How to overcome big data’s barriers


Credit: Flickr user Marcos Gasparutti

As I wrote earlier this week, data analytics technology has the potential to dramatically change the way we produce food, making it more abundant and sustainable. But a number of obstacles remain.

Here’s how we can address some of the biggest challenges and hasten ag’s big data revolution for the benefit of people and the planet.

1. Protecting privacy

Many growers have told me they are willing to share data – if they know exactly where it’s going and how it will be used, and if they can benefit from the data analysis that occurs. However, big concerns remain about data being used for regulatory compliance purposes, given to rival farmers, or shared with seed and fertilizer companies that would gain a competitive advantage.

We don’t need to reinvent the wheel to find solutions. Privacy concerns have long applied to fields such as taxes, retail sales data, and health records. We can and should learn from their experiences. For example, independent companies – rather than equipment, fertilizer, and seed companies – can manage data and ensure it stays in farmers’ hands, while still providing aggregated knowledge that benefits everyone.

Contracts and regulations around use and ownership are also essential. Last year, national ag groups met with big data companies to establish data privacy principles that apply to agreements between farmers and technology providers.

Credit: Flick user Pete Prodoehl

Credit: Flick user Pete Prodoehl

2. Integrating technologies so they speak the same language

Data connectivity between different platforms and tools is critical – but integration is largely lacking at this point. This limits adoption of precision agriculture tools and the ability to collect data at scale.

Again, we can learn from other industries. 4G wireless, for example, was developed through a specialized agency of the United Nations to ensure collaboration and integration with the multitude of companies utilizing the technology. An independent or government body could do the same for agricultural technologies.

Another emerging solution is the development of standardized application programming interfaces (APIs).  APIs are building blocks developed to exchange data between systems. For example, APIs allow your smartphone to exchange data with an “app” to give you driving directions or download a boarding pass. Examples of APIs that are currently used for agriculture tools include: Google Maps, AccuWeather, and USDA’s Economic Research Service.

3. Reducing Complexity

Collecting and formatting data is complex – and can take a lot of time. Growers’ data can include land records, seed receipts, weigh tickets, and yield monitors, to name a few. And most of the growers I’ve met with have their records on paper. Even though collecting data is important for economic and environmental reasons, getting started can be overwhelming.

Two key questions can simplify the wild world of data:

  • What data is most important for your operation? It’s nearly impossible – and often unnecessary – to collect data on every aspect of farm management. Deciding what’s most important to measure will narrow down your options for data collection.
  • Is someone else already collecting the needed data? For example, weather stations can give farmers info on precipitation – one less data point to collect. Furthermore, this data has been standardized making it easy for companies to integrate.

Fortunately, farmers don’t need to go it alone. Ag retailers and crop advisors are farmers’ primary source of counsel. According to Corn & Soybean Digest, 50 percent of farmers want their local retailers to provide help to monitor soil health and changes related to cover crops.

Sustain logoThis means ag retailers can also help growers make sense of the plethora of big data and precision agriculture offerings. Programs like United Suppliers’ SUSTAIN™ platform, which combines a set of proven, effective tools that improve nutrient-use efficiency and reduce soil erosion while enhancing productivity, are an effective way to support growers interested in data collection and sustainability. As part of the platform, ag retailers are trained on what data to collect in order to implement best practices for soil health and fertilizer efficiency – they then bring this information to the customers they serve.

Overcoming these hurdles will facilitate collection of massive amounts of data that can be analyzed to improve farmers’ bottom lines and benefit the environment.

Related links

Ag’s big data explosion can benefit the environment, too
A farmer’s perspective: 4 reasons why collecting data is important

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