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
Simulation modelling tools aim to give insights into system performance by simulating the system over a time period and then generating a set of results. When using a simulation modelling tool for decision_support it is frequently necessary to process a number of simulations or scenarios in an experiment which can generate significant amounts of data. Constructing the scenarios and then examining their results frequently involves significant work to manage the input data and the result sets. It is not uncommon to do large amounts of post processing of the result data. Systems can be complex and factors contributing to their performance may be difficult to discover without a well designed reporting or statistical analysis tool. Our solution to improving the understanding of systems by the user has been to integrate the experiment design, model processing and reporting of results within the decision_support system. The integrated process in CSIRO's GRAZPLAN DSS tools is called an Analysis. By building a scenario and then applying variations to form a factorial experiment it is possible to provide a multidimensional solution space that can demonstrate which factors contribute to certain system behaviour. In the AusFarm and GrassGro DSS tools the Analysis process is fully supported by a multidimensional reporting system that combines results from all the scenarios within the experiment and displays comprehensive reports in a format that mostly eliminates the need for manual post-processing by the user. Agricultural industry specialists, who are using GrassGro and AusFarm, have responded favourably to the effectiveness of this approach. Analysis reports show economic results and risks along with detail about the biophysical system for all the dimensions in the experiment. Users quickly develop a deeper understanding of the system being modelled. Solutions to management scenarios are being answered without the need for days or weeks of painstaking data management and post processing of outputs.
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