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 Based on Spatial Data Mining Used Decision Tree for Agriculture Land Grading
This paper introduces spatial data mining technique especially decision tree algorithm applying to agriculture land grading. The idea is to combine spatial data mining/decision tree techniques with expert system techniques and apply them to establish an intelligent agriculture land grading information system. The author adopt decision tree c4.5 algorithm and implement with Mo2.0 and VC++6.0 to build agriculture land grading expert system. Also, an experiment is presented to show the particular advantages of this methodology in addressing problems in land grading such as missing land information, difficulties in quantitative analysis of factors.
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