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


Spatial coherence of rainfall variations using the Oklahoma Mesonet


Studies on precipitation patterns and the spatial distribution of precipitation are beneficial for many aspects of society, including agriculture, transportation, and business. In this research, data from over 100 Oklahoma Mesonet stations were used in a space-time decomposition of Oklahoma rainfall from 1 March 1994 to 31 December 2003. Spatially coherent patterns of annual, warm-season, and cold-season rainfall events were derived using principal component analysis. Because the Oklahoma Mesonet records rainfall every 5 min, relatively short events (e.g. 15 min or 3 h) could be examined. Moreover, rainfall events were split into warm season and cold season to better understand the spatial differences by precipitation type (e.g. stratiform or convective). The results were not sensitive to domain size or shape. For 24-h, 3-h, and 15-min rainfall accumulations, four similar coherent rainfall patterns were identified, located across NW, NE, SE, and SW Oklahoma. As expected, as the timescales considered became smaller, the spatial scale of the patterns, especially from the 24-h to the 15-min pattern, decreased slightly. The 15-min rainfall analysis also identified a fifth region of coherent rainfall in central Oklahoma that was not identified in the first four principal components (PCs) of the 24-h or 3-h rainfall. The associated PC scores verified the rainfall patterns described by the PC loadings. Warm-season and cold-season rainfall patterns also were calculated for the 24-h, 3-h, and 15-min rainfall accumulations. There was not much difference between the warm-season and cold-season rainfall patterns, both demonstrating coherent regions in the four quadrants of Oklahoma. Copyright (C) 2011 Royal Meteorological Society

  • US
  • AU
  • Univ_Melbourne (AU)
  • Univ_Oklahoma (US)
Data keywords
    Agriculture keywords
    • agriculture
    Data topic
      Document type

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

      Institutions 10 co-publis
      • Univ_Melbourne (AU)
      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.