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
To better understand and manage the interactions of agriculture and natural resources, for example under current increasing societal demands and climate changes, agro-environmental research must bring together an ever growing amount of data and information from multiple science domains. Data that is inherently large, multi-dimensional and heterogeneous, and requires computational intensive processing. Thus, agro-environmental researchers must deal with specific Big Data challenges in efficiently acquiring the data fit to their job while limiting the amount of computational, network and storage resources needed to practical levels. Automated procedures for collection, selection, annotation and indexing of data and metadata are indispensable in order to be able to effectively exploit the global network of available scientific information. This paper describes work performed in the EU FP7 Trees4Future and SemaGrow projects that contributes to development and evaluation of an infrastructure that allows efficient discovery and unified querying of agricultural and forestry resources using Linked Data and semantic technologies.
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