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
A multiyear comparison of two types of automated-recording, weighing bucket rain gauges was conducted using precipitation data collected at the United States Department of Agriculture, Agricultural Research Service's Walnut Gulch Experimental Watershed in southeastern Arizona. The comparison was part of the conversion of all rain gauges on the watershed from an analog-recording, mechanical-weighing rain gauge to a data logger controlled, digital-recording, electronic-weighing rain gauge with radiotelemetry. This comparison applied to nine pairs of analog and digital rain gauges that were in coincident operation during a 5-year period, 1 January 2000 to 31 December 2004. This study found that (1) high errors in event intensities may be produced when analog charts are digitized at short time intervals; (2) dual digital rain gauges recorded precipitation equivalently; (3) for several different measures of precipitation, the analog and digital data were equivalent; and (4) implications for the rainfall-runoff model, Kinematic and Erosion Runoff model (KINEROS), showed a limited but significant effect in modeled runoff due to differences between analog and digital rain gauge input precipitation intensities. This study provided a useful analysis for long-term rain gauge networks that have recently converted, or will soon convert, from analog to digital technology. Understanding these differences and similarities will benefit interpretation of the combined long-term precipitation record and provide insights into the impacts on hydrologic modeling.
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