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
Development of a multi-agent system simulation platform for irrigation scheduling with case studies for garden irrigation
The adoption of irrigation control strategies, aimed at attaining the desired level of humidity for each plant type, can improve the costs and energy consumed in small-scale site-specific irrigation systems. The paper presents a knowledge-based and distributed framework that simulates the behaviour of an irrigation system and permits accurate determination of irrigation timing. Several agents, which represent the actors involved in this problem, coordinate their activities in order to evaluate different irrigation strategies. A common ontology shares the knowledge required in the agent-based framework, which can be tuned according to the particular circumstances of the field. The usefulness of the developed system is demonstrated in three case studies, in which the simulations performed by the system provide the answer to different questions (length of irrigation time, comparison of a fixed and a dynamic irrigation policy, and most efficient configuration of a garden). The system simulates the behaviour of the irrigation system for the possible solutions and finds the most efficient one in terms of water consumption. Although only at small areal scale, this paper shows how agent-based simulation techniques can be successfully used to solve agricultural problems. (c) 2012 Elsevier B.V. All rights reserved.
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