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
We present a gold standard for the evaluation of Cross Language Information Retrieval systems in the domain of Organic Agriculture and AgroEcology. The presented resource is free to use for research purposes and it includes a collection of multilingual documents annotated with respect to a domain ontology, the ontology used for annotating the resources, a set of 48 queries in 12 languages and a gold standard with the correct resources for the proposed queries. The goal of this work consists in contributing to the research community with a resource for evaluating multilingual retrieval algorithms, with particular focus on domain adaptation strategies for "general purpose" multilingual information retrieval systems and on the effective exploitation of semantic annotations. Domain adaptation is in fact an important activity for tuning the retrieval system, reducing the ambiguities and improving the precision of information retrieval. Domain ontologies constitute a diffuse practice for defining the conceptual space of a corpus and mapping resources to specific topics and in our lab we propose as well to investigate and evaluate the impact of this information in enhancing the retrieval of contents. An initial experiment is described, giving a baseline for further research with the proposed gold standard.
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