Scientific Data Visualization using WorldWide Telescope


October 11, 2010


As described in the book, The Fourth Paradigm: Data-Intensive Scientific Discovery, scientific breakthroughs will be increasingly powered by advanced computing capabilities that help researchers manipulate and explore massive datasets.

This tutorial uses three case studies to demonstrate the application of a wide range of technologies: .NET parallel extension on multicores, distributed computing on multiple nodes with Dryad/DryadLINQ, Windows Azure, HPC, data processing automation through workflows, and visualization in WorldWide Telescope. We hope that the techniques and technologies used are applicable in other data-intensive research.

WorldWide Telescope (WWT) enables your computer to function as a virtual telescope, bringing together imagery from the best ground and space-based telescopes in the world. We are working on extending WWT to visualize scientific data on Earth.

The three use case studies are: WWT LCAPI (Loosely Coupled API), TeraPixel, and MODISAzure. We will demonstrate how to use WWT to visualize the results from these projects.

LCAPI: The Worldwide Telescope “Loosely Coupled API” uses the Restful communication style between a standalone application (SA) and a Worldwide Telescope Client (WTC). We will explore using this loosely coupled interface to read time-series event data into the SA, push this data to the WTC Layer manager, control WTC Layer-based data rendering, and control WTC state (location, perspective angles, time, and time rate). From this overview we will explore both what the LCAPI enables and the potential for future directions in visualization.
Terapixel Sky image – creating the largest and clearest image of the sky from the Digitized Sky Survey data. We turned 1,800 pairs of red and blue individual image plates into 1,800 colored plates, adjusted brightness of each pixel on each plate, and stitched and smoothed them together into a terapixel sky image. The image is then visualized by the WorldWide Telescope.
MODISAzure – accessing the vast and varied remote sensing data from the MODIS (Moderate Resolution Imaging Spectroradiometer) on NASA’s Terra satellite and other data sources to study evapotranspiration (ET), which is key to water balance, hence key to understanding interactions between global climate change and the biosphere. We will demonstrate how we generated time series monthly ET maps for the state of California from MODISAzure results to visualize them in WWT. Learn more about MODISAzure.


Dean Guo, Rob Fatland, Christophe Poulain, and Catharine van Ingen

Catharine has a wealth of experience in hardware, including work with the Alpha machine and MIPS processor teams, and in industrial-strength software for algorithms used to manage water flows, logging data from particle accelerator detectors, and buying Mickey Mouse watches over the Internet.