The Table Lens: Merging Graphical and Symbolic Representations for Interactive Tabular Visualization

1. The Table Lens: Merging Graphical and Symbolic Representations in an Interactive Focus+Context Visualization for Tabular InformationRamana Rao and Stuart K. Card(pgs. 343-349)

2. Introduction • Uses a focus+context (fisheye) technique. • Allows display of crucial label info. and multiple distal focal areas. • Created because of limitations in traditional spreadsheet applications.

3. Comparison to Traditional Spreadsheet Application • The size of the information set which users can display limits the ability of users to address complex problems. • Excel can only display a max of 660 cells on a 19’ display. • Table Lens can display 30-100 times as many cells, depending on task.

4. Other Advantages of Table Lens • Merges graphical representations directly into the tables (automatic plots integrated into cells). • Allows humans to spot patterns and features much easier. • Makes exploration of data much more interactive and natural.

5. Focus+Context Technique • Supports visualizing an entire information structure at once or zooming in on specific items. • Evolved from other similar techniques: • Bifocal Display • Furnas’s Fisheye • Perspective Wall • Document Lens

6. Focus+Context Technique • Table Lens mutates the layout of a table without bending any rows or columns. • Distorts based on cell boundaries. • Distortion in each of the two dimensions is independent from the other. • Allows for easy horizontal and vertical eye scanning. • Enables label display, multiple focal areas, and multiple focal levels.

7. Focus+Context Technique • 4 types of cell regions are created by the distortions on the two axis: • Focal • Row focal • Column focal • Nonfocal • Focal data is textual, while nonfocal data is graphical.

8. Focus+Context Technique

9. The Distortion Function • Core based on Degree of Interest (DOI) function. • Maps from an item to a value that indicates the level of interest in the item. • Used to control how available space is allocated. • Transfer function • Maps uniformly distributed cell addresses to “interest-warped” physical locations.

10. The Distortion Function • Similar to Bifocal Display, except there are 2 independent distortions on vertical and horizontal. • Contrasts with Perspective Wall and Document Lens which map z-surfaces over a flat plane.

11. Interactive Manipulation of the Focus • 3 main types: • Zoom • Changes amount of space without changing number of cells. • Adjust • Changes amount of contents without changing the amount of space (size of focal area). • Slide • Changes location of entire focus area.

12. DOI DOI DOI Slide Zoom Adjust Interactive Manipulation of the Focus • Visualizing the DOI function as the three manipulations are performed:

13. Interactive Manipulation of the Focus • A 4th type of manipulation is a coordinated adjust and zoom (adjust-zoom). • Used to increase or decrease the number of focal cells w/o affecting their size. • Multiple focal levels creates a complex design space, when individual focal areas are formatted differently from each other.

14. Graphical Mapping Scheme • Designed for most common type of table: • Cases-by-variable array (Relational database) • Cases are the rows and values of the various variables (across cases) are in the columns. • Number of different types of graphical representations (presentation types) are used. • e.g. Text, color, shading, length, and position

15. Graphical Mapping Scheme • Presentation type determined by 6 factors: • Value • Value Type • Region Type • Cell Size • User Choices • Spotlighting

16. User Interface • Small number of key commands, but most of the time mouse gestures can be used exclusively. • Left mouse button click is for “touching.” • Left mouse button held down is for “grasping.” • Right mouse button brings up menu for selecting a focal area and spotlighting it, etc.

17. User Interface • Grasping control points on a focus allows adjust-focus manipulation. • Touching a context region will slide the current focus there. • You can also grasp and drag a focus to a different region.

18. User Interface • Columns can be rearranged by grasping the column label. • Columns can be sorted by clicking on the column label. Click a second time on the label to toggle between ascending and descending orders.

19. Critique • Strengths • Supports effective interaction with very large tables • Merges graphical representations directly into the process of table visualization and manipulation • Efficient display of cell values • Easily detect patterns and features, and find relationships between variables. • Good for tabular and proportional data.

20. Critique • Weaknesses • Not useful for non-tabular data. • Large number of attributes (many columns) may make scanning variables difficult.

21. Table Lens as a Tool for Making Sense of DataPeter Pirolli and Ramana Rao(pgs. 597-615)

22. Introduction • Compares performance of the Table Lens and Splus (a more traditional, command-based graphical tool) in an Exploratory Data Analysis (EDA) task.

23. Introduction • Focus on 2 typical EDA (Sensemaking) tasks involving multivariate datasets: • Assessing a batch of data and finding the features of each variable. • Finding lawful relations among a set of observed variables.

24. Sensemaking • Refers to activities in which external representations such as texts, tables, or figures are interpreted into some meaningful manner. • The data is basically summarized and abstracted differently.

25. Sensemaking • Learning Loop Complex • Search for representations to capture important regularities. • Information is encoded into the representation. • Ill-fitting residue information leads search for more accurate, informed representation. • Representation drives search for information.

26. Sensemaking • Human problem solver is viewed as an information-processing system with a problem. • Data = Fit + Residual • Example: Developing an equation that predicts a dependent variable value based on an independent variable value.

27. Representative EDA Tasks • Involves uncovering (like a detective) regularities, irregularities, and relationships between variables. • This paper focuses on the two tasks mentioned in the introduction.

28. Representative EDA Tasks • First task involves browsing the values of each variable (i.e. scanning columns in Table Lens). • Assess the following: • Batch symmetry • Spread • Outliers • Clusters • Multiple nodes

29. Representative EDA Tasks • Second task is an iterative process • First step is to find a candidate variable that highly correlates with another variable of interest. • Find possible effects of additional independent variables to further explain the residual.

30. EDA Tools Comparison • Splus and Excel are more richly featured than Table Lens.

31. EDA Tools Comparison • Table Lens • Classifying the shape and skew is a skill that is somewhat different with a batch of values than it is for a histogram. • Sorting is first step in correlation search. • Scan across columns to identify other columns which show similar trend to sorted column. • Column can be formatted to focus on 5 value summary.

32. EDA Tools Comparison • Splus • User invokes a “brush tool” which is a matrix of scatterplots. • Histogram can also be displayed for each variable. • Batch assessment can be done by looking at histograms. • Can also invoke a stem-and-leaf plot or box plot. • Cross variable correlation done by scanning row for scatterplots with strong trends (lines).

33. GOMS analysis • Explore space of content and possible courses of actions available before exploiting them. • Breakdown of actions required for each step of task.

34. Results of GOMS analysis • It may be more efficient to iterate through a batch of variables in Table Lens. • Table Lens achieves comparable performance with Splus, but it is also a much simpler interface that is easier to learn.

35. Design Refinement • Boxplots • Horizontal extent of a Table Lens column represents a coordinate system. • Boxplot could be superimposed • Rows representing outliers can have different-colored bars. • Direct Manipulation • “ladder of powers” • Tames non-linearities • Create manipulation that allows transforming the column interactively. • Slider or control points on curve.

36. Design Refinement • Variable permutations • More correlated variables (columns) on each side of the sorted variables are automatically brought close together. • Fit marks and residual curves • Allows user to see how closely data in one variable really correlates with data in another variable. • Allows user to see shape of residual data and then separate this data into a separate column.