IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i18p13746-d1240093.html
   My bibliography  Save this article

Towards Trusted Data Sharing and Exchange in Agro-Food Supply Chains: Design Principles for Agricultural Data Spaces

Author

Listed:
  • Martina Šestak

    (Faculty of Electrical Engineering and Computer Science, University of Maribor, 2000 Maribor, Slovenia)

  • Daniel Copot

    (ITC—Innovation Technology Cluster Murska Sobota, 9000 Murska Sobota, Slovenia)

Abstract

In the modern agricultural landscape, realizing data’s full potential requires a unified infrastructure where stakeholders collaborate and share their data to gain insights and create business value. The agricultural data ecosystem (ADE) serves as a crucial socio-technical infrastructure, aggregating diverse data from various platforms and, thus, advertising sustainable agriculture and digitalization. Establishing trustworthy data sharing and exchange in agro-food value chains involves socioeconomic and technological elements addressed by the agricultural data space (ADS) and its trust principles. This paper outlines key challenges to data sharing in agro-food chains impeding ADE establishment based on the review of 27 studies in scientific literature. Challenges mainly arise from stakeholders’ mistrust in the data-sharing process, inadequate data access and use policies, and unclear data ownership agreements. In the ADE context, interoperability is a particularly challenging topic for ensuring the long-term sustainability of the system. Considering these challenges and data space principles and building blocks, we propose a set of design principles for ADS design and implementation that aim to mitigate the adverse impact of these challenges and facilitate agricultural data sharing and exchange.

Suggested Citation

  • Martina Šestak & Daniel Copot, 2023. "Towards Trusted Data Sharing and Exchange in Agro-Food Supply Chains: Design Principles for Agricultural Data Spaces," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13746-:d:1240093
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/18/13746/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/18/13746/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zaid Ameen Abduljabbar & Vincent Omollo Nyangaresi & Hend Muslim Jasim & Junchao Ma & Mohammed Abdulridha Hussain & Zaid Alaa Hussien & Abdulla J. Y. Aldarwish, 2023. "Elliptic Curve Cryptography-Based Scheme for Secure Signaling and Data Exchanges in Precision Agriculture," Sustainability, MDPI, vol. 15(13), pages 1-20, June.
    2. Mohammad Amiri-Zarandi & Mehdi Hazrati Fard & Samira Yousefinaghani & Mitra Kaviani & Rozita Dara, 2022. "A Platform Approach to Smart Farm Information Processing," Agriculture, MDPI, vol. 12(6), pages 1-18, June.
    3. Katrin Martens & Jana Zscheischler, 2022. "The Digital Transformation of the Agricultural Value Chain: Discourses on Opportunities, Challenges and Controversial Perspectives on Governance Approaches," Sustainability, MDPI, vol. 14(7), pages 1-15, March.
    4. Beatrice Garske & Antonia Bau & Felix Ekardt, 2021. "Digitalization and AI in European Agriculture: A Strategy for Achieving Climate and Biodiversity Targets?," Sustainability, MDPI, vol. 13(9), pages 1-21, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haoling Ren & Jiangdong Wu & Tianliang Lin & Yu Yao & Chang Liu, 2023. "Research on an Intelligent Agricultural Machinery Unmanned Driving System," Agriculture, MDPI, vol. 13(10), pages 1-19, September.
    2. Mohammad Amiri-Zarandi & Rozita A. Dara & Emily Duncan & Evan D. G. Fraser, 2022. "Big Data Privacy in Smart Farming: A Review," Sustainability, MDPI, vol. 14(15), pages 1-18, July.
    3. Margot Luyckx & Leonie Reins, 2022. "The Future of Farming: The (Non)-Sense of Big Data Predictive Tools for Sustainable EU Agriculture," Sustainability, MDPI, vol. 14(20), pages 1-17, October.
    4. Ayman Issa & Mohammad A. A. Zaid, 2023. "Firm's biodiversity initiatives disclosure and board gender diversity: A multi‐country analysis of corporations operating in Europe," Business Strategy and the Environment, Wiley Blackwell, vol. 32(7), pages 4991-5007, November.
    5. Metta, Matteo & Ciliberti, Stefano & Obi, Chinedu & Bartolini, Fabio & Klerkx, Laurens & Brunori, Gianluca, 2022. "An integrated socio-cyber-physical system framework to assess responsible digitalisation in agriculture: A first application with Living Labs in Europe," Agricultural Systems, Elsevier, vol. 203(C).
    6. Tilman Reinhardt, 2023. "The farm to fork strategy and the digital transformation of the agrifood sector—An assessment from the perspective of innovation systems," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 45(2), pages 819-838, June.
    7. Kadukothanahally Nagaraju Shivaprakash & Niraj Swami & Sagar Mysorekar & Roshni Arora & Aditya Gangadharan & Karishma Vohra & Madegowda Jadeyegowda & Joseph M. Kiesecker, 2022. "Potential for Artificial Intelligence (AI) and Machine Learning (ML) Applications in Biodiversity Conservation, Managing Forests, and Related Services in India," Sustainability, MDPI, vol. 14(12), pages 1-20, June.
    8. Ingram, Julie & Maye, Damian & Bailye, Clive & Barnes, Andrew & Bear, Christopher & Bell, Matthew & Cutress, David & Davies, Lynfa & de Boon, Auvikki & Dinnie, Liz & Gairdner, Julian & Hafferty, Caitl, 2022. "What are the priority research questions for digital agriculture?," Land Use Policy, Elsevier, vol. 114(C).
    9. Pan Rao & Xiaojin Liu & Shubin Zhu & Xiaolan Kang & Xinglei Zhao & Fangting Xie, 2022. "Does the Application of ICTs Improve the Efficiency of Agricultural Carbon Reduction? Evidence from Broadband Adoption in Rural China," IJERPH, MDPI, vol. 19(13), pages 1-19, June.
    10. Aaron Chimbelya Siyunda & Emmanuel Chikalipa & Tibonge Mfune & Rodrick Habvumba, 2022. "Digitalizing Agriculture for Sustainable Crop production," International Journal of Science and Business, IJSAB International, vol. 11(1), pages 55-61.
    11. Zhikai Ma & Kun Chong & Shiwei Ma & Weiqiang Fu & Yanxin Yin & Helong Yu & Chunjiang Zhao, 2022. "Control Strategy of Grain Truck Following Operation Considering Variable Loads and Control Delay," Agriculture, MDPI, vol. 12(10), pages 1-14, September.
    12. Catherine E. Sanders & Kristin E. Gibson & Alexa J. Lamm, 2022. "Rural Broadband and Precision Agriculture: A Frame Analysis of United States Federal Policy Outreach under the Biden Administration," Sustainability, MDPI, vol. 14(1), pages 1-15, January.
    13. Xinxin Zhou & Tong Chen & Bangbang Zhang, 2023. "Research on the Impact of Digital Agriculture Development on Agricultural Green Total Factor Productivity," Land, MDPI, vol. 12(1), pages 1-20, January.
    14. Xiaohan Li & Yuwei Zhang & Ali Sorourkhah & S. A. Edalatpanah, 2024. "Introducing Antifragility Analysis Algorithm for Assessing Digitalization Strategies of the Agricultural Economy in the Small Farming Section," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 12191-12215, September.
    15. Weikun Zhang & Peng Gao & Zhe Chen & Hailan Qiu, 2023. "Preventing Agricultural Non-Point Source Pollution in China: The Effect of Environmental Regulation with Digitization," IJERPH, MDPI, vol. 20(5), pages 1-17, March.
    16. Xiaochen Leng & Guangji Tong, 2022. "The Digital Economy Empowers the Sustainable Development of China’s Agriculture-Related Industries," Sustainability, MDPI, vol. 14(17), pages 1-22, September.
    17. Jinying Li & Ananda Maiti & Jiangang Fei, 2023. "Features and Scope of Regulatory Technologies: Challenges and Opportunities with Industrial Internet of Things," Future Internet, MDPI, vol. 15(8), pages 1-27, July.
    18. Moisés Barbosa Junior & Eliane Pinheiro & Carla Cristiane Sokulski & Diego Alexis Ramos Huarachi & Antonio Carlos de Francisco, 2022. "How to Identify Barriers to the Adoption of Sustainable Agriculture? A Study Based on a Multi-Criteria Model," Sustainability, MDPI, vol. 14(20), pages 1-18, October.
    19. Elena G. Popkova & Shakhlo T. Ergasheva & Nadezhda K. Savelyeva & Marija A. Troyanskaya, 2024. "Change Management for the Sustainable Development of the Agrarian Economy of Artificial Intelligence," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 25(1), pages 79-90, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:18:p:13746-:d:1240093. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.