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
Recently, the world is hunting for using life sciences data in solving the problems of fighting hunger in the next coming years. Integrating this data can be useful in areas of agricultural bioinformatics and other disciplines. However, efficient integration techniques must be developed to biological data since biological data has its own challenging characteristics, such as the existence of huge data existence, heterogeneous distributed data, and frequently updated data. In the current work, a semantic network for biological data integration is proposed, utilizing both ontology provided at OBO and atomic data provided at various biological databases to encompass an integrated data layer that can be queried using XQuery. Human and Yeast proteins are used as examples from UniProt release 14, integrated with other protein-related data, such as protein-protein interaction, protein domain, protein function, protein subcellular location, and related chemical reactions.
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