CoESRA (Collaborative Environment for Scholarly Research and Analysis) is a free virtual desktop environment that gives researchers a portable and powerful computational environment to run experiments and share their works. It provides popular tools like RStudio, Canopy (IDE for python and Notebook), Kepler Scientific Workflow, KNIME, QGIS, Panoply and OpenRefine to enable users to create, execute and share data simulations, visualisation, scripts and algorithms.
Once a specific analysis is conducted, the entire process chain can be stored and shared with other scientists, which improves the reproducibility, repeatability and transparency of research outcomes.
CoESRA provides an outlet for people to compose, execute and share their experiments. Specifically, it connects existing TERN infrastructure and other data services running from the National eResearch Collaboration Tools and Resources (NeCTAR) and stored in Research Data Storage Infrastructure (RDSI) with the tools for analysis and manipulation to develop a CoESRA virtual experiment environment.
The CoESRA is a workflow-based web-platform that allows researchers to perform complex analyses without having to set up the experiment from scratch and worry about having enough resources to run the analysis. The tool will provide an opportunity not only to re-use data but also tools for data manipulations, scripts for data visualisation and algorithms for analysis processes. Once a specific analysis is conducted, the entire process chain can be stored and shared with other scientists improving the reproducibility and repeatability of the experiments. Finally, the workflow can published to Research Data Australia (RDA).
And, it's not just researcher that will benefit from the project. The community will gain access to data streams, tools and often hidden ‘pipeline’ processes to leverage further knowledge about ecosystem science experiments. This exciting project reduces the overheads of setting up environmental analyses and provides a great benefit to the science community via the creation of a platform for re-usable, repeatable and above all reproducible scientific analyses.