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
To improve work efficiency and productivity in agricultural environment, which may naturally be protean, unpredictable and laborious, many researchers have made attempts to apply information technology in the field of conventional agriculture. Especially, they have great concern toward a reasonable and reliable service control model or architecture to control agricultural works automatically and smartly. This article proposes a framework to support context-aware or smart services in agricultural environments, based on a context-aware workflow model and USN/RFID. The suggested framework is focused on supporting autonomous agricultural services in the fields of growth control, protection against disease and insects, and the output control of the agricultural computing environment using a workflow model which is one of the successful service automation models, using contexts from various sensors in agricultural fields. The proposed framework, based on a context-aware workflow, can be greatly helpful in the development of smart applications or work automation in the field of agriculture.
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