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
A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent-based model (ABM) as distinct instances of technologies with owners capable of making decisions based on economic and environmental information. This simulation setup allows us to explore the dynamics of assembly, disassembly, and use of these systems, which typically span decades, and to analyze the effect of using LCA information in decision making. We were able to integrate a simplified LCA into an ABM by aligning and connecting the data structures that represent the energy infrastructure and the supply chains from source to sink. By using an appropriate database containing life cycle inventory (LCI) information and by solving the scaling factors for the technology matrix, we computed the contribution to global warming in terms of carbon dioxide (CO(2)) equivalents in the form of a single impact indicator for each instance of technology at each discrete simulation step. These LCAs may then serve to show each agent the impact of its activities at a global level, as indicated by its contribution to climate change. Similar to economic indicators, the LCA indicators may be fed back to the simulated decision making in the ABM to emulate the use of environmental information while the system evolves. A proof of concept was developed that is illustrated for a simplified LCA and ABM used to generate and simulate the evolution of a bioelectricity infrastructure system.
Inappropriate format for Document type, expected simple value but got array, please use list format