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
Designing and Algorithm Implementing of the Expert System Platform for Assistant Identification of Agricultural Pests Based on a Dendriform Hierarchical Structure
Being numerous, the insect and disease pests were organized within classifications described as a dendriform hierarchical (tree-shape) structure The data of the structure were managed by database management system (DBMS), tables were designed to store the information about the species/category and related characteristics The characteristics were related to the species/category to construct a junction/x-ref table as the knowledge base of the expert system for insect and disease pest identification, including sets of identification characteristics for all species/category in the table Relational calculus was employed to estimate the potential species/category of the insect and disease pests in relation to inclusion of the set of characters selected by users and the sets of identification characteristics in the knowledge base of the system The system can be used as an open and flexible platform for professional users involved in plant protection to establish new expert application systems that provide pest identification services for common agricultural users
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