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
Research on Shared Information Classification in Regional Ecological Supply Chain Based on Value of Information Sharing
To achieve the economic benefits and ecological benefits of the regional ecological supply chain, the high-quality information management and information sharing in the supply chain are required. A reasonable classification of the shared information in the regional ecological supply chain is the basis of developing information control strategies and sharing information. This paper defines an abstract value of information sharing from a macro perspective, and analyzes the influencing factors in depth. On this basis, this paper establishes a grey clustering model to evaluate the value of information sharing with the application of the grey theory and AHP methods, thus achieving the goal of quantitative classification of shared information. Finally an example analysis is given for the model.
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