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 solve the problem that the performance of web application can't meet users' expectation when many users access dynamic data through the application, a data farming optimizing technique for web application is proposed. In the proposed technique, the web application is based on XML and the data are converted into XML format before being presented through XSL. To reduce page response time, SVR is employed to forecast user's requests. And based on the requests, a data farming agent is used to create web pages that may be needed by users. At last, experiments are conducted to compare page response time for three web sites: a dynamic web site without data fanning optimization, a data farming optimized web site, and a SVR based data farming optimized web site. It is proved that page response time for the last web site is the least, which proves that the proposed technique is effective.
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