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 BaBar experiment has been taking data since 1999, investigating the violation of charge and parity (CP) symmetry in the field of high-energy physics. Event simulation is an intensive computing task, due to the complexity of algorithm based on Monte Carlo method implemented using the GEANT engine. In order to satisfy the experiment requirements, in the traditional BaBar computing model events are distributed over several sites involved in the collaboration where each site manager centrally manages a private farm dedicated to simulation production. The new GRID approach applied to the BaBar production framework is discussed along with the schema adopted for data deployment via Xrootd servers, including data management rising GRID middleware, on distributed storage facilities spread over the INFN-GRID network. A comparison between the two models is provided, describing also the custom application developed for performing the whole production task on the GRID and showing the results achieved.
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