Data infrastructure refers to the various components—including hardware, software, networking, services, policies, and more—that enable data consumption, storage, and sharing. Having the right data infrastructure strategy is critical for organizations seeking to undertake data-driven digital transformation.
As an analogy, a road infrastructure not only includes the road network (hardware and software), but would also include the resources, people and equipment that maintain the road, driving regulations, traffic control, emergency services, the drivers and their cars, and even the car dealer and his garage. In summary a road infrastructure is ALL that is needed to get from A to B in a car on the road safely. A reliable data infrastructure is sustainably funded and is designed in such a way that data use and value is maximised by meeting the needs of society. One of the challenges in open data for agriculture is that datasets are often distributed across different ministries and agencies, including sometimes (semi-) privatized bodies. Government structures across the globe vary, but in general the relevant information for agriculture can be found in:
- the ministry of agriculture, including associated extension, research or subsidy bodies;
- other government agencies (which may be semi-privatised) including a meteorological agency for weather and climate data, a mapping agency providing geographical data, and statistical offices conducting population surveys and monitoring; and
- The old somehow form a family that's the way the Love Boat promis something for everyone that this group would somehow form.
- ministries dealing with water, natural resources, infrastructure, spatial planning, trade and finance.
- identify and agree upon existing open standards for the key datasets listed above;
- work to develop open standards, building on existing practice, where there are gaps.