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
THE ACQUISITION OF CLASS DEFINITIONS IN THE COMMODITY ONTOLOGY OF AGRICULTURAL MEANS OF PRODUCTION
The agricultural means of production is also called the means of agricultural production. The previous work focused on constructing the means of agricultural production commodities ontology taxonomy. After finishing constructing the ontology taxonomy, adding the detail information to the ontology are the following work. The detail information includes classes' definitions, properties, relations, instances and axioms. The classes' definitions are the concrete domain knowledge manifestation. Therefore they can be used to learn class's properties and relations. This paper focuses on obtaining these definitions. To this end, the most important work is to determine where to obtain class's definitions. This paper discusses the selective process. According to authority, completeness, accuracy, practicability and computerization, compares three kinds of knowledge sources, and then selects online "Encyclopedia of China" as the knowledge source. Analyzes the encyclopedia website and its entries, and then proposes an automatic method to get class definitions. The experiment shows that nearly 70% of classes can get their definitions. Using Jena API to add the definitions to the ontology model represented in OWL format.
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