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Agricultural Information Model

In: Information and Communication Technologies for Agriculture—Theme III: Decision

Author

Listed:
  • Raul Palma

    (Poznan Supercomputing and Networking Center)

  • Ioanna Roussaki

    (Institute of Communication and Computer Systems)

  • Till Döhmen

    (Fraunhofer Institute for Applied Information Technology FIT)

  • Rob Atkinson

    (Open Geospatial Consortium Europe Technologielaan)

  • Soumya Brahma

    (Poznan Supercomputing and Networking Center)

  • Christoph Lange

    (Fraunhofer Institute for Applied Information Technology FIT)

  • George Routis

    (Institute of Communication and Computer Systems)

  • Marcin Plociennik

    (Poznan Supercomputing and Networking Center)

  • Szymon Mueller

    (Poznan Supercomputing and Networking Center)

Abstract

One of the key challenges towards the realization of smart farming solutions is related to the lack of interoperability between different systems and platforms in the agri-food sector, especially the ones offered by different technology providers. In this respect, seamless exchange and integration of the data produced or collected by those systems is of major importance, which unfortunately is rarely supported. This is in principle due to the wide heterogeneity of data models and semantics used to represent data in the agri-food domain, as well as the lack of related standards to dominate this space and the lack of sufficient interoperability mechanisms that enable the connection of existing agri-food data models. This chapter presents the Agriculture Information Model (AIM) that has been developed by the H2020 DEMETER project, which aims to address the aforementioned issues. AIM has been designed following a layered and modular approach and is realized as a suite of ontologies implemented in line with best practices, reusing existing standards and well-scoped models as much as possible and establishing alignments between them to enable their interoperability and the integration of existing data. AIM is scalable and can easily be extended to address additional needs and incorporate new concepts, maintaining its consistency and compliance. The AIM specification includes a set of guidelines and examples for application developers and other users and is currently being validated in demanding large-scale pilots across various operational environments in the framework of the H2020 DEMETER project aiming to enable the provision of efficient interoperable solutions to farmers and other stakeholders in the agri-food value chain.

Suggested Citation

  • Raul Palma & Ioanna Roussaki & Till Döhmen & Rob Atkinson & Soumya Brahma & Christoph Lange & George Routis & Marcin Plociennik & Szymon Mueller, 2022. "Agricultural Information Model," Springer Optimization and Its Applications, in: Dionysis D. Bochtis & Claus Grøn Sørensen & Spyros Fountas & Vasileios Moysiadis & Panos M. Pardalos (ed.), Information and Communication Technologies for Agriculture—Theme III: Decision, pages 3-36, Springer.
    • Handle: RePEc:spr:spochp:978-3-030-84152-2_1
    DOI: 10.1007/978-3-030-84152-2_1
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    Cited by:

    1. Mario San Emeterio de la Parte & Sara Lana Serrano & Marta Muriel Elduayen & José-Fernán Martínez-Ortega, 2023. "Spatio-Temporal Semantic Data Model for Precision Agriculture IoT Networks," Agriculture, MDPI, vol. 13(2), pages 1-28, February.

    More about this item

    Keywords

    Smart farming; Data modeling; Information model; H2020;
    All these keywords.

    JEL classification:

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