Development of a cloud-based platform for reproducible science: a case study of an IUCN red list of ecosystems assessment

Guru, Siddeswara, Hanigan, Ivan C., Nguyen, Hoang Anh, Burns, Emma, Stein, John, Blanchard, Wade, Lindenmayer, David and Clancy, Tim (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. doi:10.1016/j.ecoinf.2016.08.003

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Author Guru, Siddeswara
Hanigan, Ivan C.
Nguyen, Hoang Anh
Burns, Emma
Stein, John
Blanchard, Wade
Lindenmayer, David
Clancy, Tim
Title Development of a cloud-based platform for reproducible science: a case study of an IUCN red list of ecosystems assessment
Journal name Ecological Informatics   Check publisher's open access policy
ISSN 1574-9541
Publication date 2016-11-01
Year available 2016
Sub-type Article (original research)
DOI 10.1016/j.ecoinf.2016.08.003
Open Access Status File (Author Post-print)
Volume 36
Start page 221
End page 230
Total pages 10
Place of publication Amsterdam, Netherlands
Publisher Elsevier BV
Language eng
Subject 1105 Ecology, Evolution, Behavior and Systematics
2303 Ecology
2611 Modelling and Simulation
2302 Ecological Modelling
1706 Computer Science Applications
1703 Computational Theory and Mathematics
2604 Applied Mathematics
Abstract One of the challenges of computational-centric research is to make the research undertaken reproducible in a form that others can repeat and re-use with minimal effort. In addition to the data and tools necessary to re-run analyses, execution environments play crucial roles because of the dependencies of the operating system and software version used. However, some of the challenges of reproducible science can be addressed using appropriate computational tools and cloud computing to provide an execution environment. Here, we demonstrate the use of a Kepler scientific workflow for reproducible science that is sharable, reusable, and re-executable. These workflows reduce barriers to sharing and will save researchers time when undertaking similar research in the future. To provide infrastructure that enables reproducible science, we have developed cloud-based Collaborative Environment for Ecosystem Science Research and Analysis (CoESRA) infrastructure to build, execute and share sophisticated computation-centric research. The CoESRA provides users with a storage and computational platform that is accessible from a web-browser in the form of a virtual desktop. Any registered user can access the virtual desktop to build, execute and share the Kepler workflows. This approach will enable computational scientists to share complete workflows in a pre-configured environment so that others can reproduce the computational research with minimal effort. As a case study, we developed and shared a complete IUCN Red List of Ecosystems Assessment workflow that reproduces the assessments undertaken by Burns et al. (2015) on Mountain Ash forests in the Central Highlands of Victoria, Australia. This workflow provides an opportunity for other researchers and stakeholders to run this assessment with minimal supervision. The workflow also enables researchers to re-evaluate the assessment when additional data becomes available. The assessment can be run in a CoESRA virtual desktop by opening a workflow in a Kepler user interface and pressing a “start” button. The workflow is pre-configured with all the open access datasets and writes results to a pre-configured folder.
Keyword Cloud computing
IUCN ecosystems assessment
Kepler workflow
Platform as a service
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Earth Sciences Publications
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