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
Successful grazing management is critical for stock farmers using pasture as the main source of food. Yet many farmers fall a long way short of the output of animal products possible given the pasture production achieved. Farmers have available a number of formal tools to help manage grazing systems, yet few make use of them. Another approach is to develop 'expert systems' encapsulating the skills of the most efficient farmers. This idea is explored based on the information obtained from three successful farmers who were interviewed on a regular basis over several years. The conclusion was that the rules and systems used by one farmer are not likely to apply to another due to their uniqueness. In effect the farmers build up their own personalised intuitive expert system. Thus, a more practical approach is to better train this intuitive skill. A discussion on what constitutes an expert is provided as this leads onto isolating the skills that need improving, and then onto exploring intuition and how it embodies the expert skills. A conclusion on how a farmer's intuition might be improved is offered. Intuition is used by all farmers so the discussion has implications for all farming types. Finally, comments on research into intuition are offered. (C) 2011 Elsevier Ltd. All rights reserved.
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