Learning about Farming Data

The issue of data collection, use, and ownership continues to be an important one. It relates to many facets of everyday life: social media, online shopping, media consumption, browsing habits, apps, and more. Questions of ownership and control of data even extend to the agricultural realm.

Farmers may have reservations about adopting data-driven technologies due to the possibility of losing ownership and control of the data generated on their farms. A recent Ask IFAS publication, Who Owns and Controls Farming Data?, discusses the components of farming data as well as principles and guidelines to follow when handling data ownership concerns in farming partnerships with Agriculture Technology Providers. It shows the structure of three categories of farming data—environmental facts, agriculture operation data, and business data—and lists relevant features and examples. The article identifies data and systems of data management that may be considered as intellectual property (IP) as well as data that would not be considered as IP, and also highlights understanding of contract law as a way to help farmers protect their raw data.

Working on a laptop.

A hypothetical smart farming case in the article illustrates several principles that include but are not limited to:

• Education
• Ownership
• Collection, access, and control
• Notice
• Transparency and consistency
• Choice
• Terms and definitions
• Data retention and availability
• Contract termination
• Liability and security safeguards

Lastly, this publication provides guidelines to help the parties involved stay on the same page when it comes to data sharing, agreements, contracts, and data management.

For exciting information on data and agricultural applications, check out more publications from the UF/IFAS Department of Agricultural and Biological Engineering, or just Ask IFAS.


Posted: November 4, 2021

Category: Agribusiness, Agriculture, Farm Management, Professional Development
Tags: Agricultural And Biological Engineering Department, Albert De Vries, D. Daniel Sokol, Farming Data, Yiannis Ampatzidis, Ziwen Yu

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