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README.md

FoodSafety-Data

This repository contains raw sensor data and ontologies used in experiments during the project titled FOOD SAFETY ASSURANCE: COMBINING PROVENANCE & THE INTERNET OF THINGS.

The latest version of the ontology can be found at http://w3id.org/abdn/foodsafety/fs-prov

More information about the project can be found in the following publication:

*Milan Markovic, Peter Edwards, Martin Kollingbaum, Alan Rowe, "Modelling Provenance of Sensor Data for Food Safety Compliance Checking", In Proceedings of the 6th International Provenance & Annotation Workshop-IPAW 2016, June, 2016

Raw sensor data were collected in a commercial kitchen environment as a result of the following simulated scenarios which reflected HACCP compliance (so-called good day scenarios) and non-compliance (bad day scenarios) were as follows:

Good

  • Remove a single burger from the fridge and cook it until it reaches 75°C (repeat x4)

  • Remove two burgers from the fridge and cook them until they reach 75°C

Bad

  • Leave a single burger out of the fridge for 1 hour. Put it back in the fridge for 40 min and then cook it until it reaches 75°C

  • Remove a single burger from the fridge and cook it below 75°C (repeat x2)

  • Remove two burgers from the fridge and cook one until it reaches 75 °C and keep the second one below 75°C

  • Remove a single burger from the fridge for approx. 5 min then return to fridge for approx. 5 min and repeat 5 times; then cook until it reaches 75°C

Raw temperature readings from the wireless tags and the wireless meat probe recorded during the simulated experiments at Rye & Soda on 10 February 2016 and 11 February 2016 are available.

Our project partner (Rye & Soda restaurant) is happy for this data to be used provided that the business is always named and that the basis on which the data was collected is made clear (see comments about scenarios above) and use of the data reflects the brand in a positive manner.

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