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
A design of spatial decision_support system to enhance decision progress in agricultural actions
Agricultural actions usually involve a decision process collaborating different decision makers and officers. Different decision process may encounter different difficulties depending on the type of actions. In order to make efficient progress in actions, a support system for decision making should be constructed to include not only supporting information for the decision, but also tools for decision management. For such decision_support and management system, enhancement in task communication, data summarizing and subtask management should be the focus of the development. In this study, we used MAKOCI (Multi-Agent Knowledge Oriented CyberInfrastructure) as a geospatial platform to convey customized decision knowledge, working procedures, and data processing capability, where ontology and multi-agent are implemented to facilitate modularized application design. A case study on detection and responses of agricultural heavy-metal contamination is given in this study to exemplify the functions of the decision_support system designed. By the proposed design, the spatial decision_support system facilitates hierarchical task definition and cross-government communications, in addition to supporting spatial and non-spatial decisional information. The decision progress can consequently be enhanced by monitoring, communication and management of actions among partaking users of the system.
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