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
Integrated Assessment Modelling provides a systematic inter-disciplinary approach to support coherent ex-ante decision-making by a flexible integration of (reusable) models and datasets across scales. Within integrated assessment modelling a coherent and robust description of projects and scenarios is required to facilitate data preparation, model integration and the graphical user-interface development. This paper explains our experiences with a challenging and time-consuming task, e. g. arriving at a shared understanding on the definition of projects, experiments and scenarios among researchers coming from different disciplines, who have been exposed to dissimilar education and research experience. We demonstrate the use of ontologies in building this shared set of definitions and the relationship between the ontology and the human computer interaction through a case study. With a common ontology that represents the joint conceptualization of the projects, experiments and scenarios each researcher can refer at any later stage to the semantics of the concepts used. A collaborative approach was used to build such a common ontology in the SEAMLESS-Integrated Project, funded through the EU sixth Framework Programme, which aims at developing an integrated modelling framework (SEAMLESS-IF) to assess, ex-ante, agricultural and environmental policy options, allowing cross-scale analysis of a broad range of sustainability issues. Through several iterations a common ontology for projects, experiments and scenarios was built. In our common ontology a project has one and only one problem definition, and it can handle at least one or more Experiments. Experiments represent the assessment of one or a combination of policy options in a given context and outlook on the future. The indicator(s) should be the same between experiments which are part of the same project, allowing the comparison of different experiments. Each of the concepts Policy Option, Context and Outlook capture one part of the input parameters required for running each of the models. As a first validation of the project ontology, a set of four fictitious sample projects were made. One of these sample projects is an integrated assessment for one region Midi-Pyrenees in the South of France concerning the impacts of the CAP2003 reform, which is described in this paper The common project ontology highlighted the imprecise meaning of the word scenario and it links projects to problems, outlooks on the future, indicators, context of the problem, policies and ultimately to model runs in experiments. Also, by this common ontology the assumptions in building the assessment are clarified, moving the focus away from the tools to the assumptions underlying models and scenarios. In any integrated assessment project, it is recommended to clarify with its participants the meaning of scenario and associated concepts. We achieved this by the use of a common ontology, which forces participants to be clear, precise and coherent in their description of concepts and relationships between concepts, while the common ontology can be directly used for development of databases, models and graphical user interfaces.
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