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
Rice pests and diseases could have significant negative effects on rice production around the world. There is a need for managing and displaying the characteristics and variability of crop diseases and pests for an agricultural region at both spatial and temporal scales. In the current study, geographic information system (GIS) and database management technologies are applied to store, manage, analyze and visualize massive long-term heterogeneous information related to rice diseases and pests in Chongqing. Spatial data including administrative district, rivers, roads, monitor locations were digitized and corrected using ArcGIS 9.2. Non-spatial data including weekly long-term (2003-) records of rice pests and diseases from monitor locations in Chongqing were collected and analyzed. The developed database could provide critical information for early warning for high-risk areas of rice production and for management decision making. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Conference ESIAT2011 Organization Committee.
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