The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
This contribution depicts an approach enabling agricultural production systems to be represented at various spatial-temporal scales and organization levels: single plot or workshop, whole farm, group of farms within a territory, supply chain. This approach is based on an 'Action-Flow-Stock' ontology according to which each production unit is represented by a stock subject to filling-emptying actions controlled by conditions derived from states or events locally observed on some processes. Whereas stocks are computed as continuous variables, actions are represented by dynamical discrete functions. The models built with this ontology, whatever the formalization framework used to implement them (systems dynamics, multi-agents systems, timed automata), aim at dynamically simulating both the material flows and the human activities within agricultural production systems. The intended use of such models is to help agricultural stakeholders design and assess actual or potential management strategies in the light of the new concerns brought by the sustainability issues.
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