Here’s how the agricultural sector can solve its data problem

Article by Satyanarayana Jeedigunta and Arushi Goel: “Food and nutrition security, skewed distribution of farmer incomes, natural disasters and climate change are severely impacting the sustainability of agricultural systems across the globe. Policy reforms are needed to correct these distortions, but innovative emerging technologies like artificial intelligence, machine learning, distributed ledger technologies, sensors and drones, can make a significant difference.

Emerging technologies need data, and it must be the right data, for the right purpose at the right time. This is how it can deliver maximum impact. Agricultural value chains comprise a complex system of stakeholders and activities. The enormity of the size and complexity of agricultural data, coupled with its fragmented nature, pose significant challenges to unlocking its potential economic value, estimated at $65 billion in India alone….

As such, there is a need to promote standards-based interoperability, which enables multiple digital systems to exchange agricultural data in an automated manner with limited human intervention. The ease and speed of such an exchange of data, across domains and technologies, would spur the development of innovative solutions and lead to evidence-driven, prediction-based decision-making on the farm and in the market.

Most agricultural data is dynamic

Most current efforts to develop standards of agriculture data are isolated and localized. The AGROVOC initiative of the United Nations’ Food and Agriculture Organization addresses a part of the data problem by creating an exhaustive vocabulary of agricultural terms. There is also a need to develop an open data format for the automated interchange of agriculture data. A coordinated initiative of the industry is an attractive approach to develop such a format…(More)”.