This data article contains annotation data characterizing Multi Criteria Assessment (MCA) Methods proposed in the agri-food sector by researchers from INRA, Europe's largest agricultural research institute (INRA, https://institut.inra.fr/en). MCA can be used to assess and compare agricultural and food systems, and support multi-actor decision making and design of innovative systems for crop production, animal production and processing of agricultural products.

Innovation is often presented as one of the main catalysts for more sustainable and inclusive development. In the agricultural and food sectors, innovation is characterized not only by specificities arising from its relationship to nature, but also from the wide diversity of its stakeholders, ranging from farmers to consumers, and including intermediaries such as the research community and advisory services. Innovation emerges from interactions between these actors, who mobilize resources and produce knowledge in collaborative mechanisms in orderto generate changes.

Innovation policies are considered the long-term strategy to overcome the present systemic crisis. But this crisis is questioning such policies, their presuppositions and institutional arrangements. This questioning includes the Triple Helix theory and its impact on research and innovation policies. The goal is to examine how this theory can respond to theoretical and practical challenges, how the theory needs to evolve in order to fit the present context.

This material was presented duting the conference: Big Data, a multiscale solution for a sustainable agriculture in Copenhagen Denmark in 2017 and brings an overview of the technological innovations of the French agricultural sector.

Agricultural machinery manufacturers historically referred to the intermediate players for selling, maintenance, customer service and/or training of equipment appear to interact with farmers and end-users. Intermediate players have therefore faced the burden to master the technology, in constant evolution, and the associated training needs at the interface between sophisticated equipment and the end-user and its sociological characteristics (age, education, background, etc.).