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
Smart farm, a subcategory of smart city, is a multidisciplinary business management method, in which agriculture and information communication are combined to manage crop growth remotely by automatically measuring and analyzing the environment and growth of crops, and controlling and constructing a database of an optimal environment on the basis of big data. A big data-based decision_support system in a smart farm has a very close relationship with crop growth, and it is therefore important to secure practical information, rather than merely collecting raw data. For the system proposed in this paper, as a defense technology for cyber target attack threats in smart farm, an intelligent security technology is designed through multiple source data collection and analysis on the basis of big data analytics, which has recently been drawing attention. In the recent internet services, as advanced threats such as APT (Advanced Persistent Threats) are increasing, big data analysis is being combined with security, all computing environments must be monitored, and when a security problem actually occurs, automatic action must be taken. The proposed system prevents various attacks in advance by applying security intelligence using security intelligence and big data analysis and taking appropriate action against a potential security threat incident.
Inappropriate format for Document type, expected simple value but got array, please use list format