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
With the rapid development of information technology, ontology is gradually used for knowledge engineering and information science sphere. Agricultural Ontology mainly is composed of the concept and relationship between concepts in agricultural knowledge, as well as the computer can identify the composition of the formal description language. The goal of build the agricultural ontology is to form a common understanding of the agricultural information organizational structure, to known and analysis of knowledge in the field of agriculture so as to further establish the foundation for the agriculture semantic web. In this paper, we present a design principles and implementation process in vegetable products domain ontology. Through the collection and analysis of the field of vegetable products information as well as the use of inference engine, used to build vegetable domain ontology with OWL. In the information extraction prototype system, we achieved a semi-automatic filled with examples of vegetable products domain ontology. Through compared to the results before and after the use of inference engine, it show that vegetables and semi-automatic domain ontology building methods is feasible.
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