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
Internet has become an important platform of information publishing, exchanging and accessing. Recently, agricultural products and food safety relating news become hot posts on internet, which profoundly impacts daily life and public affairs management. The real-time and propagation characteristics of internet information makes internet public opinion becomes a more and more important food safety warning resource. In consideration of domain ontology has good concept hierarchical structure, includes abundant semantics, and has an outstanding significance on information resources organization and knowledge expression, food safety core ontology was built up in this paper. The food safety core ontology mainly focus on food safety incidents, invasive organism contamination, agricultural food sources pollution, processed food production issue, etc., based on semantic relations of concepts in ontology we designed inference rules, and achieved food safety knowledge inference and retrieval. Under the guidance of core ontology library, we designed self-adapting food safety internet hot public opinion identification and acquisition method, through customized crawler program, web pages were collected from internet and denoising processed, information document was generated from ontology library, followed by classification and realization of existing public opinion, those that can't be classified were computed by event dimension of vectors similarity for cluster analysis, and then updated the ontology library. All these effectively accomplish detect and trace food safety public opinions. In this paper, system of total merit index of food safety warning is constructed and the technique of quantitatively calculating different levels is given. Consequently, it contributes to scientific grounds for an objective, comprehensive and deep analysis in online information of food safety sector.
Inappropriate format for Document type, expected simple value but got array, please use list format