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METROFOOD-IT: A data platform proposal using Agrifood Smart Data Model

TitleMETROFOOD-IT: A data platform proposal using Agrifood Smart Data Model
Publication TypePresentazione a Congresso
Year of Publication2024
AuthorsDi Bitonto, P., De Trizio L., Magarelli Rosaria Alessandra, Diacono D., Novielli P., Romano D., Zoani Claudia, Bellotti R., and Tangaro S.
Conference Name2024 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
KeywordsAgrifood, Architectural modeling, Data flow analysis, Data platform, Data Sharing, Digitisation, Distributed database, Ecosystems, Food sector, Information services, Integrated service, Semantics, Service oriented architecture (SOA), Smart data model, SMART datum
Abstract

METROFOOD-IT enhances the Italian Node of the ESFRI METROFOOD-RI infrastructure and promotes research and innovation in the agri-food sector through integrated services, with an emphasis on digitization, efficiency, traceability, and sustainability. The project fosters a research paradigm focused on improving metrological data flows to enhance, quality, traceability, security in the food and nutritional domain. This paper introduces the architectural model utilized for the integration of both physical and electronic facilities. A service-oriented architecture (SOA) has been designed to facilitate efficient and scalable data sharing. The METROFOOD-IT architectural model unfolds across three levels: services, data infrastructure, and linking infrastructure. The data architecture plays a central role in managing backend systems for services, ensuring continuous data availability to each ecosystem service. To guarantee a stable and recognized data model by the scientific and industrial community, the Smart Data Model Agrifood has been adopted. This model addresses standardized data sharing and standardization issues, ensuring uniformity in data syntax and semantics, implementing access restrictions, and providing essential technical aspects in data platforms. © 2024 IEEE.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85199553123&doi=10.1109%2fMetroInd4.0IoT61288.2024.10584240&partnerID=40&md5=e2363bf3d82bb6b52c9259ba98a7aca9
DOI10.1109/MetroInd4.0IoT61288.2024.10584240
Citation KeyDiBitonto2024117