The future of agriculture depends on the adoption of new technologies that gather, transfer, manage, and analyze data to make better decisions on all aspects of agriculture.
These data can be categorized into environmental facts (e.g., soil moisture, local weather), agriculture operation data (e.g., genetics, irrigation rates), and business data (e.g., tax, contracts) based on the various processes and purposes through which these data were collected. Based on their volumes, these categories can be structured as a pyramid.
The raw data collected by farmers in the fields is mostly environmental facts and agriculture operation data. Ownership of this data, however, can be questionable due to the lack of intellectual creation.
Nevertheless, through the rapid development of artificial intelligence (AI), this raw data, especially environmental facts, may potentially be of great economic value, because farming efficiencies and efficacy can be improved by mining the concepts or uncertainties that underlie this data, which were previously hard to model.
A survey released by the American Farm Bureau Federation (AFBF) in 2014 indicates that farmers and ranchers want to control the information collected from their fields and livestock. Ownership and control of farming data is a significant concern for farmers, if others could use their information for commodity market speculation without their consent.
A similar study in Australia in 2019 shows the majority of respondents did not know much about the conditions and terms of the data analysis contracts they signed.
While some Agriculture Technology Providers (ATPs) offer to subsidize their service fee by owning on-farm data, competitors or downstream companies may take advantage and use the data to leverage more significant contractual terms against growers.
Not surprisingly, these scenarios lead to concerns about how the data was collected from the fields and who owns, and has access to such data. Regulation of such data is still nascent, as court cases about data Ownership, Access, and Use (OSU) are sparse, adding to legal uncertainty and making business planning for growers more difficult because of information asymmetries regarding data-related risks.
Farming data produced by monitoring systems may involve many parties including producers, landlords, and different ATPs. Proportionally, everyone contributes to the processes in producing the physical agricultural commodities whose ownership is similar to owning a house, land, or a car.
However, farming data generated during this process is a virtual product that cannot be easily considered as a common property. Instead, US law classifies data, including farming data, as “facts.”
As the basic fact underlying certain agricultural commodities, farming data lacks a creative element which can be defined as an intellectual property (IP) whose ownership could be protected by copyright laws (17 U.S.C. § 102(a)), such as published books or commercial programs.
Even if the data collection or the fact discovery has taken years in a research project, for example, the factual data is still not protected. Therefore, legally speaking, farmers do not own the “raw” data generated from their land.
However, creativity can be part of the arrangement, management, and selection of data that can be defined as IP. For example, a database can be protected under copyright laws, if it compiles selective datasets collected from a certain field in 2020 for strawberry phenotyping. In other words, if a farmer stores and manages the data generated from their land and/or relates it to other elements, then their ownership of such a database can be copyrighted.
Actually, most farmers lack such expertise or resources and have to purchase services from ATPs. This is the exact source of the farmers’ concerns about losing ownership of their data. The IP is owned by ATPs who made creations in collecting, managing, and analyzing data, while farmers are the providers of the factual information.
Thus, farmers’ benefits are vulnerable when collaborating with ATPs. Copyright law might partially help with allowing contracts to override ownership provisions making it important for farmers to look more closely at the contracts through which both the data contributors (e.g.,
farmers) and the service providers (e.g., ATPs) bilaterally negotiate an agreement.
These are the primary legal documents that determine how agricultural data is owned, controlled, and shared. Yet, fair negotiation is rare in making such agreements, because many ATPs are large multinational corporations with powerful legal teams, which develop a long tedious unchangeable document mostly protecting the ATP’s benefits. Farmers can either accept it or not receive the service.
A set of Privacy and Security Principles were developed by American Farm Bureau Federation in 2014 for farmers to handle data ownership issues in smart farming partnerships with ATPs. Yet, although many ATPs have signed a related Ag Data Transparent agreement that declare farmers’ ownership of their data, the associated profits of the derived products are not shared
with farmers who invested their data in the development at the beginning.
Unfortunately, this problem may take years to address from the bottom up. Farmers who have
been using, or are looking forward to applying smart farming technologies should fully
understand the principles when working with ATPs. It is also important for every farmer to do the
following:
● Realize that smart farming applications are not only tools to help a specific farming operation, but are also an industry node to which farmers contribute and invest their farming data and deserve a share of the derived profit.
● Be knowledgeable about the farming data flow and the relationship between farms and ATPs.
● Know the terms and associated meanings to completely understand the contract and the explicitly defined ownership, access, and control.
● Resolve confusion before committing to any data sharing or service.
● Learn basic techniques of data management and keep a personal copy of the farming data from their farms.
● Apply smart farming applications using farming data to improve the efficiency of farming operations.
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