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 paper used a multi-level latent class model to evaluate whether online learning patterns exhibit regional differences and demographics. This study discovered that the Internet learning pattern consists of five segments, and the region of Taiwan is divided into two segments and further found that both the user and the regional segments are highly interpretable. The individual segments are dictated by demographic variables, such as age and gender. For instance, younger people were good at employing Internet services; those 21-30 years old adopted e-learning, browsed blogs, and enjoyed the Internet more than others; and females preferred e-learning applications more than males did. On the other hand, the regional segments are dictated by the individual segments. For instance, the service area segment comprised a higher proportion of members who were good at online learning applications. The agricultural area segment made up a higher proportion of members who were traditional users. The findings provide both product or service providers/vendors and curriculum designers with an applicable guideline for developing service strategies for better matches and higher service satisfaction between the curriculum and the users' needs.
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