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
Integrated Management and Visualization of Spatial Data Based on Oracle Spatial Database with Map Viewer
Integration and visualization of agricultural vector data, raster data and the corresponding attributes are the key techniques in the process of agricultural information management, and in order to enable fast spatial searching, querying and rendering, it is necessary to use the efficient index for vector data and generate appropriate Pyramids for raster data. In this paper, the integrated management and visualization of land use vector datasets, SPOT images and the corresponding agricultural attributes are presented in Oracle Spatial with MapViewer. The table structures based on the storage model of GeoRaster and Geometry in Oracle Spatial were designed firstly, and then a method for finding the right Quadtree tiling level based on the majority geometries with the similar MBR area was devised in order to speed up spatial querying. In addition, the appropriate number of image Pyramid levels based on the scale and resolution of each zoom level for better display performance and less storage requirements was calculated. The effectiveness and efficiency of the invented methods were finally examined on the large spatial datasets.
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