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
Domain Specific Categories and Relations and their Potential Applications: A Case Study of Two Arrays of Agriculture Schedule of Colon Classification
The categories/isolates are broadly conceived as common and special. The common categories are applicable to all the classes of subjects in a Classification system, whereas the specials are applicable within a domain or specified classes of a classification system. The CC has represented some unique special categories, especially in the Agriculture Subject schedule, and such a provision is not seen in any other classification system; not even in any other subject schedule of Colon Classification. These special categories are termed here as "Domain Specific Categories". The paper analyses the thematic relationships within and outside the subject schedule with potential applications in devising a scheme of metadata as demonstrated in a research study on Indian Medicinal Plants. The other potential applications of such thematic relationships are in the creation of semantic maps and in linking concepts from different domains of knowledge.
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