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
Concept Semantic Similarity Computation and its Application in High-speed Railway Domain Ontology
In the fields of knowledge retrieval fields based on ontology, concept similarity computation is an important step to expand concept. So how to promote the precision of concept similarity computation becomes one of the most important technologies to promote search quality. Some kinds of domains such as agriculture, railway, high-speed railway and aviation include different professional fields. For example, the high-speed railway domain consists of professional fields like maintenance engineering, traction power supply, EMU and operation management etc. The ontology of these domains can be integrated by ontologies of the professional fields that are built on thesaurus and thematic words. Oriented to the domain which consists of several professional fields, this paper proposes the module of domain ontology based on ontology module, and then builds a Model to compute domain ontology Concept Semantic Similarity. This paper also makes an experiment on the high-speed railway domain ontology to test the Model. The experiment shows that the model can reflect the semantic relation between concepts.
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