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Agriculture needs DATA, Farmers need INFORMATION

The word “DATA” comes from the Latin word “datum” which means ‘something given’. The innate nature of this word “DATA” has been to be open to all and yet be transformational. All of the knowledge that has ever existed hid in the plain sight as Universal Truths, and by merely transcribing it humans started claiming the ownership of this knowledge.

What if the first man to sow seeds would have kept the knowledge within his family tree?, Would it have created a monopoly controlling the global agri-produce? The answer is no, agriculture developed independently in almost 11 different civilisations across the globe. The foundation for shared knowledge in Modern agriculture was laid when the growing populations of farmers began linking to one another via trade networks.

For the past few decades we have been focussing on feeding the ever growing planet. This has put a burden on farmers and made them believe that an excess of fertiliser or pesticide will always be better than improving the practices on farm. There are actually two extreme scenarios of how agriculture could look like in future (1) a vertically integrated system where the power is consolidated in the hands of few and farmers are a mere workforce or (2) small collaborative groups where the farmers and agri-partners rely on each other letting the market forces drive the economics.


Data - especially open data - will play a crucial role in navigating and thriving through the challenges that exist and some which are unannounced. The data can power a full stack of technologies in soil and environmental conditions monitoring, Artificial Intelligence (AI), cloud computing, and the Internet of Things (IoT), to accurately measure the variations of variables in the crop field and improve the quantity and quality of agricultural products. These datasets include weather data, data on crop phenologies, data on environmental conditions, and soil data.

But we need to answer one question how is data and information different here?

For eg. - Weather forecast on the mobile phone is as available to an urban dweller as to a farmer. You might want to look at the forecast before you carry an umbrella, thereby deriving the information you need from the weather data. But for farmers just a look at the data might not help, they need tailor-made processed information, to plan their planting season and possibly increase their yield by reducing the risk of disease or drought damaging their crops. Farmers also optimise their water irrigation system to prepare for rainy or dry days and not over water or neglect watering their crops. So it should be easier done than said, but no the problem is lack of publicly available data, improper data collection standards, and restricted data sharing. Most of the experiments is done on individual farms, and the data obtained cannot be generalised for n number of agro-climatic conditions. Also it is very illogical that while the data might be open-source(eg. satellite data from NOAA) it is not provided for free to use. The problem is very early monetisation even when the models and algorithms are not properly developed. Adoption of an open source culture in agricultural analytics will allow easier sharing and evaluation, benefiting all, from farmers to developers, manufacturers and research organisations. This will solidify our knowledge on existing practices, which can drive down the cost, increase yields and promote sustainable resource usage.


Agree to disagree that institutional efforts regarding data governance, privacy or ownership are no less important. However, a higher availability of open data is not only necessary to meet the objectives of food security policies or production sustainability, but also to ensure a future where smart agriculture is based on openness and collaboration.


#opensource #iot #ai #technology #dataanalytics #agtech #launchingsoon


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