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
The rural information service in the rural area in China developed rapidly these years. But the agriculture information resources need to be further development and utilization, the key of agriculture information service at the present stage is to summarize the real demand of the rural users, choose suitable technology, find the right solution, solve the information sharing and fusion problems fundamentally. AISC(Agriculture Information Cloud-Services) is a cloud service platform, which tried to import different datasets in different data sources that constructed by different organizations, and combine all these datasets into one big dataset logically. Based on the "big dataset", many applications such as semantic information retrieve, intelligent information push, self-organized knowledge base construction etc. were developed, so the service efficiency is improved.
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