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
High Performance Computing is relevant in many applications around the world, particularly high energy physics. Experiments such as ATLAS, CMS, ALICE and LHCb generate huge amounts of data which need to be stored and analyzed at server farms located on site at CERN and around the world. Apart from the initial cost of setting up an effective server farm the cost of power consumption and cooling are significant. The proposed solution to reduce costs without losing performance is to make use of ARM g processors found in nearly all smartphones and tablet computers. Their low power consumption, low cost and respectable processing speed makes them an interesting choice for future large scale parallel data processing centers. Benchmarks on the CortexTMA series of ARMg processors including the HPL and PMBW suites will be presented as well as preliminary results from the PROOF benchmark in the context of high energy physics will be analyzed.
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