INTRODUCTION II. BACKGROUND A. The Development of Agricultural Technology Providers B. Agricultural Technology Providers' Benefits for Farmers C. Who Owns the Data? Farmers' Concerns Regarding Data Privacy D. Categorizing Agricultural Data Under the Current Legal Framework 1. Analyzing Agricultural Data Under the Trade Secret Regime 2. Examining the Uniform Trade Secrets Act and the Defend Trade Secrets Act of 2016 E. Analyzing Analogous Social Media User Agreements III. ANALYSIS A. The Future of Agricultural Data: Legal Uncertainties 1. In Support of an Open Data Sharing Policy: How Iowa's Policies Have Attracted Data Aggregators and Aid Impoverished Nations 2. How Agricultural Data is being Used Around the World by Scientists to Combat Climate Change B. Analyzing Agricultural Data Under Current Legal Regimes: Applying the Trade Secret Factors 1. The UTSA Application & Iowa's Interpretation 2. Protections and Limitations of the Defend Trade Secrets Act 3. Distinguishing Traditional Trade Secret Analysis and Data Aggregation's Applicability C. Responding to Farmers' Data Security Concerns 1. Independent Competition: Farmers Have Options 2. Analyzing Privacy Agreements and hiQ's Holding as Applied to Agricultural Data IV. RECOMMENDATION A. Free Speech Data Sharing Versus Standard Third-Party Data Aggregation: Data Aggregators' Reliance on the HiQ Framework Would be a Mistake B. Protecting Innovation in the Marketplace: Courts Should Interpret Agricultural Data as a Trade Secret C. Advertising the Social Benefits of Data Aggregation V. CONCLUSION I. INTRODUCTION
Today, agricultural data technology innovations have yielded major benefits for farming efficiency. However, those innovations come with a host of privacy and data concerns for local farmers that has left Congress at a standstill for a resolution. (1) Collaboration with "big data" companies provides farmers with invaluable levels of information for their farming needs, but also spurs concerns that farmers are sacrificing too much control over their own private farming data. (2) A variety of "big data" companies are trying to ease some of these concerns by compromising on a solution that leaves farmers satisfied with the level of control over their data without sacrificing the benefits of open sharing of data. (3) As such, there are a variety of important property ownership issues that courts will have to resolve as this data technology becomes more commonplace. This Note will explore these legal issues while recommending that data companies aggressively engage farmers privately through contract to avoid future litigation.
Part II discusses the background and historical development of agricultural technology providers and how advancements in data storage and the rise of third- party data aggregators have created a host of complicated legal concerns for farmers and agricultural technology providers. Part III analyzes a variety of opinions related to advising farmers on proactively confronting these issues and how data aggregators can ease their privacy concerns. Part IV recommends contract provisions and introduces policy arguments for why data companies should aggressively advocate for the mutual benefits of open data sharing with farmers.
This Note first examines the advancements in agricultural technology and introduces the legal issues these advancements created. It then explores how farmers have benefitted from this technological advancement while also introducing key issues of data privacy. Finally, this Part introduces Iowa's interpretation of uniform trade secret laws and their potential applicability to agricultural data providers.
The Development of Agricultural Technology Providers
Before examining the legal issues surrounding big data and agricultural technology providers, it is first necessary to examine certain key aspects and background information regarding the technology. Precision farming is a method that links information for crop-planting conditions to digitally operated farm equipment. (4) One of the key methods of precision farming is yield monitoring. (5) Yield monitors use electronic sensors and a computer coupled with a combine to transmit data to agricultural technology providers. (6) Additionally, a precision method known as grid soil sampling allows farmers to examine the nutrient status of their fields. (7) Precision grid sampling in particular provides farmers with digitally generated grids of their own fields and recommends techniques, such as fertilizer application, specially tailored to each farmer's precise needs. (8) Agricultural technology providers both store and analyze this data so that farmers can implement the provider's suggestions. (9)
Today, venture capitalist investment in agricultural technology represents a $25 billion industry, and is only continuing to grow. (10) In Iowa alone, agricultural data is a $300 million industry. (11) The aforementioned technology allows farmers to maximize their farms' potential by using data to know what crops to plant and how to plant them. (12) According to the 2012 USDA Agricultural Resource Management Survey, more than 62% of corn and soybeans were harvested using advanced agricultural technology providers, which are most commonly referred to as "big data." (13)
What exactly defines agricultural data has been a subject of debate for both lawmakers and policy experts. (14) Examples of agricultural "big data" include weather data sets, satellite imagery of farming areas, crop insurance records, and a variety of aggregated farm data. (15) This is distinguished from information that will likely never qualify as agricultural data such as farmers' financial records, logistics, and work schedules. (16) These distinctions could make a difference in determining what legal rights farmers have to proprietary information stored on data systems. (17) However, the most challenging issue facing legal experts may not be how to classify the data, but how to ensure farmers retain confidence in an evolving industry rife with legal and security uncertainties. (18)
Agricultural Technology Providers' Benefits for Farmers
Although farmers remain skeptical and cautious about the data security concerns posed by agricultural data providers, they are reaping many benefits from the technology. (19)
Major agricultural producers such as Monsanto, John Deere, SST Software, and DuPont Pioneer have embraced this agricultural revolution through substantial investments. (20) In 2012, Monsanto bought FieldScripts services, which allows farmers to specifically tailor their individual farming needs using hybrid seeds. (21) Monsanto spent $1 billion on the company's database which contained topographical maps of 25 million American fields along with weather simulation modeling systems. (22) Although companies like Monsanto and John Deere are usually considered the predominant agricultural technology providers, start-ups are also beginning to enter the industry. (23) For example, start-up agricultural data provider Farmer Business Network, a company of 37 employees, (24) allows farmers to submit their own farm data to the company to compare information with farmers nationwide. (25) using this data, Farmers Business Network advises farmers on how to find the best seeds for their soil and view a "Consumer Reports-like review of hundreds of agricultural products." (26) In addition, free software start-ups like 640 Labs have offered farmers a cheaper alternative in the agricultural data market. (27) 640 Labs uses freely available rainfall totals available on sites like the National Weather Service and geographic data from Google Maps to advise farmers. (28) Furthermore, non-profit organizations like AgGateway allow agricultural businesses to join their community and submit their agricultural business plans for review by their experts. (29) AgGateway then hosts annual conferences, which provides farmers with information on recent advancements in agricultural data practices and hosts networking opportunities for farmers. (30)
Additionally, the open sharing of agricultural data has prompted the development of tools like ADAPT which bring the benefits of interoperability to agricultural data platforms. (31) Interoperability is the "ability of computerized systems to connect and communicate with another readily, even if they were developed by widely different manufacturers in different industries." (32) In the past, critics have claimed that one of the downsides of precision agriculture was that compatibility among the platforms was not "user-friendly" for farmers. (33) Specifically, companies' systems, like John Deere's big data system, APEX, were incompatible with most other big data systems and their privacy agreements stated that farmers do not own their own data. (34) Describing the problems of compatibility, Open Ag Data Alliance founder Aaron Ault stated, "One of the reason [s] is nothing works together today. One company's stuff doesn't work with others, one has a way of handling data, another one doesn't." (35)
Today, platforms like ADAPT are committed to improving connectivity across platforms. (36) Through open-sharing of software data, farmers easily transfer agricultural data applications across different platforms. (37) This type of connectivity helps farmers who now work primarily from phones and tablets. (38) Furthermore, programs like FieldScripts helped increase farmers corn yields by five to 10 bushels per acre while relying on the open-sharing of data. (39) Similar developments are occurring internationally as well. (40) In Europe, organizations such as the Wheat Data Interoperability Working Group have committed to the open sharing of agricultural wheat data to "promote ... wheat data sharing, reusability and operability." (41) Researchers, growers, breeders, and data users alike use this framework to openly share data to improve wheat harvesting. (42)
Who Owns the...
Forecasting Change: Examining the Future of Agricultural Data Processors and Ownership Rights.
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COPYRIGHT GALE, Cengage Learning. All rights reserved.
COPYRIGHT GALE, Cengage Learning. All rights reserved.