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
Agricultural producers who possess large areas of arable land and a lot of machinery can achieve substantial savings, thus improving their business performance, if they manage to ensure adequate assignment of machinery to appropriate jobs during the entire production cycle. When attempting to establish the optimum assignment set of agricultural machinery, a variety of factors need to be taken into consideration, for example the features of human and technical resources engaged in production, weather conditions. characteristics of soil and crops, distance of fields from the machinery storage space. In this domain it is possible to use the assignment model as a decision_support. The initial assignment model, which is deterministic in character, has undergone improvements in this paper by means of computer simulation, which makes it suitable for usage in conditions of uncertainty, which are quite common in agriculture. In the proposed model, simulation is carried out for the values of all the parameters estimated to be stochastic. Oil the basis of scores assigned according to set criteria, the efficiency matrix is then formed, whose elements represent the expected benefits from assigning the machinery to particular activities in agriculture. The optimum assignment set of agricultural machinery is the one in which the sum of efficiency for all assignments is maximum. Usage of modern information technologies is an essential prerequisite for implementing the model discussed in this paper.
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