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
This work handles the optimization of the grid computing performances for a data-intensive and high "throughput" comparison of protein sequences. We use the word "throughput" from the telecommunication science to mean the amount of concurrent independent jobs in grid. All the proteins of 355 completely sequenced prokaryotic organisms were compared to find common traits of prokaryotic life, producing in parallel tens of Gigabytes of information to store, duplicate, check and analyze. For supporting a large amount of concurrent runs with data access on shared storage devices and a manageable data format, the output information was stored in many flat files according to a semantic logical/physical directory structure. As many concurrent runs could cause reading bottleneck on the same storage device, we propose methods to optimize the grid computing based on the balance between wide data access and emergence of reading bottlenecks. The proposed analytical approach has the following advantages: not only it optimizes the duration of the overall task, but also checks if the estimated duration is compliant with the scientific requirements and if the related grid computing is really advantageous compared to an execution on a local farm.
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