EXPLORE THE DATA ECOSYSTEM

The project name reflects the overall aim of this project: to strengthen support systems in creating space for innovating farmers.
Innovative farmers are everywhere, but their environment determines the rate of success. The project aims to create more space for innovations, through amplifying good examples of innovation support systems and through multi-actor learning about ways to stimulate innovation and remove obstacles. The main target group is intermediates who connect initiators to other actors for involving them in creating innovations, such as farmers, knowledge workers, actors in the value chain, administrators, civil society groups, etc.

11 European project partners are playing this intermediate role in their regional AKIS. 4 scientific partners complete the team. Each regional partner will host a Cross Visit. The visiting team, composed of project partners, studies interesting cases of agricultural innovations. The scientists provide sound methodology for making these visits valuable.
Throughout the project period partners support each other in an emerging professional innovation network. They inspire each other and initiate improvements in their own systems. The project also addresses the institutional environment, involving public managers, administrators and policy makers.

Case studies and lessons learned are made available to a wider public. Attention will be given to cultural and historical particularities, requiring tailor made solutions for every region. The scientists explore lessons to be generalised and added to the scientific discourse on knowledge brokers.

Once the approach of joint learning through Cross Visits has been well tested and the professional network is functional, the project is ready for collaboration with other partners such as thematic networks and operational groups under the EIP as well as other interested regions in joint learning about innovation support systems.

Acronym
AgriSpin
Website
Address
DK
Scientific discipline(s)
Geographic coverage
Type
Data science categories
Data science categories