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Reproducible ecosystem risk assessment as virtual desktop case study

Our paper on a computational environment for reproducible workflows for climate change assessments is available for free access for limited time until Jan 28 via https://authors.elsevier.com/a/1UBJF5c6cKey5~

  • Guru, S., Hanigan, I. C., Nguyen, H. A., Burns, E., Stein, J., Blanchard, W., Lindenmayer, D., Clancy, T. (2016). Development of a cloud-based platform for reproducible science: A case study of an IUCN Red List of Ecosystems Assessment. Ecological Informatics, 36, 221–230. http://doi.org/10.1016/j.ecoinf.2016.08.003.

In this project we re-implemented a previously created project from an ArcGIS and R scripted process into a reproducible workflow in Kepler. That original analysis was for a climate change risk assessment using the IUCN Red list of Ecosystems Assessment framework and was done for Mountain Ash forests located in the Central Highlands of Victoria, Australia. This served as our case study.

Our aim was to demonstrate how this could be implemented as a more reproducible workflow and how it could be disseminated by creating a standalone computation environment for sharing the entire operating system and toolchain along with the work. The IT infrastructure we developed offers analysis tools as a “Platform as a Service” in a virtual desktop offered as a “Desktop as a Service” at https://www.coesra.org.au and new features are under development at https://portal.coesra.org.au. A R package of generic functions was created https://bitbucket.org/coesra/iucnecosystemriskassessment/src, and execution is possible as a pipeline of R scripts https://bitbucket.org/coesra/iucn_ecosystemriskassessment_mountainashforests as well as a Kepler workflow.

I made heavy use of the flowchart R function 'newnode' which I wrote as part of my PhD project (and is distributed in my own misc R package available on Github https://github.com/ivanhanigan/disentangle. This function takes a simple data.frame of steps, inputs and outputs and returns a string of text written in the dot language which can be rendered in R using the DiagrammeR package, or the standalone graphviz package. This creates the graph view shown below.

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Posted in  reproducible research pipelines reproducible research reports reproducible research cloud building


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