The role of government

Governments can take a number of different roles in supporting open data for agriculture. The possibilities include: supporting capacity building for end users in the agricultural sector to receive and use information services; supporting information service providers financially or with knowledge to use the information sources; enforcing the national technical infrastructure; building networks of organisations supporting the information chain; supporting sustainable business development; and encouraging other stakeholders (e.g. private sector, international organisations, NGOs, researchers) to publish their data or to use open data from government and other sources to become more efficient.

Governments collect and generate enormous amounts of data to develop and monitor policies, and/or provide information and stimulate developments. The purpose of this document is to encourage governments to start publishing their own data, to support the agricultural sector and food security as a whole.

We identified six policy areas where open government data can make a difference. The list of these areas was developed from desk research and discussions with policymakers; it is not exhaustive, but provides a starting point and inspiration for developing a country- or region-specific open data strategy for agriculture. Considering the diversity in agricultural practice and the variations in environmental conditions and socio-economic contexts across the globe, it is unrealistic to provide a prescriptive blueprint for action. The strategy (and policies) depend on the different needs and objectives in a country. Therefore, an open data strategy needs to be designed in consultation with the different actors and stakeholders in the agricultural sector and open data community (see also identifying local needs and opportunities in section 3).

Connecting agriculture data to user needs: 6 policy areas

1. Empowering the farmer. Farmers (especially smallholders) often have less access to information than other more specialist actors in the value chain, e.g. traders or input suppliers, etc. This may be because of their education level, but even more so because of the remoteness of many rural areas, the relative immobility of the farmers, and the many things farmers need to know. The combination of open data and mobile information services can help to overcome this power imbalance. Relevant data for farmer empowerment includes actual and historical market prices, physical infrastructure and its condition, the location of licensed organisations, permitted chemicals and land ownership.
2. Optimizing agricultural practice. Government extension services possess a lot of data on agricultural best practices. By providing agronomic data as open data and supporting public or private information service development, the information can be more widely spread and many more farmers can benefit from the latest agronomical insights. This information includes data on crop selection, farm management, early warnings, and sustainable production methods, but also environmental data such as weather forecasts, climate change predictions, soil data, altitude data and hydrological data.
3. Stimulating rural finance. The price of financial services for farmers is strongly dependent on the risks assumed by financial institutions. These institutions (whether microfinance institutions or banks) require information on local price history, regional production figures over time, regional farm profiles, regional growing conditions, local crop characteristics, climate change predictions, and extreme weather events to set out financing strategies, and accurately estimate risks while lending to or insuring clients.
4. Facilitating the agricultural value chain. The agricultural value chain is the whole range of goods and services necessary for an agricultural product to move from farm to consumer. Actors in one part of the value chain need to know about performance in other parts of the value chain in order to make decisions such as whom to do business with, or how to comply with the quality standards in different markets. Key datasets include regional production figures over time, regional farm profiles, registered companies, and the condition of transportation infrastructure.
5. Enforcing policies. Many regulations result in lists of items or organisations that are permitted, licensed, restricted or forbidden. Having this data and the related legislation openly available can lower administrative costs, promote internal collaboration between different government agencies, and enable third-party services to make this information easily accessible for actors in the agri value chain to act upon. Relevant datasets include land registration, licensed organisations (corporations, businesses, NGOs), safety inspection results, import/export tariffs, and permitted crop protection products.
6. Government transparency and efficiency. Donors, policymakers, beneficiaries, and civil society require data on government spending in the agricultural sector to promote more efficient decision-making, equity and prevent corruption. Relevant data includes government spending, subsidy distributions, and rural development projects.