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
Agriculture-based precise and accurate information needs to be disseminated promptly to farmers so that better decisions such as managing farm fields, making continuous and scientific changes in their production systems and grabbing advantage of market opportunities can be made. In this paper, mobile technology is assessed for the agriculture information dissemination system. A survey has been conducted to find out potential technology, related to the use of the Internet and mobile among farmers in the state of Punjab in India, to deliver agriculture-related information to them. Results show that agricultural information system needs to be developed based on the mass communication technology such as mobile systems. It is also noted that localization and native language of farmers are the concerns to be incorporated into the systems. It has been focused that the use of soft-computing techniques in conjunction with communication networks, for inferring the decision regarding best practices for agricultural activities, is helpful in the development of these systems.
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