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
This paper studies information extraction of special domain based on ontology and document object model (DOM). In this paper, we present an ontology-based vegetable information extraction model, which fully considers the features of Web information and Web documents in the field of agricultural vegetable products. Combining ontology and DOM extraction algorithm, it extracts useful information from Web pages in the agricultural Website. The analytical module of document changes Web pages into ruled pages, and then the analytical module of Web pages structure convert pages into the DOM tree. The DOM tree extraction algorithm obtains information from the spots in the DOM tree. In the process of extraction information, domain ontology assists to construct the extraction rules at all times. This information extraction rules are based on the domain ontology and on DOM path through being attached to syntax information and learning samples. It implements information extraction through traveling DOM tree. The main contribution of this paper is to the agricultural vegetable ontology that is composed of the all kinds of vegetable classes and hierarchy relationship of vegetable products classes. The domain ontology is filled with the property of classes and instances reflected in the classes. The model offers a better solution in the information extraction of synonyms to the semantic question and provides the basis for Semantic Information Retrieval of the agricultural products. The test of system shows that the model can extract vegetable products from Web pages and solves the synonymous problem better.
Inappropriate format for Document type, expected simple value but got array, please use list format