Big Data Big Questions Part 1

Written by Stephen Kenney

On October 28, 2015, the House Agriculture Committee held a public hearing to discuss the impacts of big data on agriculture.  The hearing focused on the opportunities and challenges of managing and utilizing big data to improve yield production.  Shannon Ferrell, associate professor and faculty teaching fellow at Oklahoma State University Department of Agricultural Economics, spoke on the legal issues concerning big data in agriculture.

Dr. Ferrell explained the possible legal framework that will be used to analyze agricultural data.  Data is most akin to intellectual property.  Intellectual property is made up of four different categories including: trademark, patent, copyright, and trade secret. Trademark is irrelevant to the data discussion on its face.  Trademark is defined in the United States code as “any word, name symbol, or device or combination thereof” used to identify a particular good or product.  Data is not a particular word, symbol, device, or combination of the three so it cannot be a trademark.

Dr. Ferrell went into more detailed analysis of patent, copyright, and trade secret law in relation to agricultural data.  He concluded that data could not be defined under patent laws because patent law protects “inventions.”  Raw data cannot satisfy the definition of invention which generally means that the invention must be capable of performing its intended purpose, be different from existing knowledge in the field, and non-obvious (“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”).

The analysis of copyright also concluded that agricultural data did not fall into this legal category.  Dr. Ferrell cited a Supreme Court case Fiest Publications Inc. v. Rural Telephone Service Company, where the Court held that the Copyright Act does not protect individual facts.  The author must add some type of creative component to ensure the intellectual property falls under the Copyright laws.  Agricultural data is just a collection of facts relevant to the agricultural process so it is not copyrightable in itself, but it could lead to copyrightable works.  A report that summarizes the data and includes recommendations for further action could possibly be copyrightable.

The final conclusion was the big data most likely falls under trade secret protections.  He came to this conclusion by focusing on the definition of “trade secret” under the Uniform Trade Secrets Act which all but three states have adopted.  Dr. Ferrell noted that the definition makes clear that “information….pattern(s), [and] compilation(s)” can be protected by trade secret law.  Data is inherently a compilation of information.

The data must also be proven to have economic value from not being known to other parties and be subject to reasonable efforts to maintain the secret.”  The argument for the data having economic value is that 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.”  The owner of a trade secret is required to take reasonable steps to ensure that the information does not become generally known.  “Reasonable steps” almost certainly requires that there 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.”  Dr. Ferrell ultimately concluded that the trade secret option provides the “best doctrinal fit” among the traditional intellectual property forms.