On-farm data collection in agriculture has changed monumentally over the last 10 years. As growers update equipment, many have the ability to collect their own digital agricultural data. This can include geo-referenced soil samples, “as-planted” data (selective hybrid or variety, and prescriptive seeding rates); prescriptive fertilizer, lime and pesticide applications; multispectral imagery capture (NDVI, NIR and RGB aerial photometry); and yield data.

BIG DATA: Know what you should ask about data collection and sharing before working with a data provider.

Producing this data, by definition, becomes a “big data” set. Big data can be described as extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially relating to human behavior and interactions.

Producers often question what to do with their data. Many are turning to companies that offer services to help analyze this information and provide applicable management solutions. When choosing a provider, ask questions and understand how they will use, analyze and potentially share your data.

Producers often question what to do with their data. Many are turning to companies that offer services to help analyze this information and provide applicable management solutions. When choosing a provider, ask questions and understand how they will use, analyze and potentially share your data.

What should I ask?
To learn how to use the data, Ohio State University Extension’s Precision Agriculture Department created a special website, A part of this department, OSU Extension ag engineer John Fulton offers some key points:

1. Ask questions before making a decision about sharing your data or signing up for a service. Before working with an agricultural technical and data service providers, obtain the company’s data privacy policy. The companies who have signed on to the Privacy and Security Principles for Farm Data know the waters can become murky when producers start sifting through privacy policies and consent agreement verbiage. As you choose your preferred provider, compare its privacy policies and consent agreements to ensure it aligns with the Privacy and Security Principles for Farm Data Policy.

2. Understand that as a producer, you should retain a personal copy of your precision ag data and, at minimum, organize by year.

3. Farmers own information generated on their farming operation. However, it is the responsibility of the farmer to agree upon data use and sharing with other stakeholders that have an economic interest, such as a tenant, landowner, cooperative, agriculture technology provider (ATP), etc.

4. Because it is important that growers be the ones in control of their own data, portability is key in moving that data and using it with a variety of other systems and platforms. Growers should have the ability to move data from one location to another, without penalty. It will be necessary for growers to review their contracts to determine which data is considered “anonymous or aggregated.” Sometimes it is difficult to interpret how data is classified, but having a positive working relationship with the ATP selected should aid in this process and make it understandable. Data portability is essential to using your farm data.

5. While some growers are comfortable with their farm data being aggregated and used as a marketing tool, others are not. Big data companies will have the ability to provide targeted marketing with information based on data collected similar to those seen online when searching for goods. Growers should be able to choose how their data is being used and sold to third-party data aggregators. By specifically reviewing the disclosure, use and sale limitations within an ATP contract, growers have the ability to make an informed decision about how their data will be used, on their own terms.

6. Within the agreement or terms and conditions between growers and their ATP, there should be an explicit statement regarding the prohibition of anticompetitive activities. If the contract does not specifically mention these unlawful or anticompetitive activities, one should be on guard for wording that could disguise these types of actions. For example, verbiage that mentions being exclusive to one particular ATP, discriminatory pricing practices that appear as pricing based on the amounts or quality of data being managed, and requirements that a grower must purchase additional services in order to use basic ones. By being knowledgeable about what activities constitute unlawful or anticompetitive behavior, growers can be better prepared when entering into contract agreements with an ATP.

The intended output from big data should always improve a farm’s bottom line and delineate which evaluated practice made a significant difference.

Johnson is a CCA and field agronomist in southern Ohio for DuPont Pioneer. Email him at [email protected].