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
In order to improve the mutton traceability efficiency for Internet of Things and solve the problem of data transmission, analyzed existing tracking algorithm, proposed the food traceability application model, Petri network model of food traceability and food traceability of time series data of improved K-means algorithm based on the Internet of things. The food traceability application model to convert, integrate and mine the heterogeneous information, implementation of the food safety traceability information management, Petri network model for food traceability in the process of the state transition were analyzed and simulated and provides a theoretical basis to study the behavior described in the food traceability system and structural design. The experiments on simulation data show that the proposed traceability method based on Internet of Things is more effective for mutton traceability data than the traditional K-means methods.
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