The Datatalouskasvattamo project aims to provide training and support to service providers and farmers interested in using data from the agricultural sector. Different roles can be identified in the agricultural data ecosystem. These roles can be roughly divided into data producers, data holders and data users. On this page we try to gather information on examples of use cases, on data economy business models, fair data economy and technical solutions to implement data ecosystems for both data producers and those who process and use data.

The data economy is an area of the economy where the collection and use of data is an important part of business. An effective data economy requires organizations to have the capacity to manage data, the ability to collaborate in so-called ecosystems, and the ability to share data that can be scaled up in other contexts. Agriculture is a large sector, and farming and primary food production are highly mechanized. A lot of data is generated from the different stages of farming, but so far this information has been stuck in different systems and it is difficult to transfer data between systems. A lot of work is still needed to make the data created in primary production available to the whole food industry.

Data management and data sharing will enable actors in the agricultural sector to develop innovative products and services. Good data management and data sharing is also essential for training in AI systems. In the data farm demos, you can try out data sharing in a data-space pilot environment. Typical agricultural applications and data-driven service providers have been created in the data farm ecosystem. With model datasets collected by research institutions, you can safely explore the role of data owner, data holder and data user.