{"id":5542,"date":"2015-10-07T16:50:23","date_gmt":"2015-10-07T20:50:23","guid":{"rendered":"http:\/\/blogs.edf.org\/growingreturns\/?p=5542"},"modified":"2025-06-11T12:50:34","modified_gmt":"2025-06-11T16:50:34","slug":"how-to-overcome-big-datas-barriers","status":"publish","type":"post","link":"https:\/\/blogs.edf.org\/growingreturns\/2015\/10\/07\/how-to-overcome-big-datas-barriers\/","title":{"rendered":"How to overcome big data\u2019s barriers"},"content":{"rendered":"
\"21842202345_e287f71cc9_b\"<\/a>
Credit: Flickr user Marcos Gasparutti<\/a><\/figcaption><\/figure>\n

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

Here\u2019s how we can address some of the biggest challenges and hasten ag\u2019s big data revolution for the benefit of people and the planet.<\/p>\n

1. Protecting privacy<\/strong><\/p>\n

Many growers have told me they are willing to share data \u2013 if they know exactly where it\u2019s 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.<\/p>\n

We don\u2019t 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 \u2013 rather than equipment, fertilizer, and seed companies \u2013 can manage data and ensure it stays in farmers\u2019 hands, while still providing aggregated knowledge that benefits everyone.<\/p>\n

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

\"Credit:<\/a>
Credit: Flick user Pete Prodoehl<\/a><\/figcaption><\/figure>\n

2. Integrating technologies so they speak the same language<\/strong><\/p>\n

Data connectivity between different platforms and tools is critical \u2013 but integration is largely lacking at this point. This limits adoption of precision agriculture tools and the ability to collect data at scale.<\/p>\n

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.<\/p>\n

Another emerging solution is the development of standardized application programming interfaces (APIs).\u00a0 APIs are building blocks developed to exchange data between systems. For example, APIs allow your smartphone to exchange data with an \u201capp\u201d 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\u2019s Economic Research Service<\/a>.<\/p>\n

3. Reducing Complexity <\/strong><\/p>\n

Collecting and formatting data is complex \u2013 and can take a lot of time. Growers\u2019 data can include land records, seed receipts, weigh tickets, and yield monitors, to name a few. And most of the growers I\u2019ve met with have their records on paper. Even though collecting data is important<\/a> for economic and environmental reasons, getting started can be overwhelming.<\/p>\n

Two key questions can simplify the wild world of data:<\/p>\n