CIS 467/602-01: Data Visualization

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1 CIS 467/62-1: Data Visualization Multiple Views Dr. David Koop CIS 467, Spring 215

2 Visualization Evaluation More details about how studies are developed Use of eye tracking to evaluate visualizations Eye tracking as a measure of user attention Types of studies: expert or heuristic versus user studies CIS 467, Spring 215 2

3 Interaction Overview Change over Time Select Navigate Item Reduction Zoom Geometric or Semantic Attribute Reduction Slice Pan/Translate Cut Constrained Project [Munzner (ill. Maguire), 214] CIS 467, Spring 215 3

4 Multiform [Improvise, Weaver, 24] CIS 467, Spring 215 4

5 Small Multiples sepal length sepal width petal length petal width [ CIS 467, Spring 215 5

6 Overview-ail View [Wikipedia] CIS 467, Spring 215 6

7 Assignment 4 ~dkoop/cis467/assignment4.html Extra regions: Don't need to color extra regions (DC, Puerto Rico) in Part 1 lodash URL issues: use rawgit.com Brushing direction: [Required] Mouse over states highlights corresponding bars [Extra credit] Mouse over bars highlights corresponding states CIS 467, Spring 215 7

8 Linked Views (Juxtaposition & Coordination) Same visual encoding or different? (also highlighting) Do views show the same data, are they showing different data, or is one view showing a subset of the data in another view? How is navigation synchronized between views? CIS 467, Spring 215 8

9 Multiple Views Juxtapose and Coordinate Multiple Side-by-Side Views Linked Highlighting Share Data: All/Subset/None Share Navigation [Munzner (ill. Maguire), 214] CIS 467, Spring 215 9

10 D3 Brushing (Linked Highlighting) Example Date Home Away Score Nov. 15 UMass Dartmouth Norwich Nov. 15 Eastern Connecticut Newbury 96-2 Nov. 15 Southern Maine Maine Farmington Nov. 15 New York U. Western Connecticut Nov. 15 Colby UMass Boston Nov. 15 Williams Rhode Island College Nov. 15 Wheaton (Mass.) Plymouth State Nov. 15 Tufts Keene State Nov. 16 Western Connecticut Juniata Nov. 16 Yeshiva Plymouth State Nov. 16 UMass Dartmouth Colby-Sawyer Nov. 16 Southern Maine Bridgewater State Nov. 16 Babson Rhode Island College Nov. 16 Eastern Connecticut Framingham State Nov. 16 Wellesley Keene State Nov. 18 Rivier Plymouth State Nov. 18 Keene State Amherst Nov. 18 Emmanuel (Mass.) Eastern Connecticut Nov. 19 Southern Maine University of New England Nov. 19 Western Connecticut Sage Nov. 19 WPI UMass Dartmouth Nov. 2 Rhode Island College Emmanuel (Mass.) Nov. 2 Eastern Connecticut Trinity (Conn.) 6-27 Nov. 21 Lasell UMass Boston Nov. 22 UMass Dartmouth Coast Guard Nov. 22 Lyndon St. Plymouth State Nov. 22 Trinity (Conn.) Western Connecticut Nov. 22 Smith Keene State Nov. 22 Rhode Island College WPI Nov. 22 Salem State UMass Boston Nov. 25 Keene State Trinity (Conn.) Nov. 25 Bates Southern Maine 61-6 CIS 467, Spring 215 1

11 Multiple Views All Subset None Same Redundant Overview/ ail Small Multiples Multiform Multiform, Overview/ ail No Linkage [Munzner (ill. Maguire), 214] CIS 467, Spring

12 Schneiderman's Mantra Visual lnformation-seeking Mantra [B. Schneiderman, 1996]: - Overview first - Zoom and filter (Chapter 13) - ails on demand Goal of the overview is to summarize all of the data Want specific details about some aspect(s) of the data, need another view/layer - May be permanent: side-by-side - May be a popup layer: often opaque or separated (see textbook Ch. 6.7) CIS 467, Spring

13 Overview-ail (Same Encoding) [Wikipedia] CIS 467, Spring

14 Overview-ail (Different Encoding) EXPENDITURES BY FUNCTION (BAR & DONUT) EXPENDITURES BY CAMPUS FY 212 reset Academic Support Auxiliary Enterprises Depreciation and Amortization Impairment of Capital Assets Institutional Support Instruction Interest Medical Centers Operation and Maintenance of Plant Other Public Service Research Student Financial Aid Student Services 5k 1M 1.5M 2M 2.5M CIS 467, Spring 215 5M 4.5M 4M 3.5M 3M 2.5M 2M 1.5M 1M 5k 1M 5M Berkeley 28 Davis Irvine Los Angeles FIVE-YEAR TREND 21 Merced Riverside San Diego San Francisco Santa Barbara 212 Santa Cruz [S. Quigley, 14

15 Overview-ail (with Zoom-Filter) ail involves some subset of the full dataset Involves user selection or filtering of some type How question: includes facet Examples: - Maps: partition into two views with same encoding, overviewdetail - UC Trends: partition into multiple views, coordinated with linked highlighting, overview+detail of expenditures CIS 467, Spring

16 Multiform & Small Multiples (Cerebral) [Barsky et al., 28] CIS 467, Spring

17 Navigation across multiple views Often navigation in one view updates navigation in another Example: Maps: overview shifts as you move around in detail view Selections in one view may trigger selections in another CIS 467, Spring

18 Multiple Views Partition into Side-by-Side Views Superimpose Layers [Munzner (ill. Maguire), 214] CIS 467, Spring

19 Partitioned Views Split dataset into groups and visual each group Extremes: one item per group, one group for all items Can be a hierarchy - Order: which splits are more "related"? - Which attributes are used to split? usually categorical CIS 467, Spring

20 Glyphs, Views, and Regions Glyphs are composed of multiple marks Views are a contiguous region of space A region is usually associated with a group of data Blurry lines of distinction between them CIS 467, Spring 215 2

21 Example: Grouped Bar Chart 1M 9.M 8.M 7.M Population 65 Years and Over 45 to 64 Years 25 to 44 Years 18 to 24 Years 14 to 17 Years 5 to 13 Years Under 5 Years 6.M 5.M 4.M 3.M 2.M 1.M. CA TX NY FL IL PA [M. Bostock, CIS 467, Spring

22 Example: Small Multiples Bar Chart Group 4 Group 3 Group 2 Group 1 Q18 Q28 Q38 Q48 Q19 Q29 Q39 Q49 [M. Bostock, CIS 467, Spring

23 Matrix Alignment & Recursive Subdivision Matrix Alignment: - regions are placed in a matrix alignment - splits go to rows and columns - main-effets ordering: use summary statistic to determine order of categorical attribute Recursive subdivision: - Designed for exploration - Involves hierarchy - User drives the ways data is broken down in recursive manner CIS 467, Spring

24 Example: Trellis Matrix Alignment Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuna No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Svansota Waseca Waseca Crookston Crookston Morris Morris.i :31 University Farm University Farm Duluth Duluth Grand Raoids Grand Raoids Barley Yield (bushels/acre) Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota Trebi Wisconsin No. 38 No. 457 Glabron Peatland Velvet No. 475 Manchuria No. 462 Svansota 1932 o 1931 I I I I Waseca Crookston Morris University Farm Duluth Grand Rapids I:) Barley Yield (bushels/acre) [Becker et al., 1996] CIS 467, Spring

25 F Ter Islin Barking Flat Ter Ter City offlat London Flat Kingston M Ter A Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Harrow Barnet Enfield Haringey Waltham Forest Redbridge Havering Sem F Hammer Example: HiVE System Flat Flat Mert Havering T Newham Ter Se Flat Ter Flat Westminster Ter Flat Ter Fl Harrow B Se Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Hillingdon Brent Camden Westminster Hackney Newham Barking Flat Ter Fl Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Fl Hounslow Ealing Hammersmith Kensington Islington Tower Hamlets Greenwich Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Richmond Kingston Merton Wandsworth City of London Southwark Bexley Se E Hounslow Se Flat Ter Fl K Richmond Se Flat Ter Flat Ter Flat Ter Flat Ter Flat Ter Fl Sutton S Croydon Lambeth C CIS 467, Spring 215 B Hillingdon Lewisham Bromley Se [Slingsby et al., 29] 25

26 oloured by number of sales: shier(/,$gd,$yr,$mn); y average price: ocolor(/,3,$prc). Barnet Harrow Haringey BrentCamden Ealing Islington Wandsworth Richmond Merton Tower Hamlets Southwark Hammersmith Hillingdon Kensington Newham City of London Greenwich Bromley Sutton Enfield Redbridge Havering Barking Barnet Harrow Bexley Lewisham Haringey BrentCamden Ealing Waltham Forest Enfield Havering Barking Hackney Westminster Hounslow Bromley Sutton Redbridge Croydon Merton Bexley BrentCamden Ealing Lambeth Richmond Greenwich Lewisham Haringey Kingston Wandsworth Tower Hamlets Southwark Hounslow Newham City of London Lambeth Kensington Havering Barking Waltham Forest Islington Flat Westminster Barnet Harrow Islington Newham Havering Barking Hackney Hillingdon Redbridge Redbridge Waltham Forest Bromley Enfield Croydon Bexley BrentCamden Ealing Islington Southwark Greenwich Haringey Hammersmith mi Tower Hamlets Barnet Harrow Kingston Barking Hillingdon Newham Enfield Havering Hillingdon Redbridge Waltham Forest Example: HiVE System Redbridge Havering Barking Bexley Bromley CIS 467, Spring 215 Merton Sutton Wandsworth Richmond Bromley C Merton Sutton Lambeth Hounslow Newham City of London Tower Hamlets Southwark Hammersmith Bexley Hackney Greenwich Lewisham Bexley Croydon Southwark Kingston Richmond Greenwich Lewisham Westminster Kensington Kingston Wandsworth Southwark Hounslow Tower Hamlets Croydon Westminster Kensington Newham City of London Lambeth Greenwich Hammersmith et Ter Tower Hamlets Hackney Bromley [Slingsby et al., 29] 26

27 Superimposed Layers Put different layers in the same spatial region, overlay information Usually each layer spans the entire view Must be identifiable: visually distinguishable Cartography has to deal with this a lot May be static or dynamic (user controls which layers are shown) CIS 467, Spring

28 Example: Superimposed Line Charts 8 Temperature (ºF) 7 Austin 6 New York San Francisco October November December 212 February March April May June July August September [M. Bostock, CIS 467, Spring

29 Example: Hierarchical Edge Bundles [D. Holten, 26] CIS 467, Spring

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