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
Applying Knowledge Engineering and Ontology Engineering to construct a Knowledge Base for Early Warning and Proactive Control
Early Warning and Proactive Control systems intend to help managers predict and prevent problems in Food Supply Chain Networks. Since those problems are of various types and have broad scopes, an easy-to-access and easy-to-extend Knowledge Base is needed. This paper presents a structure for such Knowledge Base. The structure is designed with combined techniques from Ontology Engineering and Knowledge Engineering. It contains an ontology and a rule base with inference mechanism. A prototype system, filled with information from case studies, shows that the designed structure supports consulting the Knowledge Base on relevant knowledge for encountered problems, and extending the Knowledge Base with obtained novel knowledge.
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