Organization of 2D Space
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- Rodney Preston
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1 Organization of 2D Space Linear Frequency is Mapped in 2D Space Linear frequency time series, bar charts, histograms, etc. feature 2possible more sets of information Most data have multi-dimensional and multivariate metadata that can be effectively charted Linear frequency may not fully describe multivariate data but. 1
2 All checkouts of "Catcher in the Rye, Anis Haron! Click for Interactive Version Hot Topics , Patrick Rudolph! 2
3 " Statistical " Narrative " Play of the Imagination " Visual Explorations Hot Topics , Patrick Rudolph! Arc Diagram: Bible Studies 3!
4 Histogram-like map with boxplot!" Select Boxplot: Five Number Summary!" Outliers!" Spread with!" Upper quartile!" Median!" Lower quartile 4!
5 SPL has Multi-dimensional Data ItemNumber: // Unique to each specific item BibNumber: // Unique to each bib record Ckodate: Ckotime: 16:55:00 Ckidate: Ckitime: 18:21:00 Collcode: nanf // where its located, what it is, etc. Itemtype: acbk Barcode: // Like ItemNumber Title: Untangling my chopsticks, a culinary sojourn in Kyoto CallNumber: R358U 2003 DeweyClass: Keywords: Cookery Japanese, Japanese tea ceremony, Kyoto Japan Social life and customs, Food habits Japan Kyoto Boxplot: Five Number Summary!" Outliers!" Spread with!" Upper quartile!" Median!" Lower quartile 5!
6 Analysis of check-out items in 2007, Yung-Ting Chuang! Boxplot: Five Number Summary 6
7 Parallel Coordinates: Multi-dimensional Data ogy Parallel Coordinates: Multi-dimensional Data 7!
8 Scatter Plots A diagram using Cartesian coordinates to display values for two variables for a set of data The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis Easy to identify outliers Scatterplot: Summary of a set of bivariate data Potential association between two variables 8
9 Scatterplot: Summary of a set of bivariate data!" Clustering to show change over time Combine Scatterplot with 2D matrix 9!
10 2S Spatial Maps NY Times Sector Snapshot 10
11 2D Spatial Maps 2D Spatial Maps 11
12 2S Spatial Maps E.J. Marey Bivariate Data Train Schedule (1880s) 12
13 Time Graphs George Legrady! Winter 2006! 25! 13!
14 14!
15 Mosaic Plots A Graphical Display that visualizes the relationship among two or more categorical variables Categorical: No intrinsic ordering (Itemtypes) Ordinal: Clear ordering: CollCode Interval: Ordinal variable equally spaced (Dewey) Mosaic Plots A Graphical Display that visualizes the relationship among two or more categorical variables Categorical: No intrinsic ordering (Itemtypes) Ordinal: Clear ordering: CollCode Interval: Ordinal variable equally spaced (Dewey) 15
16 Dimensional Mosaic Plot: Spatially conveys 4 variables: xpos,ypos, height, width TreeMap: SmartMoney (Schneiderman/Wattenberg) 16!
17 Kohonen Self-Organizing Map Algorithm Visualizing knowledge domain spatially using Kohonen (Skupin) 17!
18 InfoGraph: 50 loneliests islands Visual Complexity: Visualizing Networks 18!
19 Visual Network Bertin: Semiology of Graphics!" Cartographer: published 1967!" Theoretical foundation for Information Visualization!" Information Visualization: The visualization of abstract data!" Semiology: the study of signs and how they convey meaning!" What are the basic units by which meaning is created in a visual system? 19!
20 Bertin: Reorderable Matrix!" Data are often presented in a table or chart whose rows and columns are intrinsically unordered, but which are arranged in an order which conceals patterns, rather than reveal them.!" Bio-infomatics use re-ordering to make patterns more visible Labeling Issues 2D Spatial Maps 20!
21 Bertin: Reorderable Matrix US Political History: Alphabetical 2D Spatial Maps 21!
22 US Political History: Most recent results 2D Spatial Maps US Political History: 3 regions 2D Spatial Maps 22!
23 Kosara: US Political History 2D Spatial Maps Bertin: Reorderable Matrix!" Data are often presented in a table or chart whose rows and columns are intrinsically unordered, but which are arranged in an order which conceals patterns, rather than reveal them.!" Bio-infomatics use re-ordering to make patterns more visible 23!
24 US Political History 2D Spatial Maps 24!
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