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
The article introduces the knowledge-based agricultural decision_support system. The system includes database and knowledge base as well as modules used for formation of models, optimization, simulation, decision analysis and inference. The linear programming model contains several hundreds of variables and restrictions. The farm model, using entered data, is formed according to "if-then" type rules that are stored in the knowledge base. Having solved the task of optimization, the particular values of variables indicate what kind of crops should be grown and in what area, as well as what animals and how many of them should be kept and what resources and how much of them have to be used for achieving the biggest benefit under the environmental and other conditions. The simulation was employed to test the sensitivity of the plan to weather and market variations. Having applied a set of production rules to the given facts and modelling results within the module of decision analysis and inference, conclusions and suggestions are made. decision_support system performs the analysis of production efficiency, resource reserves and shortage, and with the help of the Internet in real time provides a farmer with conclusions and suggestions necessary to increase the efficiency of production conforming to environmental constraints. The integration of optimization calculations and knowledge management into the agricultural decisions-support system expands its possibilities and improves the quality of solutions.
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