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
Research farm management in agricultural experimental stations requires effective use of geographical information on farm layout, field boundaries, location of buildings, roads, irrigation channels, wells and electric lines, together with information facilities like farm machinery, livestock, etc. and the planned crop field experiments. The field experiment data will include details of crop and variety information, field preparation and input applications. Record-keeping of such information is laborious, time-consuming and cumbersome process. It also becomes difficult to maintain these records over time, when evaluating the effectiveness of changes in management plans. Advances in information technology allow agricultural experimental farms to acquire large amount of farm data more efficiently. Geospatial technologies can enhance the efficacy incorporating traditional IT information management tools for farm management. This study presents the design and application of a web-based spatial decision_support system (SDSS) for experimental farm management using open-source GIS. This prototype SDSS allows farm managers, researchers and students to explore and access land-use options, fertilizer and pesticide applications, and track and visualize historical data of weather, input use, pest infestation and yield by field plots for better farm management.
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