Georeferenced data are a key factor in many decision-making systems. However, their interpretation is user and context dependent so that, for each situation, data analysts have to interpret them, a time-consuming task. One approach to alleviate this task, is the use of semantic annotations to store the produced information. Annotating data is however hard to perform and prone to errors, especially when executed manually. This difficulty increases with the amount of data to annotate.
According to the literature on regime transition, niches are sources of innovation that may lead to the transformation of the dominant regime, if processes at other level of the system – the landscape and the mainstream regime - are supportive. A focus on actors involved in the transition process and the analysis of their specific role in knowledge networks can help assessing the robustness of a specific niche and its growth potential. Knowledge systems, and in particular the dynamics of local and expert knowledge, have in fact a key role in innovation models.
Increasing attention is being given to evaluating the impact of advisory services in terms of their effectiveness in providing farmers with knowledge and networks for innovation as well as understanding the factors that influence this effectiveness (Prager et al, 2017). The demand and uptake of advisory services is one factor and Klerkx et al (2017) comment on the variation in farmers’ demand and the influences of variables such as farm size, asset status and education as well as stability or turbulence in the regulatory environment.