e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

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.

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Applying GIS and high performance agent-based simulation for managing an Old World Screwworm fly invasion of Australia


Agent-based modelling has proven to be a promising approach for developing rich simulations for complex phenomena that provide decision_support functions across a broad range of areas including biological, social and agricultural sciences. This paper demonstrates how high performance computing technologies, namely General-Purpose Computing on Graphics Processing Units (GPGPU), and commercial Geographic Information Systems (GIS) can be applied to develop a national scale, agent-based simulation of an incursion of Old World Screwworm fly COWS fly) into the Australian mainland. The development of this simulation model leverages the combination of massively data-parallel processing capabilities supported by NVidia's Compute Unified Device Architecture (CUDA) and the advanced spatial visualisation capabilities of GIS. These technologies have enabled the implementation of an individual-based, stochastic lifecycle and dispersal algorithm for the OWS fly invasion. The simulation model draws upon a wide range of biological data as input to stochastically determine the reproduction and survival of the OWS fly through the different stages of its lifecycle and dispersal of gravid females. Through this model, a highly efficient computational platform has been developed for studying the effectiveness' of control and mitigation strategies and their associated economic impact on livestock industries can be materialised. Copyright (C) International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

  • AU
  • Univ_New_England (AU)
Data keywords
  • information system
  • high performance computing
Agriculture keywords
  • agriculture
  • livestock
Data topic
  • information systems
  • modeling
  • sensors
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • Univ_New_England (AU)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.