These add to the widely used FAIR principles indicating that open data should also be data that is Findable, Accessible, Interoperable, and Reusable. Making agriculture data open facilitates the development of solutions to food security in ways that would otherwise be expensive, time intensive or impossible. Impacts from open data include:
- enabling more efficient and effective decision making by stakeholders at all levels, from smallholder farmers to policy-makers;
- fostering innovation that everyone can benefit from – as a raw material for creating new services, insights, and applications;
- driving organisational and sector change through transparency in food production chains, and by openly measuring progress against targets.
Many different actors exist each contributing to the food security challenge from their own perspective. Sharing data means that actors in the agricultural sector can start making more informed decisions, making the sector run more smoothly and contributing more to the food security challenge. However each of the potential end users of open data will have different data needs. As an example: a smallholder farmer needs information at a plot level to make operational or strategic decisions on when to plant what crop and how to manage these crops on his or her farm. A financial service provider or a trader needs a more general picture on the agricultural risks or harvest successes in a particular region to determine a strategy for their operations. More studies demonstrate the impact of open data for agriculture. Governments can play a pivotal role by publishing relevant datasets and making sure they are ready for reuse.
Open data for agriculture should not be seen as a development on its own, but is part of a much broader development: the E-agricultural Transformation. E-agriculture is an emerging field focusing on the enhancement of agricultural and rural development through improved information and communication processes.This includes the usage new and traditional communication devices such as mobiles, fixed telephones, televisions, radios to convey information; decision making tools such as models, artificial intelligence and data mining techniques and all kinds of data coming from sensors, end users and other resources to improve decision making in the agricultural value chain. E-agriculture continues to evolve in scope as new ICT applications continue to be harnessed in the agriculture sector. [Government] open data feeds the pool of information that can be used to develop information services and decision making tools for stakeholders in the agricultural value chain.