IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i11p2170-d1283588.html
   My bibliography  Save this article

Analysis of Farm Data License Agreements: Do Data Agreements Adequately Reflect on Farm Data Practices and Farmers’ Data Rights?

Author

Listed:
  • Jasmin Kaur

    (School of Computer Science, University of Guelph, Guelph, ON N1G 2W1, Canada)

  • Rozita Dara

    (School of Computer Science, University of Guelph, Guelph, ON N1G 2W1, Canada)

Abstract

Farm data license agreements are legal documents that play an important role in informing farmers about farm data processing practices such as collection, use, safeguarding, and sharing. These legal documents govern the exchange, access, and dissemination of farm data and are expected to provide legal protection against misuse of data. Despite their significant influence on farm data processing and governance, there is limited understanding of the content of farm data license agreements and standards for drafting them. Although online privacy policy content has been extensively studied, farm data agreements’ evaluation and analysis have been overlooked. This study aims to investigate the structure, content, and transparency of farm data licenses. We collected 141 agricultural terms of use agreements and used natural language processing methods such as keyword and keyphrase analysis to perform text feature analysis, Flesch Readability Ease Score and Flesch Grade Level readability analysis, transparency analysis, and content analysis to gain insight into common data practices adopted by the agriculture technology providers. We also manually reviewed these agreements to validate the results and strengthen the observations. The findings show that data agreements are long, complex, and difficult to read and comprehend. The results suggest that 95% of the agreements fall under the difficult-to-read category and close to 75% of the policies require university-level education to understand the content. Furthermore, it is noted that some of the data management practices are not given adequate attention and are not as frequently mentioned in the agreements as expected. Finally, our analysis enabled us to provide recommendations on the content of farm data license agreements and strategies to improve them.

Suggested Citation

  • Jasmin Kaur & Rozita Dara, 2023. "Analysis of Farm Data License Agreements: Do Data Agreements Adequately Reflect on Farm Data Practices and Farmers’ Data Rights?," Agriculture, MDPI, vol. 13(11), pages 1-28, November.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:11:p:2170-:d:1283588
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/11/2170/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/11/2170/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wolfert, Sjaak & Ge, Lan & Verdouw, Cor & Bogaardt, Marc-Jeroen, 2017. "Big Data in Smart Farming – A review," Agricultural Systems, Elsevier, vol. 153(C), pages 69-80.
    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. Lin Xie & Biliang Luo & Wenjing Zhong, 2021. "How Are Smallholder Farmers Involved in Digital Agriculture in Developing Countries: A Case Study from China," Land, MDPI, vol. 10(3), pages 1-16, March.
    2. Oliver Falck & Johannes Koenen, 2020. "Rohstoff „Daten“: Volkswirtschaflicher Nutzen von Datenbereitstellung – eine Bestandsaufnahme," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 113, October.
    3. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitalization of the agricultural sector: the impact of ICT on the development of enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), December.
    4. Ascui, Francisco & Ball, Alex & Kahn, Lewis & Rowe, James, 2021. "Is operationalising natural capital risk assessment practicable?," Ecosystem Services, Elsevier, vol. 52(C).
    5. Huo, Dongyang & Malik, Asad Waqar & Ravana, Sri Devi & Rahman, Anis Ur & Ahmedy, Ismail, 2024. "Mapping smart farming: Addressing agricultural challenges in data-driven era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    6. Pigford, Ashlee-Ann E. & Hickey, Gordon M. & Klerkx, Laurens, 2018. "Beyond agricultural innovation systems? Exploring an agricultural innovation ecosystems approach for niche design and development in sustainability transitions," Agricultural Systems, Elsevier, vol. 164(C), pages 116-121.
    7. Tianyu Qin & Lijun Wang & Yanxin Zhou & Liyue Guo & Gaoming Jiang & Lei Zhang, 2022. "Digital Technology-and-Services-Driven Sustainable Transformation of Agriculture: Cases of China and the EU," Agriculture, MDPI, vol. 12(2), pages 1-16, February.
    8. Viet, Nguyen Quoc & Behdani, Behzad & Bloemhof, Jacqueline, 2018. "Value of Information to Improve Daily Operations in High-Density Logistics," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 9(1), January.
    9. Hrosul, Viktoriia & Kruhlova, Olena & Kolesnyk, Alina, 2023. "Digitization of the Agricultural Sector: The Impact of ICT on the Development of Enterprises in Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(4), January.
    10. Thomas M. Koutsos & Georgios C. Menexes & Andreas P. Mamolos, 2021. "The Use of Crop Yield Autocorrelation Data as a Sustainable Approach to Adjust Agronomic Inputs," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    11. Li, Lei & Lin, Jiabao & Ouyang, Ye & Luo, Xin (Robert), 2022. "Evaluating the impact of big data analytics usage on the decision-making quality of organizations," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    12. Panos Constantinides & Ola Henfridsson & Geoffrey G. Parker, 2018. "Introduction—Platforms and Infrastructures in the Digital Age," Information Systems Research, INFORMS, vol. 29(2), pages 381-400, June.
    13. Iban, Muzaffer Can & Aksu, Oktay, 2020. "A model for big spatial rural data infrastructure in Turkey: Sensor-driven and integrative approach," Land Use Policy, Elsevier, vol. 91(C).
    14. Divya Suresh & Abhishek Choudhury & Yinjia Zhang & Zhiying Zhao & Rajib Shaw, 2024. "The Role of Data-Driven Agritech Startups—The Case of India and Japan," Sustainability, MDPI, vol. 16(11), pages 1-17, May.
    15. Fengwan Zhang & Xueling Bao & Xin Deng & Dingde Xu, 2022. "Rural Land Transfer in the Information Age: Can Internet Use Affect Farmers’ Land Transfer-In?," Land, MDPI, vol. 11(10), pages 1-14, October.
    16. Simon Marvin & Lauren Rickards & Jonathan Rutherford, 2024. "The urbanisation of controlled environment agriculture: Why does it matter for urban studies?," Urban Studies, Urban Studies Journal Limited, vol. 61(8), pages 1430-1450, June.
    17. Hidalgo, Francisco & Quiñones-Ruiz, Xiomara F. & Birkenberg, Athena & Daum, Thomas & Bosch, Christine & Hirsch, Patrick & Birner, Regina, 2023. "Digitalization, sustainability, and coffee. Opportunities and challenges for agricultural development," Agricultural Systems, Elsevier, vol. 208(C).
    18. Madhu Khanna & Shady S. Atallah & Saurajyoti Kar & Bijay Sharma & Linghui Wu & Chengzheng Yu & Girish Chowdhary & Chinmay Soman & Kaiyu Guan, 2022. "Digital transformation for a sustainable agriculture in the United States: Opportunities and challenges," Agricultural Economics, International Association of Agricultural Economists, vol. 53(6), pages 924-937, November.
    19. 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).
    20. Víctor M. Albornoz & Lia C. Araneda & Rodrigo Ortega, 2022. "Planning and scheduling of selective harvest with management zones delineation," Annals of Operations Research, Springer, vol. 316(2), pages 873-890, 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:jagris:v:13:y:2023:i:11:p:2170-:d:1283588. 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.