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
Technology change stimulates the expectations of society and seeks to satisfy its demands. Continuing advances in electronics and information technology over the last 20 years have responded to the challenge posed by the environmental impacts of agricultural production systems. Future agriculture will require precision techniques to assemble information and achieve increasingly precise and responsive management practices in order to reduce wasteful inputs, and meet the social and economic pressures for safe high quality food at lower cost. Biosystems engineering, an interdisciplinary science linking biology, physics, engineering and mathematics, can provide understanding and then innovative precision Solutions for agriculture. Public and industry investment will be needed to achieve the necessary goals of lower environmental impact, and precision techniques will make a significant contribution. Worldwide, the availability of tools that allow accurate control of inputs and traceable management of food production will contribute to sustainable food production for all. The vision is of systems that utilise sensing methods and mathematical models of the biological process, and link them through to control algorithms that realise practical benefits. Tools to measure spatial variation in crop yield will draw on statistical models to interpret complex variation and provide robust information to justify variable input management. Machine vision will interpret complex natural scenes, leading to real-time control, and biosensors will be incorporated into automated systems for sensing animal fertility status, leading to automatic monitoring of animal health and welfare.
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