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
Controlled experimentation has been the most common source of research data in most biological sciences. However, many research questions lend themselves to the use of population data, or combinations of population data and data resulting from controlled experimentation. Studies of important economic outcomes, such as efficiency, profits, and costs, lend themselves particularly well to this type of analysis. Analytical methods that have been most commonly applied to population data in studies related to livestock production and management include statistical regression and mathematical programming. In social sciences, such as applied economics, it has become common to utilize more than one method in the same study to provide answers to the various questions at hand. Of course, care must be taken to ensure that the methods of analysis are appropriately applied; however, a wide variety of beef industry research questions are being addressed using population data. Issues related to data sources, aggregation levels, and consistency of collection often surface when using population data. These issues are addressed by careful consideration of the questions being addressed and the costs of data collection. Previous research across a variety of cattle production and marketing issues provides a broad foundation upon which to build future research. There is tremendous opportunity for increased use of population data and increased collaboration across disciplines to address issues of importance to the cattle industry.
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