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
An Expert System Shell is an interface for strengthening, refining and maintaining the knowledgebase of an Expert System by directly interacting with it. The expert system shell is a complete development environment for developing and maintaining Knowledge-Based Applications and Expert Systems. It provides a step-by-step methodology for a knowledge engineer that allows the domain experts themselves to be directly involved in structuring and encoding the knowledge through an expert interface. Agriculture being a multidisciplinary science there is a scope of developing multiple expert systems for various crops, disease, insects, irrigation scheduling, fertilizer management and various other issues needed for a sustainable agriculture. There has been no such system or software that supports information management in this area. Developing such a platform for developing multidisciplinary and multi crop expert systems is a new approach that can provide computational convenience to replicate it for multiple crops. The shell described in this paper deals with the development procedure of multi crop expert system using the same inference engine used for " Expert System on Wheat Crop Management" developed by Division of Computer Applications, IASRI, New Delhi.
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