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
As a subsequent step of the conceptual modelling and the information modelling involving the specification of the knowledge content of the decision processes and the involved data imbedded in the information entities, a derivation of the functional requirements was carried out to support and guide the selection of the technological infrastructure of a dedicated farm management information system (FMIS). The study employed the core-task analysis (CTA) method involving a combination of science-based modelling, practice-based modelling, and integrated information modelling. The "process" entities of the information flow model which represent the usage processes of the information, and of the "information" entities which represent the data elements were identified for the specific case of fertilising. This identification of the usage processes as well as the associated data elements showed the complexity of the decision making process within the domain of field operations. In a fully structured and formalised information flow decomposition, many actors are required to deliver information to the decision processes in order to fully emulate the tacit knowledge that the farmer are currently using. Especially, the concept of assisting services has to evolve in order to sustain the need of more automated decision processes in the future. New information management concepts and designs mean that farmers have to be ready to adopt new working habits and perhaps also undergo further training. (C) 2011 Elsevier B.V. All rights reserved.
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