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
IOT-enabled Quality Management Process Innovation and Analytics in China's Dairy Industry: A Data Flow Modeling Perspective
Since the "melamine" incident was reported in China, China's dairy industry attracts more and more attention, leading some scholars to conduct research on quality management and safety monitoring issues of China's dairy industry. The technology of the Internet of Things (IOT) is viewed as one of the best ways to solve the safety problems of China's dairy industry by supporting the development of dairy traceability systems. This paper firstly analyses the current situation of China's dairy industry supply chain to get at the root of the problem. We then propose an IOT-enabled quality management framework which is an innovation mode of quality management in China's dairy industry supply chain. To further highlight the important role of IOT technology, we employ a business process modeling approach based on data flow perspective to describe this innovation management mode. The artifacts we design, especially the matrix of dairy products and process information, can help the practitioners to efficiently monitor the quality information of dairy products.
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