Given that the world’s population is expected to reach 9 billion by 2050, while the amount of arable land remains roughly the same, there is little doubt that agricultural productivity, especially at smallholder farmer level, will have to be improved.
Data has always been used to develop the information and knowledge that is applied in farming. However, data about agriculture itself, nowadays, can come from multiple sources. For example, remote sensing information does not come solely from satellite sources, but is increasingly complemented by information captured by UAVs, automatic weather stations and sensors located in the field. Data about the social and transactional aspects of agriculture is generated in the form of ‘big data’ through the use of computers, mobile phones and GPS devices. Thus, the term ‘data-driven farming’ is being used, rather than ‘knowledge-based farming’, to reflect the speed at which we are able to process data and the volumes of data from various sources that can be incorporated into decision-making in agriculture.
Agricultural stakeholders have realised that making data relevant to agriculture and nutrition available, accessible and usable can help policymakers, farmers and the private sector collaborate in achieving more sustainable agriculture. Hence the establishment of the Global Open Data for Agriculture and Nutrition (GODAN) initiative back in 2013. While the platform advocates for open data, it also addresses the concerns that are expressed by stakeholders about access to their data, or data that can be linked to them. Thus, CTA has joined the conversation around establishing a suitable regulatory framework on data standards, data quality and data sharing to effectively support the smallholder within the initiative.
But will the farmers themselves have to deal with a mass of data? Not necessarily, if we also develop the tools that make use of this data to generate the information needed by the farmer. The kinds of services that data-driven farming provides include, delivering access to more efficient and cheaper payment and savings tools through mobile financial services, bringing weather forecasts to actors throughout the agriculture value chain, and providing real-time pricing information to small-scale producers. These services, coupled with data analytics can be leveraged to make agriculture more precise, productive, resilient, and profitable.
Improving productivity at the smallholder farmer level requires any data and information shared to complement the farmer’s knowledge of the local environment and lead to a desired change in behaviour. However, in the context of climatic shocks and a changing environment, the farmer will have to make decisions based on his/her best informed judgement and their learnings from the practical experience may need to be shared. Thus, there will be cases where the farmer becomes the source of data for such data-driven farming initiatives based on indigenous knowledge!
CTA’s February 2017 issue of ICT Update addresses the topic of open data for agriculture and nutrition (https://tinyurl.com/myn7so6).
Another initiative that may be worth following, on a related topic, is the current global call for the data-driven farming prize, which is seeking innovations on how to apply open data to address the needs of the agricultural sector in Nepal (http://datadrivenfarming.challenges.org/)
