e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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:

Discover all records
Home page


High throughput comparison of prokaryotic genomes


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.

  • IT
  • INFN_Natl_Inst_Nucl_Physics (IT)
Data keywords
  • semantic
Agriculture keywords
  • farm
Data topic
  • big data
  • information systems
  • modeling
  • semantics
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • INFN_Natl_Inst_Nucl_Physics (IT)
Powered by Lodex 8.20.3
logo commission europeenne
e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.