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
Numerous resources have been developed to have a better access to scientific information in the agricultural domain. However, they are rather concerned with providing general metadata of bibliographic references, which prevents users from accessing precise agricultural information in a transparent and simple manner. To overcome this drawback, in this paper, we propose to use domain-specific resources to improve the results in the answers obtained by an Open-Domain Question Answering (QA) system, obtaining a QA system for the agricultural domain. Specifically, it has been made by (i) creating an ontology that covers concepts and relationships from journal publications of the agricultural domain, (ii) enriching this ontology with some public data sources (e.g the Agrovoc thesaurus and the WorldNet lexical database) in order to be precisely used in an agricultural domain, and (iii) aligning this enriched ontology with articles from our case-study journal, i.e. the Cuban Journal of Agricultural Science. Finally, we have developed a set of experiments in order to show the usefulness of our approach.
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