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 H1N1 pandemic of 2009 and the ongoing Ebola outbreak in West Africa serve as a reminder of the social, economic and health burden of infectious diseases. The ongoing trends towards urbanization, global travel, climate change and a generally older and immuno-compromised population continue to make epidemic planning and control challenging. Recent quantitative changes in high performance pervasive computing have created new opportunities for collecting, integrating, analyzing and accessing information related to large urban social systems, disease surveillance and global logistics and supply chains. The advances in network and information science that build on this new capability provide entirely new ways for reasoning and controlling epidemics. In this talk I will overview of the state of the art in computational networked epidemiology with an emphasis on computational thinking and on the development of high performance computing oriented decision-support environments for planning and response in the event of epidemics. I will describe how such systems can be used to support near real-time planning and response during the 2009 H1N1 swine flu and the recent Ebola Outbreak in West Africa. Computational challenges and directions for future research will be discussed.
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