Building Interactive Data Visualization Systems: A Tool for Light Curve Exploration

Transcript

1. Building Interactive Data Visualization Systems: A Tool for Light Curve Exploration Zhe Wang PhD Student Department of Computer Science University of Arizona
2. Interactive Data Visualization • Make the visual representation of information respond to human input • Human-Data Interaction
3. Why interactive data visualization? Raw Data Data Product Data Vis Data Analysis Data Vis
4. Data Exploration • First step before a formal data analysis • Help the user to get familiar with the dataset • Ask questions you may not even have raw data collection data cleaning data exploration Design models & algorithms Data product
5. Ok, let’s build a vis app for light curves.
6. Light Curve Time(MJD) Magnitude 52665.418 15.894 52677.430 15.835 52712.315 15.712 … …
7. Traditional Light Curve Visualization
8. Traditional Light Curve Analysis
9. Interactive Light Curve Visualization
10. Technical Detail HTML+Javascript(D3) JSON Web Application • Platform Independent • Easy Access
11. Next Step?
13. Real-time Interactive PCA
14. Problem 1: Speed up PCA Calculation • Data Cube • Precompute the intermediate parameters that will be used by PCA • Example (http://vis.stanford.edu/projects/immens/)
15. Speed up PCA calculation • Covariance Matrix a b c … … … extra space for each row in the data cube for d-dimension dataset
16. Problem 2: Speed up PCA Plotting • 1 million points??
17. Speed up PCA Plotting • 1 million points?? Heat map !
18. Speed up PCA Plotting • Specialized Data Structure (For extremely large dataset) 10 20 (5, 20) (5, 15) (15, 20) (5, 10) (10, 15)
19. Demo
20. Technical Detail HTML+Javascript(D3) JSON Client Server Python(Flask) Data Cube
21. Build an interactive visualization system • Overview of the entire dataset + linked charts showing details of subsets. • SVG or Canvas or WebGL? • Special Data Structure
22. Thanks!