checking'. Together they form a unique fingerprint.

Cite this