raceability plays an important role in the food industry because it is directly connected with food quality and safety. Safety, in fact, can only be guaranteed by following food products along the entire supply chain. In the last years, a series of food safety scandals have invested the meat sector, highlighting the lack of common standards for information encoding and management and the inability to link food products with the elements involved in their transformation process. This paper describes the MEat Supply Chain Ontology (MESCO), an ontology developed for supporting the management of meat traceability along the whole supply chain. In particular, in this paper the authors instantiate MESCO to take the problem of meat traceability from the farmer to the final consumer. The article describes the main features of MESCO, illustrating the different steps followed for its development and some example of application. MESCO has been validated and interrogated through the formulation of several queries expressed in Description Logic (DL), executed using the Pellet reasoner, to deal with different scenarios and problems of traceability. The results show that MESCO is able to represent all the knowledge and information related to the meat traceability domain into a single ontology, enabling interoperability among different systems and allowing for integrating the heterogeneous databases adopted by each actor involved in the supply chain. One of the main advantages in using MESCO is the facility in obtaining essential data, fundamental in case of food outbreak disease, addressing the key issues that makes the job of food safety agents frustrating. © 2016 Elsevier Ltd
MESCO (MEat Supply Chain Ontology): An ontology for supporting traceability in the meat supply chain
MIRABELLI, Giovanni;GRASSO, Giovanni;
2017-01-01
Abstract
raceability plays an important role in the food industry because it is directly connected with food quality and safety. Safety, in fact, can only be guaranteed by following food products along the entire supply chain. In the last years, a series of food safety scandals have invested the meat sector, highlighting the lack of common standards for information encoding and management and the inability to link food products with the elements involved in their transformation process. This paper describes the MEat Supply Chain Ontology (MESCO), an ontology developed for supporting the management of meat traceability along the whole supply chain. In particular, in this paper the authors instantiate MESCO to take the problem of meat traceability from the farmer to the final consumer. The article describes the main features of MESCO, illustrating the different steps followed for its development and some example of application. MESCO has been validated and interrogated through the formulation of several queries expressed in Description Logic (DL), executed using the Pellet reasoner, to deal with different scenarios and problems of traceability. The results show that MESCO is able to represent all the knowledge and information related to the meat traceability domain into a single ontology, enabling interoperability among different systems and allowing for integrating the heterogeneous databases adopted by each actor involved in the supply chain. One of the main advantages in using MESCO is the facility in obtaining essential data, fundamental in case of food outbreak disease, addressing the key issues that makes the job of food safety agents frustrating. © 2016 Elsevier LtdI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.