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
Internet of Things (IoT) was faced with some difficulties which contained mass data management, various standards of object identification, data fusion of multiple sources, business data management and information service providing. In China, some safety monitoring systems of agricultural product always adopt centralized system architecture in which the data is stored concentratively. These systems could not be connected with or accessed by each other. This paper proposed an information system of agriculture Internet of Things based on distributed architecture. A distributed information service system based on IoT-Information Service, Object Naming Service, Discovery Service is designed to provide public information service including of capturing, standardizing, managing and querying of massive business data of agriculture production. A coding scheme for agricultural product, business location and logistic unit is provided for data identification. A business event model of agriculture IoT is presented for business data management. The whole system realizes the tracking and tracing of agricultural products, and quality monitoring of agriculture production. The implementation of this information service system is introduced.
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