MIRACLE (Mining relationships among variables in large datasets from complex systems) is a Digging into Data project that aims to build a cloud-based community platform for reproducible data analysis, visualization and management for ABM output data.
WICI core member and director Dawn Parker has received new grant funding from the Social Sciences and Humanities Research Council (SSHRC) via the Digging into Data Challenge (DiD). The international DiD program was established to advance the use of computational methods to explore, analyze and visualize the rapidly expanding pool of crowd-sourced and remotely sensed “big data” from real-world systems. Unique among this year’s awards, Parker’s research team is developing tools to analyze output from computerized simulation models and compare that output to real-world “big data.”
The University of Waterloo is the lead institution for the larger DiD $567,000 (U.S.) project titled, Mining relationships among variables in large datasets from complex systems (MIRACLE). Local WICI team members include post-doc Xiongbing Jin and graduate student Kirsten Robinson. The project will be hosted through the Waterloo Institute for Complexity and Innovation (WICI). The international team includes participants from Arizona State University, USA (PI C. Michael Barton ) the University of Twente, NL (PI Tatiana Filatova) the University of Dundee, UK (PI Terence P. Dawson ) and the James Hutton Institute UK (Collaborator J. Gary Pohill).
MIRACLE will be a community platform that will support complex systems research across research communities. Our research group is very appreciative of SSHRC’s top dollar support for our innovative new venture to create community infrastructure that will be available to local stakeholders, university researchers, and the international community to support complex systems research.
GitHub repository for the MIRACLE platform: https://github.com/comses/miracle
GitHub repository for the example projects: https://github.com/comses/miracle-example-projects
Demo server: https://miracle.comses.net (Please contact the development team if you would like a test account. Alternatively, you can setup a local testing server using the instructions provided in our GitHub repository)
You can download a draft paper on how to use the prototype cloud-based MIRACLE platform here.
A video demonstration of the prototype platform, narrated by Allen Lee, is available here. Note that this video represents the state of the project as of January 2016.
You can download a PDF overview of the technical details of this research project here.
Download the Call for Participation to the related workshop at the 8th International Congress on Environmental Modelling and Software (iEMSs 2014) conference here.
Publications and presentations
MIRACLE: A prototype cloud-based reproducible data analysis and visualization platform for outputs of agent-based models Journal Article
In: Submitted for review, 2016.
2016 "Round Three" Digging into Data Challenge Conference, Glasgow, UK, 2016.
The MIRACLE project: Cyber infrastructure for visu- alizing model outputs Presentation
Professor Dawn Parker, School of Planning, University of Waterloo
Professor Michael Barton, Center for Social Dynamics & Complexity, Arizona State University
Professor Tatiana Filatova, University of Twente (UT)
Professor Terence Dawson, Centre for Environmental Change and Human Resilience, University of Dundee
January 16th, 2014 – National Science Foundation (NSF), National Science Foundation contributes to four international projects in data-intensive social science and humanities research
January 17th, 2014 – University of Waterloo, Waterloo researcher uses big data to see LRT impact on housing market
January 23rd, 2014 – Arizona State University, ASU professor wins ‘Digging Into Data’ challenge