Stack Zooming for Multi-Focus Interaction in Time-Series Data Visualization

1. Stack Zooming forMulti-Focus Interaction inTime-Series Data Visualization Waqas Javed (wjaved@purdue.edu)Niklas Elmqvist (elm@purdue.edu) Presented by Jean-Daniel Fekete

2. Motivation: Multi-Focus Interaction Multiple Focus Regions Motivation Mélange [Elmqvist 2008]

3. Outline • Stack Zooming • Introduction • Stack zooming in detail • Layout and correlation graphics • Stack zooming in action • The TraXplorer System • System design • Visual interface • Video Demonstration • Summary • Future Work

4. Introduction • Time-series data tends to be long and often its analysis requires comparison across multiple focus regions • Current time-series visualization tools have limited support for comparing several foci while retaining context • Stack zooming is a method for supporting this kind of multi-focus interaction in time-series data exploration • Based on building hierarchies of stacked 1D strips • Each subsequent stack represents a higher zoom level • Sibling strips represent branches in the visual exploration

5. Layout and Correlation Graphics • Stack zooming is based on creating a stack of zoom areas • Nodes in a zoom stack are laid out on the visual substrate using a space-fillinglayout algorithm • Splits the vertical space by the depth of the zoom stack • Splits the horizontal space by the number of siblings at each level

6. Layout and Correlation Graphics Layout allocations can be changed by dragging the borders of a strip The order of child strips for each level in the zoom stack is significant for conveying the positions of the displayed intervals of a time series The layout manager will always order child strips for each level in the zoom stack to be the same as the order of their intervals on the parent strip

7. Layout and Correlation Graphics • Relationships between parent and child strips in adjacent levels of zoom stack must be visible • Focus • Context • Distance awareness • We discuss three different correlation graphics that visually indicate the relationships between different visual strips in the zoom stack

8. Layout and Correlation Graphics • Color-coded zoom areas: • Parent strips show color-coded semi-transparent selection areas • Indicates the position and extents of each child strip in the time series Color-coded strip frames: Child strips have color-coded frames that correspond to the color of its parent selection area This gives a visual link between parent and child

9. Layout and Correlation Graphics • Color-coded zoom areas: • Parent strips show color-coded semi-transparent selection areas • Indicates the position and extents of each child strip in the time series • Color-coded strip frames: • Child strips have color-coded frames that correspond to the color of its parent selection area • This gives a visual link between parent and child

10. Layout and Correlation Graphics • Correlation links: • Explicit correlation links drawn as dotted lines and arrows from zoom areas in parents to the children • Allows for quickly understanding the correlation structure • May be shown in a transient overlay to minimize visual clutter

11. Stack Zooming in Action When the user begins to analyze the dataset, the whole display is taken up by the full time series drawn as a line visualization on a single strip

12. Stack Zooming in Action Using a drag on the surface of this strip, the user can create a child strip of the main strip that displays the selected subset of the time data

13. Stack Zooming in Action Additional zoom operations on any of the dataset strips will create additional children in the zoom stack

14. The TraXplorer System

15. System Design • TraXplorer is designed to support a communication-minded iterative workflow • Exploration • Collaboration within the analysis team • Dissemination to external stakeholders

16. The Visual Interface • Components: • Main visualization window • Data box • Layer control box • Presentation tree window

17. The Main Visualization Window The main visualization window is a visual space supporting stack zooming Contains a visualizations of time-series data on a common time axis and potentially different value axes Visualization type is independent of the layout management Our implementation currently supports basic line graphs, filled line graphs, and horizon graphs

18. The Layer Control Box Each data series is a unique layer in TraXplorer The layer control box can be used to move, to delete, and to toggle the visibility of individual tracks, as well as to change color mapping, transparency, and track title Used to determine which track should be used for the value axis labels

19. The Layer Control Box Two or several tracks can be linked to use the same scale for the value (Y) axis, thereby supporting direct comparison of values

20. The Data Box • The data box displays local statistics about the currently selected region • Detail-on-demand for computing measures for a particular track • Min/max, average, median, standard deviation, etc • Add comments to any particular track • Checkboxes to add this data to the visual display of the track

21. The Presentation Tree The presentation tree is a hierarchical representation of the zoom stack The analyst can prune, move, or hide individual zoom nodes (i.e. child strips) using the presentation tree to refine the presentation Can access the exploration history using the presentation tree to linearizethe combined exploration sessions of the data similar to a slideshow presentation suitable for presentation to the audience

22. Video

23. Summary • Theoretical background of a novel multi-focus interaction technique called stack zooming • Multiple focus points in time-series dataset visualizations • Context, distance, and relationships between time-series • The TraXplorer implementation • A visual interface to support the time series exploration • Supports stack zooming • Communication-minded workflow

24. Future Work Study the empirical performance of the tool in comparison to similar tools Improve the tool to better support collaborative visual exploration settings involving teams of analysts working together Study how the tool can help analysts fill different roles in the analysis process

25. Questions? http://web.ics.purdue.edu/~wjaved/projects/stackzooming Merci JD!!! Contact information: Waqas Javed wjaved@purdue.edu Thanks!