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
Finding high predictive modeling has been an important task in agriculture. Recently, a machine learning technique using big data achieved high prediction model performance. Following this trend, the goal of this study was to predict the number of pig shipments by using production data collected from pig management systems. This study used weighted sampling to prevent system user sample bias and inconsistency and compared the performance of a model that used a machine learning technique to apply a weighted value and one that did not apply a weighted value. The results indicated that the model that used the machine learning technique to apply a weighted value had higher prediction performance than the model without the applied weighted value.
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