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Novel Approaches to Data Visualization

Speaker  Darren Thompson, Dawn Wright, and George Djorgovski

Affiliation  California Institute of Technology, CSIRO (Advanced Scientific Computing), Environmental Systems Research Institute

Host  George Djorgovski, California Institute of Technology

Duration  01:19:20

Date recorded  9 October 2012

Data Visualization in Virtual Spaces and High Dimensions
Speaker: George Djorgovski
Visualization is a bridge between the quantitative content of data and human intuition and understanding. Effective visualization is a critical bottleneck as the complexity and dimensionality of data increase. I will describe some experiments in collaborative, multi-dimensional data visualization in immersive virtual reality.

CT and Imaging Tools for Windows HPC Clusters and Azure Cloud
Speaker: Darren Thompson
Computed Tomography (CT) is a non-destructive imaging technique widely used across many scientific, industrial, and medical fields. It is both computationally and data intensive. Our group within CSIRO has been actively developing X-ray tomography and image processing software and systems for GPU-enabled Windows HPC clusters.

A key goal of our systems is to provide our “end users”—researchers—with easy access to the tools, computational resources, and data via familiar interfaces and client applications without the need for specialized HPC expertise. We have recently explored the adaptation of our CT-reconstruction code to the Windows Azure cloud platform, for which we have constructed a working “proof-of-concept” system. However, at this stage, several challenges remain to be met in order to make it a truly viable alternative to our HPC cluster solution.

Work in Progress Toward Enhancing Multidimensional Visualization with Analytical Workflows
Speaker: Dawn Wright
Big Data, particularly from terrestrial sensor networks and ocean observatories, exceed the processing capacity and speed of conventional database systems and architectures, and require visualization in three and four dimensions in order to understand the Earth processes at play. Successfully addressing the scientific challenges of Big Data requires integrative and innovative approaches to developing, managing, and visualizing extensive and diverse data sets, but is also critically dependent on effective analytical workflows. This talk will present an emerging agenda and work in progress toward this end at Environmental Systems Research Institute.

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