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
A segmentation transmission approach and information system for agriculture information based on mobile communication
Considering the information transmission system of agriculture M-informatization, pertinence and practicability are critical factors, but the current system lack these factors in China. Based on the case study of Agriculture Space Time of China Unicorn and Agricultural ICT of China Mobile, the segmentation transmission approach is presented in this paper. To make the current information transmission system more pertinent and practical, we adopt segmentation transmission approach in the critical nodes of the closed loop information transmission system, which includes produce, gathering, analysis & process, supplying, sending, distribution, receiving, application and feedback. According to the key attribute dimensionality of users, this approach employs intelligent IMS (Information Matching System) to match the Content of data dictionary with the individual needs of users, and analyze the static and dynamic attributes of users' datum and the content of service by using the high-powered rule-engine. This data dictionary is based on the scientific multilayer-integrated data dictionary concerning farm products. Adopting the approach presented in this paper in current agriculture M-informationization system can successfully transmit all kinds of segmentation agriculture information to the right agriculture users.
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