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
Agricultural energy consumption is an important environmental and social issue. Several diagnoses have been proposed to define indicators for analyzing energy consumption at large scale of agricultural farm activities (year, farm, family of production, etc.). However, to define ad-hoc environmental energetic policies to better monitor and control energy consumption, new indicators at a most detailed scale are needed. Moreover, by defining detailed scale indicators, large quantities of geo-referenced data need to be collected to feed these energetic diagnoses. This huge volume of data represents another important limitation of systems that implement these diagnoses because they are usually based on classical data storage systems (such as spreadsheet tools and Database Management Systems). These systems do not allow for interactive analysis at different granularities/scales of huge volumes of data and do not provide any cartographic representation. By contrast, Spatial OLAP (SOLAP) and spatial data warehouse (SDW) systems allow for the analysis of huge volumes of geo-referenced data by providing aggregated numerical values visualized by means of interactive tabular, graphical and cartographic displays. Thus, in this paper, we (i) propose new appropriate indicators to analyze agricultural farm energy performance at a detailed scale and (ii) show how SDW and SOLAP technologies can be used to represent, store and analyze these indicators by simultaneously producing expressive reports.
Inappropriate format for Document type, expected simple value but got array, please use list format