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
Decision-making on animal welfare issues requires a synthesis of information. For the assessment of farm animal welfare based on scientific information collected in a database, a methodology called 'semantic modelling' has been developed. To date, however this methodology has not been generally applied. Recently, a qualitative Risk Assessment approach has been published by the European Food Safety Authority (EFSA) for the first time, concerning the welfare of intensively reared calves. This paper reports on a critical analysis of this Risk Assessment (RA) approach from a semantic-modelling (SM) perspective, emphasizing the importance of several seemingly self-evident principles, including the definition of concepts application of explicit methodological procedures and specification of how underlying values and scientific information lead to the RA output. In addition, the need to include positive aspects of welfare and overall welfare assessments are emphasized. The analysis shows that the RA approach for animal welfare could benefit from SM methodology to support transparent and science-based decision-making.
- Wageningen_Univ_and_Res_Ctr_WUR (NL)
- Ghent_Univ (BE)
- Swedish_Univ_Agr_Sci_SLU (SE)
- Newcastle_Univ (UK)
- Oniris (FR)
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