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 paper presents a knowledge-based intelligent e-commerce system for selling agricultural products. The KIES system not only provides agricultural products sales, financial analysis and sales forecasting, but also provides feasible solutions or actions based on the results of rule-based reasoning. The intelligent system integrates a database, a rule base and a model base to create a tool of which managers can use to deal with decision-making problems via the Internet. Rules in the rule base are explained in detail to illustrate the processes of reasoning. Also, an automatic and practical inference engine that provides monitoring and controlling a verity of processes is presented to show how the system can deal with knowledge management. In order to obtain more profits and manage future change, artificial neural network models in the model base have been developed and compared for demand forecasting. Finally, for offering convenient delivery and user-friendly services to customers, an e-map combined with a GPS is used. (c) 2007 Elsevier B.V. All rights reserved.
Inappropriate format for Document type, expected simple value but got array, please use list format