Today we continue in our Big Data on the Farm Series by looking at what laws may apply to protect farmers’ data. As I mentioned in Part I, this three-part blog series comes from a paper co-authored by myself and Shannon Ferrell at Oklahoma State University.
When the topic of big data is brought up, many farmers’ first reaction is to ask how they can protect their information from others? An adequate legal analysis of this question must necessarily start with determining who actually owns the data in the first place. The landowner? The farmer (if they are not the same person)? The agricultural technology provider?
Ashley Newhall, ag law specialist at the University of Maryland, explained this issue in a blog post that sets forth the six rights that generally apply to ownership: (1) right to possess; (2) right to use; (3) right to enjoy; (4) right to exclude others from; (5) right to transfer; and (6) right to consume or destroy. Some of these interests do not fit, or at least do not fit well, with data ownership. Excluding others from data, for example, is difficult, particularly when it is possible for many people to “possess” the property without diminishing its value to the others. Thus, the better question may be what are the rights and responsibilities of the parties in a data disclosure relationship with respect to that data?
In order to answer that question, we need to consider what legal protections may apply to farm data. Most agree that data most closely resembles intellectual property. As a result, the intellectual property framework serves as a useful starting point to define what rights a farmer might have to their farm data. Intellectual property can be divided into four categories: (1) trademark, (2) patent, (3) copyright, and (4) trade secret. The first three categories compose the realm of federal intellectual property law as they are defined by the Constitution as areas in which Congress has legislative authority. The fourth category–trade secret–is a matter of state law.
For the purposes of the following discussion, “farm data” will include the types of data typically uploaded automatically by the farmer’s equipment, such as diagnostic and use data, input application data, harvest data, and global positioning system (GPS) and geographic information system (GIS) data.
One of the easiest intellectual property models to discard as a viable farm data protection tool is trademark. The Federal Trademark Act (sometimes called the Lanham Act) defines trademark as “any word, name, symbol, or device, or any combination thereof…to identify and distinguish his or her goods, including a unique product, from those manufactured or sold by others and to indicate the source of the goods, even if that source is unknown.” 15 U.S.C. § 1127. Examples of trademark include product names, such as Coca-Cola® or the design of its contoured bottle. One quickly realizes trademark fits poorly as a model for defining farm data ownership, as trademark addresses intellectual property used for branding purposes rather than information.
Likewise, Patent law is likely inapplicable to farm data. The U.S. Patent Act states “whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor.” 35 U.S.C. § 101. Generally, for an invention to be patentable, it must be useful (capable of performing its intended purpose), novel (different from existing knowledge in the field), and non-obvious (somewhat difficult to define, but as set forth in the Patent Act, “a patent may not be obtained… if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains”). 35 U.S.C. §§ 102, 103. Patent serves as a poor fit for a model of farm data ownership since it protects “inventions.” Raw data, such as farm data, would not satisfy the definition of invention.
It should be noted patentable inventions could be derived from the analysis of farm data. While this does not mean the data itself is patentable, it does suggest that the agreement governing the disclosure of farm data by the farmer should address who holds the rights to inventions so derived (as discussed below).
The federal Copyright Act states the following: Copyright protection subsists, in accordance with this title, in original works of authorship fixed in any tangible medium of expression, now known or later developed, from which they can be perceived, reproduced, or otherwise communicated, either directly or with the aid of a machine or device. Works of authorship include the following categories: literary works; musical works, including any accompanying words; dramatic works, including any accompanying music; pantomimes and choreographic works; pictorial, graphic, and sculptural works; motion pictures and other audiovisual works; sound recordings; and architectural works. 17 U.S.C. § 102(a).
More so than trademark and patent, the copyright model at least resembles a model that could potentially be applicable to farm data. At the same time, however, the model also has numerous problems in addressing agricultural data.
First, the list of “works of authorship” provided in the statue strongly suggests a creative component is important to the copyrightable material. Second, the term “original works of authorship” also has been interpreted to require some element of creative input by the author of the copyrighted material.
This requirement was highlighted in the case of Fiest Publications Inc. v. Rural Telephone Service Company, 499 U.S. 340 (1991), where the U.S. Supreme Court held that the Copyright Act does not protect individual facts. There, the question was whether a pure telephone directory (consisting solely of a list of telephone numbers, organized alphabetically by the holder’s last name) was copyrightable. Since the directory consisted solely of pure data and was organized in the only practical way to organize such data, the Supreme Court held the work did not satisfy the creative requirements of the Copyright Act. This ruling affirmed the principle that raw facts and data, in and of themselves, are not copyrightable.
However, an author can add creative components to facts and data such as illustrations, commentary, or alternative organization systems and can copyright the creative components even if they cannot copyright the underlying facts and data. Put another way, the facts that hydrogen has an atomic number of 1 or that the number of ABC Plumbing is 555-1234 are not copyrightable, but an article about hydrogen in an encyclopedia or a Yellow Pages® ad with ABC Plumbing’s number along with a graphic and description of their services are.
As with patent, farm data can lead to copyrightable works even if the underlying data is not protected itself. For example, farm data may not be copyrightable, but a report summarizing the data and adding recommendations for action might be. Again, then, it is incumbent upon those disclosing farm data to include language in their agreements with the receiving party to define the rights to such works derived from the data.
While trademark, patent, and copyright do not appear to fit as models for farm data ownership, trade secret has the potential to fit the bill. Importantly, trade secret is a function of state law. This could pose difficulty as state laws often greatly differ. However, this concern is mostly alleviated because, as of this writing, all but three states have adopted the Uniform Trade Secrets Act, providing a significant degree of consistency in trade secret law across most states.
Under the Uniform Trade Secrets Act, a “trade secret” is defined as:…information, including a formula, pattern, compilation, program, device, method, technique, or process, that:
(1) derives independent economic value, actual or potential, from not being generally known to, and not being readily ascertainable by proper means by, other persons who can obtain economic value from its disclosure or use, and (2) is the subject of efforts that are reasonable under the circumstances to maintain its secrecy. Uniform Trade Secret Act, § 1.
Importantly, this definition makes clear that “information… pattern[s], [and] compilation[s]” can be protected as trade secret. This, at last, affords hope of a protective model for farm data. This is not to say that trade secret is a “slam dunk” for protecting farm data, however. Note the two additional requirements of trade secret: first, that the information has actual or potential economic value from not being known to other parties, and second, that it is the subject of reasonable efforts to maintain the secret.
The first provision requires that to be protected as a trade secret, farm data such as planting rates, harvest yields, or outlines of fields and machinery paths must have economic value because such information is not generally known. While a farmer may (or may not) have a privacy interest in this information, the question remains as to whether the economic value of that information derives, at least in part, from being a secret. The counterargument to that point is that the economic value of the information comes from the farmer’s analysis of that information and the application of that analysis to his or her own operation – a value completely independent of what anyone else does with that information – and that the information for that farm, standing alone, has no economic value to anyone else since that information is useless to anyone not farming that particular farm. One can see then this first element poses potential problems for the trade secret model. But all is not lost. The counterargument is that there is a clear economic benefit to the collection of farm data; otherwise Monsanto would not spend nearly $1 billion in acquiring a company to aggregate such data. This represents a question yet to be answered clearly by the body of trade secret law: whether one can have trade secret protection in information that standing alone has no economic value to other parties, but does have such value when aggregated with similar data from other parties.
The second provision – that the data be subject to reasonable efforts to maintain its secrecy – also finds problems in an environment where the data is continuously uploaded to another party without the intervention of the disclosing party. The fact that data is disclosed to another party does not mean it cannot be protected as a trade secret; if that were the case, there would be little need for much of trade secret law. Rather, the question is how and to whom the information is disclosed. An owner is not required to go to “extraordinary lengths” to maintain secrecy,k but must take reasonable steps to protect trade secret info from becoming generally known. The question becomes what constitutes “reasonable steps” to keep continuously uploaded data protected. Almost certainly this means there must be some form of agreement in place between the disclosing party and the receiving party regarding how the receiving party must treat the received information, including to whom (if anyone) the receiving party may disclose that information.
While an explicit written agreement is not necessary to claim trade secret protection, such an agreement is almost certainly a good idea. Not only can such an agreement clarify a number of issues unique to the relationship between the disclosing and receiving parties; it can also address numerous novel issues in the current information environment that trade secret law has not yet reached. In Part III of our series, we will discuss what should be included in a written agreement related to disclosure of big data.