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
This study proposes an approach for building a Semi-Automatic Agricultural Extension Support System based on mobile communication networks and machine learning. This system can be used to link farmers and agricultural experts, thus, it can be considered as an online "farmer-expert bridge". To build the system, at first, we need to build modules for sending and receiving SMS/MMS messages. These modules are important for farmers to send questions or images, e.g., about their rice status, that need to be consulted by the agricultural experts. Next, a message classification module is built using a combination of machine learning method (e.g., SVM) with image and text processing technologies. Finally, a whole web-based system is conducted to integrate these modules. Initial results show that construction of this system is feasible. This is also the foundation for building an online automatic agricultural extension support system through mobile communication networks.
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