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
In this paper, at first, we discuss the state of the art and the research challenges that are involved in developing the computing infrastructure needed for e-Science in agricultural Semantic Grid portal. In so doing, a conceptual architecture for the agricultural Semantic Grid is presented. This architecture adopts a service-oriented perspective in which distinct stakeholders in the agricultural process provide services to one another in various forms of marketplace. The view presented in the report is holistic, considering the requirements of e-Agriculture and the agricultural expert at the datalcomputation, information and knowledge layers. The data, computation and information aspects are discussed from a distributed systems viewpoint and in the particular context of the Web as an established large scale infrastructure. A clear characterization of the knowledge grid is also presented. This characterization builds on the emerging metadata infrastructure with knowledge engineering techniques. These techniques are shown to be the key to working with heterogeneous information and also to working with experts and establishing communities of e-Scientists in agriculture.
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