Key data categories for agriculture, datasets and data standards

Based on consultations with the agricultural and open data community, 14 key data categories from government sources have emerged (Table 1). Each of the 14 key categories has been evaluated in terms of impact and effort. However, it is important to note the following.

1. Measuring impact in general terms is notoriously difficult; studies on the impact of open data are in many cases still under investigation. In this document the impact is assessed by indicating the potential use of the data by farmers and other actors in the agricultural ecosystem. The impact is linked to the different policy areas.
2. To estimate the amount of effort it takes to publish the data as open data the following questions have been considered:
• Is the data already being collected by a government for its own purposes, or does the government have a strong influence on the organisation that can make the dataset open?
• Is the data collected/available in many different countries around the globe?
• Is the data available or easily converted to a machine-readable format?
• Is only simple data cleaning or processing needed, if needed at all?
• Are there sensitivities that would prevent the data from being released: e.g. privacy concerns, financial interests etc?

A dataset does not need to be owned by a government. Datasets which are government-owned in one country may be held in the private sector in other countries. For example, there is a varied picture worldwide on ownership of national address registers. Some are held by central government, some by local agencies, and others by private providers. Regardless of ownership, this is still important data for policy makers to be aware of, and they should be thinking about how to increase accessibility of this data: e.g. governments can regulate to require that other people publish their data as open data. In the tables that follow we provide an overview of the expected impact in the different policy areas and ease of publication. Below, we describe the key data categories in more detail, addressing the following questions:

• What is the data is about?
• Why is it important for agriculture?
• Who can use this data and for what?
• What is the estimated effort to publish the data as open data?

There are also examples of implementation on the web and links to initiatives that support interoperability.

Key data categories and policy impact

Table 1: Overview of the 14 identified key data categories; the colours in the right-hand columns constitute a “heat map” showing the potential for impact: dark = high, medium = moderate, pale = low, white = no impact expected.