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
Evaluation of the usefulness at national level of the dairy cattle health and production recording systems in Great Britain
The aim of this study was to formally evaluate, qualitatively, the ability of existing recording systems to generate accurate and reliable estimates of the frequency of selected health conditions in the dairy herd of Great Britain. Fifty-nine recording systems were identified, of which 36 had their key characteristics defined through a web-based questionnaire. Nineteen of them were further assessed following the SERVAL, a SuRveillance EVALuation framework against a set of 12 attributes: benefit, bias, communication, coverage, data collection, data management, data analysis, data completeness, flexibility, multiple utility, representativeness and stability/sustainability. The evaluated systems showed considerable differences in their coverage, implementation and objectives. There were overlaps in recorded conditions, with Johne's disease, bovine viral diarrhoea, mastitis and lameness being recorded by most of the systems. Selection bias, data ownership and lack of integration of data from different systems appeared to be a key limitation on the future use of existing systems for nationwide monitoring. The results showed that even though the individual systems can provide reliable estimates of dairy health for individual farmers, none of the systems alone could provide accurate and reliable estimates for any of the conditions of interest at national level.
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