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Data Law: Questions and answers.


You stated that data law is currently reactive rather than proactive. Can you cite an example?

The law is classically always playing catch-up to new issues. The process is cyclical and usually comes about in a variation of the following cycle: existing law fails to directly address a societal or technological issue, court system tries to address the issue with current laws or common law system, Government creates statutory and/or regulatory schemes in order to codify a particular way to examine legal issues. All endeavoring to be broad enough to encompass a vast variety of fact patterns.

The concept of stare decisis then applies precedents of these codified schemes to real-world fact patterns and which creates more precedent for future cases. Stare decisis applies decisions from past fact patterns to current ones and some persuasive court wording may even contemplate future fact patterns (the proverbial square peg in a round hole problem).

The problem with this current structure is the time-lag in implementing a legal scheme where there has been no cases, statutes, or regulations promulgated, and therefore no precedent to go off of, particularly where technology changes extremely rapidly. This is especially the case where traditional or “old” legal concepts, such as property law, meet a revolutionary new concept or fact pattern such as data ownership. The intertwining of a classical area of law in property law meeting the new concept of precision ag. data brings about a new kind of problem; whether we apply classic property concepts to new technologies and legal issues or divert and form another specialized legal scheme.

To illustrate, consider the classic property law theory that if something is tied to the land, whoever owns the land owns the thing tied to it (unless there’s some contract, agreement, or writing specifying otherwise). This holds true with regards to mineral rights, water rights, some aerospace rights, crops that might be growing on the land, the soil itself, any improvements made on the land, etc. We all know these property interests can be contracted away, but what about precision ag. data gleaned from the process of growing crops on a particular piece of land? Applying strict property law concepts, the data was gathered from the land and without that piece of land the data is arguably much less valuable. Simultaneously, without that piece of land, the data would not have been gathered. The question is the data gathered from a particular piece of land inherently a part of the property rights associated with that particular piece of land or, rather, is the data a product of the gatherer’s time, labor, and investment? A specific example in Ag. Data law as it relates to landlord/tenant issues is the statute for farmland leasing in Kansas, K.S.A. 58-2506, K.S.A. 58-2506a, and K.S.A. 58-2531 which do not address anything relating to ag. data. Further, I am unaware of any cases in any state or jurisdiction where the ownership of ag. data has been adjudicated or even raised as an issue. To that end, it seems that farmers and landlords are unaware of any potential dispute arising from the ownership interests in data collected from the land. My opinion is that the value of the data is entirely overlooked. There may also be some preconceived notions where they simply think, “Well, of course, the data is mine, I bought the equipment, I gathered it, it’s mine and no one else’s.”

You stated that it was both good and bad: Good because you set your own standards – such as? Other legal areas where this has happened?

Good - because people are free to contract their rights in the data however they may see fit, but the bad part is it is not exactly clear what those rights are and who has them, i.e. if one party would have inherent rights in the data, it’s arguably unnecessary for them to contract their rights. It’s also good because hopefully farmers and landowners and attorneys can come up with their own standards rather than having standards forced upon them by government or courts.

By far the best way to protect your interest and access to this data is to property contract for it. This includes with all custom operators you share it with, contractors that handle the data collection itself, with landlords or tenants, and in the licensing and user agreements with the software and hardware vendors or the equipment used in data collection.

Absent a contract a farmers best method currently to protect the data would be to assert it is a trade secret. The concept of a trade secret as property evolved out of common law and then was codified in the Uniform Trade Secret Act (UTSA). Under the UTSA, a trade secret is defined as “information, including a formula, pattern, compilation, program, device, method, technique, or process, that: (i) 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 (ii) is the subject of efforts that are reasonable under the circumstances to maintain its secrecy.” The origins of a trade secret as a property right under common law became such a disputed issue that, over time, it was codified into a statutory scheme. It seems as if the concept of codifying common law and the concept of establishing precedent could abstractly be considered a “chicken before the egg” scenario where although the origins of the codification are from the common law (essentially using precedent from previous cases to determine outcomes as it applies to new fact patterns), we still go back to using precedent to interpret the codification and apply it to different fact patterns to reach outcomes. An overriding theme to this process is that when drafting contracts and agreements, attorneys and sophisticated parties can use precedents established in caselaw as well as statutory and regulatory guidance to fill in any gaps, “loopholes”, or to address uncontemplated fact patterns.

Bad – lack of direction: Any chance of international laws being used as precedence?

I think the biggest area that may have some impact would be disputes over the data internet companies gather on individuals, simply because this is vastly more common and probably more impactful on “ordinary” people. The fear is that an analogy might try to be drawn between the type of data collected on individuals by internet companies and the type data collected during farming practices. I think that is an entirely inaccurate analogy to draw. The way to illustrate why that is an inaccurate analogy is that some California court may create a precedent used on Silicon Valley companies who are collecting internet browsing data, then other courts may try to implement that same precedent on farmers collecting precision ag. data from cropping systems. It is simply two entirely different problems with two entirely different solutions, but since many attorneys, judges, and legislators lack agricultural knowledge, they will likely read the word “data” in the Silicon Valley case and automatically assume “data” in this precision ag. data dispute case from rural Kansas should be decided the same way. Agricultural law is often the law by exception. In almost every area of the law there are exceptions for agriculture.

As far as using international law goes, one of the blessings of living in the United States is that we live in a country where individual property rights are very well protected in comparison to other countries and along with that, a vast majority of property laws are enforced, determined, and applied at the state-level jurisdiction rather than federal. Furthermore, international law concepts are merely persuasive in application to individual property rights in the United States.

Is the primary legal knot to untangle in the landlord/tenant & partnership areas?

I think that is where most of the potential for disputes could arise, simply because there are so many farmer-tenants who have to keep landlords satisfied and partnership/entity formations with multiple members who have differing opinions on how the operation should be run. When you have two or more persons who have differing ideas on how property should be owned or shared, there is much more potential for disputes. Even on a “smaller” level, in a LLC, Partnership, or Corporation situation disputes can come about and a decision needs to be made as to who may have access or ownership rights in the data collected. The key in a leasing situation is that in one respect, the landlord probably has rights to the data because they own the land it was collected off of, however, the farmer also has rights because they are the ones investing in the equipment and using their labor and time to compile and use the data. To determine who has a claim in what, the type of lease is one of the biggest deciding factors. In a pure cash-rent leasing situation, the landlord has no skin in the game (as it relates to investment in equipment or in the potential returns on investment) whereas, in a sharecropping lease arrangement, the landlord likely has more ground to stand on because they do have skin in the game as it relates to the potential return on investment from implementing the technologies.

Can you give three examples of agronomic data? Would that be soil, fertilizer and such?

There are so many different examples of agronomic data being collected by farmers today. Just a few are weather data (temperature, humidity, wind speed, precipitation), soil data including fertility levels, ph levels, electroconductivity, moisture levels, planting date, seeding population, plant population, seed variety, pesticide application rates and dates. There’s also variable rate fertilizing, variable rate seeding, variable rate irrigation, and infrared imaging using drones to assess plant health throughout the growing season. Even tissue sampling can be used and implemented during a growing season. The “daddy of them all” is the yield data when the crop is harvested. The yield data is the final result that gives you a look at the impact of the different management practices used during the growing season. All of these can be put into maps that you can stack on top of each other to give you a baseline for the field and then can be used to improve management decision for the next year and subsequent years. The key is that all of these maps can offer minute by minute data gathering with sub-inch accuracy.

Many farmers are meticulous in what they input into these maps i.e. planting date, variety, seeding population, plant population, soil type and fertility levels, etc. I believe the future of the implementation of all of these different data gathering and implementing tools is that their implementation limits a farm’s potential productivity and profitability to a few factors: weather, market prices, and disease/insect pressures. One of the most important things to consider with all of these tools is proper calibration of the technology used to collect the data. If the equipment used in gathering the data is not properly calibrated, the final results are not going to be accurate or precise.

Often we get caught up in viewing the importance or value of data’s use for farmers, but the data’s use can be extremely important for crop insurance, USDA farm program base yields, and, even more interesting, to seed companies who are developing hybrids and varieties. The data’s value for seed companies is that it is real world research and development “experiments” on hybrids with real world conditions and management practices that are logged with minute-by-minute tracking and sub-inch accuracy. In contrasts, thinking about it from the technology developers and equipment companies’ perspective, they do not necessarily have a stake in what yields a farmer is getting from his crops, but rather how they can improve the technology/equipment’s use, functionality, and user-friendliness.

How would the previously mentioned groups share the data? Through what means?

They can share the data either through electronic formats with software or through hard copy data reports with maps and table data. Either way, there is likely also cloud systems backing the data up. The key is to have some documentation on who may view the data or who may share it. Non-disclosure agreements or licenses to view or disclose would be good documents to have in place as well as leases or operating agreements that detail these disclosures or licenses. Are the companies that developed and sold the software and hardware keeping copies of the data for their own use and sale? If so is it specific and identifiable to a particular track of land or is the data aggregated, and if so is it done county by county, statewide, or some other pool.

How would the previously mentioned groups share the data? Through what means?

They can share the data either through electronic formats with software or through hard copy data reports with maps and table data. Either way, there is likely also cloud systems backing the data up. The key is to have some documentation on who may view the data or who may share it. Non-disclosure agreements or licenses to view or disclose would be good documents to have in place as well as leases or operating agreements that detail these disclosures or licenses. Are the companies that developed and sold the software and hardware keeping copies of the data for their own use and sale? If so is it specific and identifiable to a particular track of land or is the data aggregated, and if so is it done county by county, statewide, or some other pool.

Why would they elect NOT to share data? Is there a certain type of data that would be unfavorable to share between partners?

The issue with disclosing the data is that often times the data is reflective of a farmer or land’s productivity, so the data represents a competitive advantage. If the data is disclosed, a farmer could be in jeopardy of losing a competitive advantage he or she may have on a piece of land. The classic example would be where a farmer “1” farms “X”x piece of ground for landlord “A” and a competing farmer somehow gains access to the data gathered, then approaches landlord “A” saying how he or she could produce more on that piece of land or outbids the first farmer resulting in the landlord terminating the leasing agreement with farmer “1” and entering into a leasing agreement with farmer “2”.

Furthermore, any sharing or disclosure of data by farmer “1”, even to trusted sources or custom operators, could jeopardize farmer “1’s” argument that the data was a trade secret and therefore lose the trade secret defense as a claim to the data. A trade secret infringement suit could protect farmer “1’s” interest in the data and investment in the technology used to gather the data (when thinking of a trade secret claim, think of the Coca Cola recipe, if Coca Cola disclosed the recipe, they could lose their claim that the recipe is a trade secret – that the recipe represents an economic advantage). Additionally, farmer “1” could argue that farmer “2’s” use of farmer “1’s” gathered data represents unjust enrichment because farmer “2” is using farmer “1’s” investment of time, equipment, and labor to get a leg up or head start on farming of the land because farmer “2” now has a solid baseline of the land’s productivity, fertility/variety needs, and capability. Again, the type of lease would likely be a factor in determining who has what interests in the data.

Trade Secret Determination Example from presentation:
Say Farmer “B” obtains data Farmer “A” compiled while farming leased land. Farmer “B” evaluates the data and determines he or she could produce the land more efficiently or profitably than Farmer “A”. Farmer “B” presents this information to the owner of the leased land, bidding the lease of such land away from Farmer “A”. Courts have noted just because secret information is of value to its owner does not mean it has value to others. Instead, the economic value element of a trade secret determination requires the farmer's economic interest derives from others not knowing the information. Whether or not a real-world Farmer “B” exists may not matter for purposes of a trade secret determination, as at least some cases require "only that there be actual or potential value from the information being secret" although Farmer “A” might also have to prove Farmer “B” is indeed a competitor.

The same issues can be used in a defense against sharing data with a partner or member of an LLC or corporation. Again, the importance of non-disclosure agreements, operating/partnership/corporate agreements, or licenses are important to protect the economic value of the data are important even in situations dealing with an entity.