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

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In this IEEE PacificVis 2010 presentation, we introduce a method for supporting multi-focus interaction in time-series datasets that we call stack zooming. The approach is based on the user interactively building hierarchies of 1D strips stacked on top of each other, where each subsequent stack represents a higher zoom level, and sibling strips represent branches in the visual exploration. Correlation graphics show the relation between stacks and strips of different levels, providing context and distance awareness among the focus points.

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  • Consider a stock market analyst trying to use line graph visualizations to analyze a stock market data set spans over a long period of time. It is often the case that the analyst want to compare different subsets of the whole dataset with one another. This kind of comparison can be supported by providing multiple-focus interaction. Where each focus region correspond to a particular subset.In the earlier work by one of the author, a space folding technique Melange is introduced to support Multi-focus interaction.This work is about a space filling technique Stack Zooming to support Multi-focus interaction for time series data.
  • In this presentation, I will first introduce the stack zooming technique that allows the support for a side by side comparison among multiple focus regions.Next, I will discuss the working and functionalities of the TraXploer system that is designed to support stack zooming. I will talk about the visual interface of the tool and how it provide support for collaboration and dissemination.Towards the end of the presentation I will play a video demo of the tool.
  • The TRAXPLORER system is a time-series visualization tool that support multi-focus interaction using the stack zooming technique while analyzing one or more time series.
  • In the exploration phase an individual, or potentially a number of analysts, explores the time series data. To collaborate in a team an analyst can save the exploration session and can also add the comments to each visual strip. In the dissemination phase, the analyst can use the presentation tree interface of the traXplorer system.
  • Stack Zooming for Multi-Focus Interaction in Time-Series Data Visualization

    1. 1. Stack Zooming forMulti-Focus Interaction inTime-Series Data Visualization<br />Waqas Javed (wjaved@purdue.edu)Niklas Elmqvist (elm@purdue.edu)<br />Presented by Jean-Daniel Fekete<br />
    2. 2. Motivation: Multi-Focus Interaction<br />Motivation<br />Mélange [Elmqvist 2008]<br />Multiple Focus Regions<br />
    3. 3. Outline<br />Stack Zooming<br />Introduction<br />Stack zooming in detail<br />Layout and correlation graphics<br />Stack zooming in action<br />The TraXplorer System<br />System design<br />Visual interface<br />Video Demonstration<br />Summary<br />Future Work<br />
    4. 4. Introduction<br />Time-series data tends to be long and often its analysis requires comparison across multiple focus regions<br />Current time-series visualization tools have limited support for comparing several foci while retaining context<br />Stack zooming is a method for supporting this kind of multi-focus interaction in time-series data exploration<br />Based on building hierarchies of stacked 1D strips<br />Each subsequent stack represents a higher zoom level<br />Sibling strips represent branches in the visual exploration<br />
    5. 5. Layout and Correlation Graphics<br />Stack zooming is based on creating a stack of zoom areas<br />Nodes in a zoom stack are laid out on the visual substrate using a space-fillinglayout algorithm<br />Splits the vertical space by the depth of the zoom stack <br />Splits the horizontal space by the number of siblings at each level<br />
    6. 6. Layout and Correlation Graphics<br />Layout allocations can be changed by dragging the borders of a strip<br />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<br />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<br />
    7. 7. Layout and Correlation Graphics<br />Relationships between parent and child strips in adjacent levels of zoom stack must be visible<br />Focus<br />Context<br />Distance awareness <br />We discuss three different correlation graphics that visually indicate the relationships between different visual strips in the zoom stack<br />
    8. 8. Layout and Correlation Graphics<br />Color-coded zoom areas:<br />Parent strips show color-coded semi-transparent selection areas <br />Indicates the position and extents of each child strip in the time series<br />Color-coded strip frames: <br />Child strips have color-coded frames that correspond to the color of its parent selection area<br />This gives a visual link between parent and child<br />
    9. 9. Layout and Correlation Graphics<br />Color-coded zoom areas:<br />Parent strips show color-coded semi-transparent selection areas <br />Indicates the position and extents of each child strip in the time series<br />Color-coded strip frames: <br />Child strips have color-coded frames that correspond to the color of its parent selection area<br />This gives a visual link between parent and child<br />
    10. 10. Layout and Correlation Graphics<br />Correlation links: <br />Explicit correlation links drawn as dotted lines and arrows from zoom areas in parents to the children<br />Allows for quickly understanding the correlation structure<br />May be shown in a transient overlay to minimize visual clutter<br />
    11. 11. Stack Zooming in Action<br />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<br />
    12. 12. Stack Zooming in Action<br />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<br />
    13. 13. Stack Zooming in Action<br />Additional zoom operations on any of the dataset strips will create additional children in the zoom stack<br />
    14. 14. The TraXplorer System<br />
    15. 15. System Design<br />TraXplorer is designed to support a communication-minded iterative workflow<br />Exploration<br />Collaboration within the analysis team<br />Dissemination to external stakeholders<br />
    16. 16. The Visual Interface<br />Components:<br />Main visualization window<br />Data box<br />Layer control box<br />Presentation tree window<br />
    17. 17. The Main Visualization Window<br />The main visualization window is a visual space supporting stack zooming<br />Contains a visualizations of time-series data on a common time axis and potentially different value axes<br />Visualization type is independent of the layout management<br />Our implementation currently supports basic line graphs, filled line graphs, and horizon graphs<br />
    18. 18. The Layer Control Box<br />Each data series is a unique layer in TraXplorer<br />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<br />Used to determine which track should be used for the value axis labels<br />
    19. 19. The Layer Control Box<br />Two or several tracks can be linked to use the same scale for the value (Y) axis, thereby supporting direct comparison of values<br />19<br />
    20. 20. The Data Box<br />The data box displays local statistics about the currently selected region<br />Detail-on-demand for computing measures for a particular track<br />Min/max, average, median, standard deviation, etc<br />Add comments to any particular track<br />Checkboxes to add this data to the visual display of the track<br />
    21. 21. The Presentation Tree<br />The presentation tree is a hierarchical representation of the zoom stack<br />The analyst can prune, move, or hide individual zoom nodes (i.e. child strips) using the presentation tree to refine the presentation<br />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<br />
    22. 22. Video<br />
    23. 23. Summary<br />Theoretical background of a novel multi-focus interaction technique called stack zooming<br />Multiple focus points in time-series dataset visualizations <br />Context, distance, and relationships between time-series<br />The TraXplorer implementation <br />A visual interface to support the time series exploration <br />Supports stack zooming<br />Communication-minded workflow<br />
    24. 24. Future Work<br />Study the empirical performance of the tool in comparison to similar tools<br />Improve the tool to better support collaborative visual exploration settings involving teams of analysts working together<br />Study how the tool can help analysts fill different roles in the analysis process<br />
    25. 25. Questions?<br />Thanks!<br />http://web.ics.purdue.edu/~wjaved/projects/stackzooming<br />Merci JD!!!<br />Contact information: <br />Waqas Javed<br />wjaved@purdue.edu<br />

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