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
This article describes the interpretation and recommendation modules of the Ceres system, an Expert System that supports the interpretation of soil samples, recommendation for lime, fertilizer and data management using resources from expert system and database technologies. Among the requirements of the application domain, it is the information analysis resulting from the interpretation process, which has the purpose of finding the causes of productivity variation. This analysis makes possible human interaction in the sense of preserving proprieties that favor the developing of vegetables. In this way, the Ceres system has been proposed to assist experts on possible actions to be implemented to improve soil quality. The system is compound by several modules that implement tools to analyse the different soil properties. The focus of this paper is to analyze soil chemical aspects and the analysis tasks related to them. The modules proposed were conceived with a knowledge base formed by ontology, an inference engine and an interface for external access.
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