1. Table Lens From papers 1 and 2 By Tichomir Tenev, Ramana Rao, and Stuart K. Card

2. Overview Uses focus+Context apporach Context elements are represented graphically Focus elements have text and graphic display

4. Advantages Increases viewable portion of table by 100 times Ease of Navigation Ease of Exploration

5. Table Lens Focal Technique Mutates layout of table Does not bend any rows or columns

7. Distortion Function Framework DOI function: item -> value. Value indicates level of interest DOI function controls how available space is allocated among items

8. DOI in Table lens DOI maps cell address to interest level 2 of them, one for each dimension

10. Manipulation of Focus Operations Zoom- changes amount of space to focal area Adjust- changes amount of contents viewed within focus area Slide- changes location of focus area within the context

12. User manipulation Clicking at upper left corner- zooms all cells Touching any region in context will slide current focus to that location Grasping focus slides focus to that location

13. Results Apply data to baseball stats of 323 rows by 23 columns (7429 cells) Display whole table on screen at one time

16. Paper #2 Design 1 Nesting Focal Levels Space allocated to each element is dependent on the focal level of element 2 foci, Primary focus always inside region of secondary focus 2ndary focus used for coarse navigation Primary used for finer navigation

18. Design II Controlling focal spans Space allocated per data element dependent on focus level and parameter specified by user Primary focus elements may vary in size Spatial map at any time depends on History of user interaction

19. Conclusion Felt design 2 was the better design.

21. Disadvantage Works only for data tables which have have <= number of entries as pixel rows and each column has enough pixels wide to accommodate variables. Paper #2 discusses how to improve it

22. Polaris: A System for Query, Analysis and Visualization of Multi-dimensional Relational Databases Chris Stolte and Pat Hanrahan Standford University

23. Polaris Interactive exploration of large multi- dimensional databases Expressive set of graphical displays Uses tables to organize multiple graphs on a display

24. Relational databases Each row in table = basic entity (tuple) Each column represents a field Fields can be ordinal, or quantitative

26. Visual Specification Is the configuration of the fields of the tables on shelves User does this by dragging and dropping fields onto shelves

27. Visual Specification Mapping of data sources to layers # of rows, columns, and layers, and relative order Selection of tuples from the database Grouping of data within a pane Type of graphic displayed in each pane Mapping of data fields with retinal properties

28. Table Algebra Used to specify table configurations. Dragging and dropping implicitly does it Operands are the names of the ordinal and quantitative fields of database Operators (concatenation, cross, nest)

30. Types of Graphics (Ordinal- Ordinal) Axis variables are independent of each other R represents the fields encoded in the retinal properties of the marks Following slide shows sales and margin as a function of product type, month and state for items sold by coffee chain

32. Ordinal-Quantitative Graphics Bar charts, dot plots, Gantt chart Quantitative variable is dependent of ordinal variable Figure 6c shows a case where a matrix of bar charts is used to study several functions of the independent variables product and month

34. Quantitative-Quantitative Graphics Discover causal relationships between the two quantitative variables. Figure 3e shows how flight scheduling varies with the region of the country the flight originated.

36. Visual mappings Encoding different fields of the data to retinal properties Shape, Size, Orientation, Color Used in the ordinal to ordinal example

37. Generating Database Queries 1. Selecting the Records

38. Generating Database Queries 2. Partitioning the records into pains Putting retrieved records in their corresponding pane

39. Generating Database Queries 3. Transforming Records within the Panes If aggregation, it is done here

40. Results Cut expenses for a national coffee store Create table of scatterplots showing relationship between marketing costs and profit (Figure 6a) Notice trend; certain products have high marketing costs with no or little profit

42. Results Used linked displays to determine that in New York several products are offering very little return despite high costs Creates bar chart for products in New York

43. Future Work Exploring interaction techniques for navigating hierarchical structures of mulit-dim databases Use selected mark in one display as the data input to another