Belief Propagation Through Provenance Graphs

• Published in: Provenance and Annotation of Data and Processes Vol. 11017; pp. 145 - 157
• Main Authors: Batlajery, Belfrit Victor, Weal, Mark, Chapman, Adriane, Moreau, Luc
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2018; Springer International Publishing
• Series: Lecture Notes in Computer Science
• ISBN: 3319983784; 9783319983783
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-98379-0_11

Provenance of food describes food, the processes in food transformation, and the food operators from the source to consumption; modelling the history food. In processing food, the risk of contamination increases if food is treated inappropriately. Therefore, identifying critical processes and applying suitable prevention actions are necessary to measure the risk; known as due diligence. To achieve due diligence, food provenance can be used to analyse the risk of contamination in order to find the best place to sample food. Indeed, it supports building rationale over food-related activities because it describes the details about food during its lifetime. However, many food risk models only rely on simulation with little notion of provenance of food. Incorporating the risk model with food provenance through our framework, prFrame, is our first contribution. prFrame uses Belief Propagation (BP) over the provenance graph for automatically measuring the risk of contamination. As BP works efficiently in a factor graph, our next contribution is the conversion of the provenance graph into the factor graph. Finally, an evaluation of the accuracy of the inference by BP is our last contribution.