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
Improved understanding of the biology of traits of livestock species necessitates the use and combination of information that is stored in a variety of different sources such as databases and literature. The ability to effectively combine information from different sources, however, depends on a high level of standardization within and between various resources, at least with respect to the used terminology. Ontologies represent a set of concepts that facilitate standardization of terminology within specific domains of interest. The biological mechanisms underlying quantitative traits of farm animal species related to reproduction and host pathogen interactions are complex and not well understood. This knowledge could be improved through the availability of domain-specific ontologies that provide enhanced possibilities for data annotation, data retrieval, data integration, data exchange, data analysis, and ontology-based searches. Here we describe a framework for domain-specific ontologies and the development of 2 first-generation ontologies: Reproductive Trait and Phenotype Ontology (REPO) and Host Pathogen Interactions Ontology. In these first-generation ontologies, we focused on "female fertility in cattle" and "interactions between pigs and Salmonella". Through this, we contribute to the global initiative toward the development of an Animal Trait Ontology for livestock species. To demonstrate its usefulness, we show how REPO can be used to select candidate genes for fertility.
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