Information visualization: presentation

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Information about Information visualization: presentation

Published on March 13, 2014

Author: kverbert


13/03/14 pag. 1 Information visualization lecture 4 presentation Katrien Verbert Department of Computer Science Faculty of Science Vrije Universiteit Brussel

13/03/14 pag. 2 Support  for  report  prepara+on.  Many  sources  of  content  are  visible  and  ready  to  hand   A problem

13/03/14 pag. 3 The presentation issue present (tr.v): to offer to view; display.

13/03/14 pag. 4 overview Space  limita+ons     •  Scrolling   •  Overview  +  detail   •  Distor+on   •  Suppression   •  Zoom  and  pan           Time  limita+ons     •  Rapid  serial  visual   presenta+on   •  Eye-­‐gaze                

13/03/14 pag. 5 Space limitations

13/03/14 pag. 6 7.1 A PROBLEM Many of us have found ourselves with a report that has to be completed by a deadline, with the result (Figure 7.1) that the dining room table, extended to its 12- guest state, is covered by piles of paper as well as reports, books, clippings and slides; perhaps with more arranged on the floor and on a couple of chairs. There may even be piles on top of piles. Such a presentation of vital information makes a lot of sense: everything relevant is to hand (hopefully!) and, moreover, its very visibility acts as a reminder (Bolt, 1984, page 2) of what might be relevant at any particular juncture, possibly triggering a situated action (Suchman, 1987). In this environment I can concentrate on creative tasks rather than organisation. Despite the availability of high-resolution displays and powerful workstations I still write most of my reports in this way. Why? Because the display area provided by the typical workstation is far too small to support, visibly, all the sources that are relevant to my composition. 7.2 THE PRESENTATION PROBLEM I am not alone in the sense of having too much data to fit onto a small screen. A very large and expensive screen, for example, would be needed to display the London Underground map in sufficient detail(Figure 1.1), and it would be difficult or impossible to present, on a normal display, the complete organisation chart of IBM or ICI. Moreover, the recent emergence of small and mobile information and communication devices such as PDAs and wearable displays has additionally identified a pressing need for a solution to the ‘ too much data, too little display area’ problem: the presentation problem. How can it be solved, mindful of the need to support the activity of visualising the underlying data? 7.2.1 Scrolling An obvious solution is to scroll the data into and out of the visible area. In other words, to provide a means whereby a long document can be moved past a window until it reaches the required ‘page’ (Figure 7.2). This mechanism is widely used, but carries with it many penalties. One relates to the "Where am I?" problem: I’m working on Chapter 2, (it may be section 2.3, I don’t know) and I want to remind myself of a figure that is in chapter 5, it may be in section 5.3 – or was it 5.6? All I can do is operate the scrolling mechanism and look out for the figure I need, albeit assisted by various cues such as the page number indicated in the scrolling mechanism. With a scrolling mechanism, most of a document is hidden from view. I have the same problem when using a microfilm reader, with the additional complication that if I move the tray to the left, the image moves to the right. A similar difficulty applies to my use of the famous London ‘AtoZ’ street directory. I’m driving along a road that goes off the edge of the page, so I desperately need whatever page contains the continuation of that road (and quickly!). Even if I get it, I will typically have trouble locating the same road on the new page. These and other similar problems can be ameliorated by the provision of context. Much of this chapter, in fact, is concerned with deciding how to provide context. Scrolling

13/03/14 pag. 7 Overview + detail

13/03/14 pag. 8 Source:  Courtesy  Colin  Grimshaw   Overview + detail

13/03/14 pag. 9 Overview + detail hDp://    

13/03/14 pag. 10 A  journey  north  towards  Halifax  requires  detail  of  the  town  (Huddersfield)  through  which   the  traveller  passes   Overview + detail

13/03/14 pag. 11 The  use  of  a  real  or  digitally  simulated  magnifying  glass  masks  detail  around  the  magnified  region     Overview + detail

13/03/14 pag. 12 The  DragMag  technique  allows  flexible  posi+oning  of  the  region  to  be  magnified     Overview + detail

13/03/14 pag. 13 Connection between the detail and overview presentations missing Overview + detail Issues?  

13/03/14 pag. 14 Focus + context

13/03/14 pag. 15 Metaphor  illustra+ng  the   principle  of  the  Bifocal  Display   (a) An information space containing documents, emails, etc. (b) The same space wrapped around two uprights. (c) Appearance of the information space when viewed from an appropriate direction direction of view Distortion

13/03/14 pag. 16 An early illustration of the bifocal display principle

13/03/14 pag. 17 An early illustration of the bifocal display principle

13/03/14 pag. 18 Bifocal display features 1.  Distortion: available display area is allocated to two different regions –  Focus  (undistorted)   –  Context  (distorted)   2.  Information moves smoothly and continuously from context to focus 3.  Display affords for representation –  opportunity  to  use  two  dimensions   –  for  instance,  +me  assigned  to  horizontal  axis   –  type  of  item  to  Y-­‐axis   4.  Main purpose –  Focus:  provide  detail   –  Context:  awareness  and  iden6fica6on     5.  Manual control

13/03/14 pag. 19 What is the Bifocal Display Doing? Transforming the information space to the display space 7.19   Informa+on   space   Display   Space   Normal display Informa+on   space   Display   Space   Bifocal   display   context   focus   Slide  source:  Ken  Brodlie  

13/03/14 pag. 20 A  sequence  of  amino  acids  within  a  protein   Source:  Courtesy  of  Tom  Oldfield   Applications of distortion technique

13/03/14 pag. 21 Table lens without distortion

13/03/14 pag. 22 Table lens with distortion

13/03/14 pag. 23 Table Lens: demo hDp://    

13/03/14 pag. 24 Schematic representation of X-distortion

13/03/14 pag. 25 Schematic representation of combined X- and Y- distortion

13/03/14 pag. 26 hDp://    

13/03/14 pag. 27 Distorted presentation of the London Underground map

13/03/14 pag. 28 11Sun 12 Mon 13 Tue 14 Wed 15 Thur 16 Fri 17Sat Fly LA Kathy to airport Model Maker Check slides, notes. Family barbeque Fly LHR Kathy to collect Chapter 2/ see Dave March JulyJuneMayAprilMar Aug Sept Oct Flight to SFO Tutorial set-up Tutorial United flight Heathrow Pointer Color OHs Jane+John Call Kathy Combined X- and Y-distortion provides a convenient calendar interface

13/03/14 pag. 29 Visual  designer’s  sketch  of  the  applica+on  of  the  flip-­‐zoom  technique  to  the  presenta+on  of   photographs  on  a  Nokia  mobile  phone   Source:  Courtesy  Ron  Bird  

13/03/14 pag. 30 Source:  Courtesy  David  Baar,  IDELIX  SoFware  Inc.   Distorted map on a PDA, showing the continuity of transportation links

13/03/14 pag. 31 Source:  Courtesy  IDELIX  and  Mitsubishi   Distorted map on a table

13/03/14 pag. 32 Equal X- and Y-distortion centred around a manually chosen location in the Macintosh OSX ‘dock’

13/03/14 pag. 33 The Perspective Wall applies a 3D effect to the bifocal display

13/03/14 pag. 34 Advantages Perspective Wall •  User can adjust ratio of detail to context •  Smooth animation helps user perceive object constancy •  Relationship between detail and context is consistent: objects bend around the corner Slide  source:  Ken  Brodlie  

13/03/14 pag. 35 Perspective Wall Perspective gives smoother transition from focus to context Informa+on   space   Display   Space   Perspective Wall context focus Slide  source:  Ken  Brodlie  

13/03/14 pag. 36 overview Space  limita+ons     •  Scrolling   •  Overview  +  detail   •  Distor+on   •  Suppression   •  Zoom  and  pan           Time  limita+ons     •  Rapid  serial  visual   presenta+on   •  Eye-­‐gaze                

13/03/14 pag. 37 Suppression •  Applies a distance function and relevance function •  Less relevant other items are dropped from the display •  Classic example: New Yorker’s idea of the world

13/03/14 pag. 38 Suppression •  Originally proposed by Furnas (1986), but many variations of applications. •  Basic idea: more relevant information presented in great detail; the less relevant information presented as an abstraction. •  Relevance is computed on basis of the importance of information elements and their distance to the focus.

13/03/14 pag. 39 Degree of interest (DOI) function: DOI(a|.=b)  =  API(a)  –  D(A,b)   •  DOI(a|.=b):  DOI  of  a,  given  the  current  focus  is  b.   •  API(a):  sta+c  global  a  priori  importance  measure.   •  D(a,b):  distance  between  a  and  b.  

13/03/14 pag. 40 G P President S M N F K The organization tree of a company

13/03/14 pag. 41 1 2 3 3 4 4 22 1 1 1 22 P Focus Showing the ‘distance’ of each node from the focus of attention

13/03/14 pag. 42 Focus Context P S M NK The context defined by setting an upper threshold of unity for distance from a focus

13/03/14 pag. 43 Example of a display that might be associated with the focus and context

13/03/14 pag. 44 Each  node  in  the  organiza+on  tree  has  been  assigned  an  a  priori  importance  (API)       10 9 9 8 7 7 7 8 8 6 8 8 6 9 API

13/03/14 pag. 45 Degree of Interest (DoI) DoI = API – D Expressed as a function of two quantities: •  A priori importance (API) •  Distance (D) between an item and the item currently in focus

13/03/14 pag. 46 Segng  a  lower  limit  of  6  for  DoI  iden+fies  the  nodes  within  the  shaded  region   8 6 6 8 6 6 6 4 4 4 6 6 4 8 Focus Context Nodal values of degree of interest (=API – D)

13/03/14 pag. 47 Part  of  an   engineering  drawing   Applications of DoI concept

13/03/14 pag. 48 The  engineering  drawing   simplified  in  the  context   of  a  suspected  fault   Applications of DoI concept

13/03/14 pag. 49 Illustra+ng  the  concept  of  a  magic  lens.  (a)  shows  a  conven+onal  map  of  an  area,  (b)  shows  the   loca+on  of  services  (gas,  water  and  electricity  pipes)  in  the  same  area,  and  (c)  a  (movable)  magic   lens  shows  services  in  an  area  of  interest,  in  context   Application in magic lens technique

13/03/14 pag. 50 hDp://    

13/03/14 pag. 51 A  molecular  surface  of  the  protein  transferase  coloured  by  electrosta+c  poten+al  bound  to   DNA  shown  as  a  schema+c.  (ID  =  10mh).  The  magic  lens  window  allows  a  view  of  the   atomic  structure  bonding  to  be  shown,  with  the  bound  ligand  structure  highlighted  as   cylinders,  thereby  providing  a  view  inside  the  protein   Source:  By  kind  permission  of  Tom  Oldfield  and  Michael  Hartshorn   Magic lens

13/03/14 pag. 52 A 3D Flexible and Tangible Magic Lens in Augmented Reality  

13/03/14 pag. 53     A  combina+on  of  rubber-­‐sheet  distor+on  and  suppression  lead  to  a  map  appropriate  to  a   journey  from  one  city  to  another   Combined distortion and suppression

13/03/14 pag. 54 The rubber-sheet distortion technique employed in the map

13/03/14 pag. 55 Historical note •  Distortion and suppression appeared in early 1980s •  Need to maintain a balanced view of focus + context identified earlier – for example by Farrand (1973) “an effective transformation must somehow maintain global awareness while providing detail” “… there is a need for presenting a display with 1. sufficient detail for interaction, while 2. maintaining global vision of the entire scene.”

13/03/14 pag. 56 Fisheye view •  Farrand also coined the term “fisheye” •  Nowadays appears to refer to both distortion and suppression

13/03/14 pag. 57 Fisheye Menus •  Here is the same idea applied to menus –  Ben  Bederson,  University  of  Maryland   •  See also: –  hDp://­‐demo.shtml   ENV  2006  

13/03/14 pag. 58 Fisheye View, Polyfocal Display Can  distort  boundaries  because  applied  radially  rather  than  x  y   1D  Fisheye   2D  Polyfocal   Slide  source:  Hornung  and  Zagreus    

13/03/14 pag. 59 hDp:// cmsc838s/+chi/fisheye.html    

13/03/14 pag. 60 hDp://  


13/03/14 pag. 62 Source:  By  kind  permission  of  Patrick  Baudisch   The use of representation (by a ‘halo’) to provide context for a small display

13/03/14 pag. 63 overview Space  limita+ons     •  Scrolling   •  Overview  +  detail   •  Distor+on   •  Suppression   •  Zoom  and  pan           Time  limita+ons     •  Rapid  serial  visual   presenta+on   •  Eye-­‐gaze                

13/03/14 pag. 64 Panning  is  the  smooth  movement  of  a  viewing  frame  over  a  2D  image     Zoom and pan

13/03/14 pag. 65   Zooming  is  the  increasing  magnifica+on  of  a  decreasing  frac+on  of  an  image  (or  vice  versa)   Zoom and pan

13/03/14 pag. 66 Zooming •  Conventional zooming-in –  No  change  in  data  or  representa+on  –  only  filtering   –  Loss  of  context     •  ≠distortion whose purpose is to permit focusing rather than filtering •  Supports two cognitive tasks (Cairns and Craft 2005) –  Zooming-­‐in:  extraneous  informa+on  is  removed  from  visual  field  –  more   manageable  view   –  Zooming-­‐out:  reveals  hidden  informa+on  

13/03/14 pag. 67 A space-scale diagram relevant to combined zooming and panning Furnas  and  Bederson  (1995)  

13/03/14 pag. 68 Google earth

13/03/14 pag. 69 Exploring Information Spaces by Using Tangible Magic Lenses hDp://­‐mF4_OAhU0    

13/03/14 pag. 70 Semantic zoom •  Previous example: geometric zoom –  Con+nuous   –  Zooming-­‐in:  filtering  and  loss  of  context   •  Semantic zoom –  Discrete  transi+on   –  Addi+onal  detail  

13/03/14 pag. 71 A combination of geometric and semantic zoom

13/03/14 pag. 72 overview Space  limita+ons     •  Scrolling   •  Overview  +  detail   •  Distor+on   •  Suppression   •  Zoom  and  pan           Time  limita+ons     •  Rapid  serial  visual   presenta+on   •  Eye-­‐gaze                

13/03/14 pag. 73 A  collec+on  of  images  is  presented,  one  at  a  +me,  at  a  rapid  rate  (e.g.,  ten  per  second)     time Rapid serial visual presentation

13/03/14 pag. 74 Tile mode: concurrent presentation of images opposed to ‘slide show mode’

13/03/14 pag. 75 ‘Floa+ng  RSVP’  in  which   images  appear  to  approach   the  viewer  from  a  distance.   Sensi+ve  arrows  allow  the   speed  and  direc+on  of   ‘movement’  to  be  controlled   by  a  user   Source:  Courtesy  Kent  WiNenburg   Floating RSVP

13/03/14 pag. 76 The  contents  of  an  online  bookstore  are  presented  in  ‘collage  mode’  RSVP,  simula+ng  the   placing  of  book  covers  on  a  table  in  sequence.  The  set  of  arrows  just  under  the  presenta+on   allows  control  of  the  speed  and  direc+on  of  presenta+on   Source:  Courtesy  Kent  WiNenburg   Collage mode RSVP

13/03/14 pag. 77 An  interface  facilita+ng  the  browsing  of  posters  adver+sing  videos.    Cursor  movement  along  the   stacks  causes  posters  to  briefly  ‘pop  out’  sideways,  and  the  whole  bifocal  structure  can  be   scrolled  to  bring  a  video  of  interest  to  the  central  region,  where  a  mouse  click  will  cause  a  clip   from  a  video  to  be  played  (Lam  and  Pence  1997)   RSVP + bifocal principle

13/03/14 pag. 78 Space-time trade-off

13/03/14 pag. 79 Space-time trade-off

13/03/14 pag. 80   An  experiment  to  test  a  subject’s  ability  to  recognise  the  presence  or  absence  of  a  previously   viewed  target  image  within  a  collec+on  presented  sequen+ally  at  a  rate  of  around  ten  per  sec.     Prior instruction to subject Subjectsʼ performance “Here is a target image. Tell me if this image appears in the sequence of N images youʼre about to see” Recognition about 80% to 90% successful time about 100 ms unrelated images Presentation of images Briefly glimpsed images

13/03/14 pag. 81 Representa+on  of  limits  on  display  area  and  total  presenta+on  +me  by  a  ‘resource  box’     Display area Presentation time Space and time resources

13/03/14 pag. 82 Source:  Courtesy  of  Katy  Cooper   Three ‘static’ image presentation modes (A, B, C) and three ‘moving’ image presentation modes (D, E, F)

13/03/14 pag. 83 Slide show

13/03/14 pag. 84 Mixed

13/03/14 pag. 85 Tile

13/03/14 pag. 86 Diagonal

13/03/14 pag. 87 Ring

13/03/14 pag. 88 Stream

13/03/14 pag. 89 Source:  Courtesy  of  Katy  Cooper   Favorite mode?

13/03/14 pag. 90 The  accuracy  with  which  the  presence  or  absence  of  a  target  image  was  reported  for  the   six  presenta+on  modes,  averaged  over  all  tasks  and  presenta+on  +mes.         1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 Slide-show Mixed Tile Diagonal Ring Stream Recognition accuracy Presentation modes

13/03/14 pag. 91 The  (sta+c)  slide-­‐show,  mixed  and  +le  image  presenta+on  modes  account  for  three-­‐quarters  of   the  preferred  modes  (Cooper  et  al.  2006)  

13/03/14 pag. 92 Almost  all  the  least  preferred  image  presenta+on  modes  were  moving  modes  and  the  stream   mode  accounted  for  over  half    

13/03/14 pag. 93   A  simple  representa+on  of  eye-­‐gaze  behaviour.  The  rapid  saccades  are  shown  green,  the   fixa+ons  (F)  of  varying  dura+on  by  circles  of  propor+onate  size   F F F F F F F F Eye-gaze

13/03/14 pag. 94 Eye-gaze trajectory slide show

13/03/14 pag. 95 Eye-gaze trajectory tile mode

13/03/14 pag. 96 Eye-gaze trajectories mixed mode

13/03/14 pag. 97 Eye-gaze trajectories diagonal mode for subject who disliked the mode

13/03/14 pag. 98 Eye-gaze trajectories diagonal mode for subject who liked the mode

13/03/14 pag. 99 Eye-gaze trajectory stream for subject who disliked the mode

13/03/14 pag. 100 The  acquisi+on  of  an  expanding  target.  (a)  The  dormant  appearance  of  the  image  collec+on,   and  (b)  its  appearance  when  the  cursor  rests  over  image  6     1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 10 11 12 13 14 15 16 17 18 19 209861 2 3 4 (a) (b) Manual control: ‘expanding target’ presentation mode

13/03/14 pag. 101 An  experiment  in  which  a  subject  first  views  the  rapid  (e.g.,  10  per  second)  presenta+on  of  a   collec+on  of  images,  is  then  shown  a  single  image  and  asked  to  say  whether  that  image  was   part  of  the  collec+on.  Iden+fica+on  success  is  highly  dependent  upon  the  +me  elapsing   between  the  end  of  the  presenta+on  and  the  ques+oning  of  the  subject   Prior instruction to subject Presentation of image collection Subject’s performance about 100ms unrelated images time None The subject was shown an image and then asked, ‘Was this image present in the sequence you have just seen?’ Recognition success was 10% to 20% unless the question was aksed within about 4 seconds of the end of the presentation Models of human visual performance

13/03/14 pag. 102 An  experiment  in  which  a  collec+on  of  images  is  presented  to  a  subject.  Each  image  is  presented   briefly  (e.g.,  for  100ms)  and  followed  by  a  ‘visual  mask’  las+ng  about  300ms.  Subjects  were  able   to  say,  with  a  considerable  degree  of  success,  whether  an  image  shown  arerwards  had  been   part  of  the  presenta+on   Prior  instruc+on     to  subject   Presenta+on  of  image  collec+on   Subject’s  performance   about  300ms   unrelated  images   +me   None   The  subject  was  shown  an  image  and  then     asked,  ‘Was  this  image  present  in  the     sequence  you  have  just  seen?’   Up  to  92%  recogni+on  success   etc  .  .  .  .  Visual   mask    .     Visual   mask       Visual   mask   about  100ms   Models of human visual performance

13/03/14 pag. 103 A  third  palleDe  for  the  interac+on  designer,  addressing  issues  of  presenta+on   Presentation   concepts and   techniques   Scrolling   Overview+detail   Distortion   Suppression   Zoom   Pan   RSVP   Eye gaze   Recap

13/03/14 pag. 104 Visual Information Seeking: Mantra Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Overview, zoom & filter, details-on-demand Ben  Shneiderman,  1996  

13/03/14 pag. 105 Shneiderman’s “7 Tasks” •  Overview task –  overview of entire collection •  Zoom task –  zoom in on items of interest •  Filter task –  filter out uninteresting items •  Details-on-demand task –  select an item or group to get details •  Relate  task   –  relate  items  or  groups  within  the   collec+on   •  History  task     –  keep  a  history  of  ac+ons  to  support   undo,  replay,  and  progressive   refinement   •  Extract  task   –  allow  extrac+on  of  sub-­‐collec+ons  and   of  the  query  parameters  

13/03/14 pag. 106 Questions?

13/03/14 pag. 107 Readings •  Chapter 4

13/03/14 pag. 108 References •  Furnas, G. W., & Bederson, B. B. (1995, May). Space-scale diagrams: Understanding multiscale interfaces. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 234-241). ACM Press/Addison- Wesley Publishing Co.. •  Shneiderman, B. (1996, September). The eyes have it: A task by data type taxonomy for information visualizations. In Visual Languages, 1996. Proceedings., IEEE Symposium on (pp. 336-343). IEEE. •  Some relevant notes: presentation.html

13/03/14 pag. 109 Research presentations

13/03/14 pag. 110 Research presentations •  Schedule on PointCarré •  Select a second paper in the same slot for questions: e.g. session 1: •  Links to doodle polls for all six sessions will be included in the schedule.

13/03/14 pag. 111 Team project

13/03/14 pag. 112 Team project milestones 1.  Form teams 2.  Project proposal 3.  Intermediate presentation 4.  Final presentation 5.  Short report due  27  Feb.   due  13  March   due  3  April   22  May   due  29  May  

13/03/14 pag. 113 Project proposal 1 page description of your intended project: –  mo+va+on   –  which  datasets  you  will  use   –  current  status.  If  available,  first  designs.   –  problems/ques+ons   due 13 March If you want earlier feedback, send us your proposal earlier ;-)

13/03/14 pag. 114 Data collection • 1gHwVWHZLzWdSz1F37jA1Gungrl56bT215M6FYW3YqGY/ viewform Or • Anonymous! Choose your own ID. •  Please report your data ;-)

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Info 247. Information Visualization and Presentation | UC ...

Information visualization is widely used in media, business, and engineering disciplines to help people analyze and understand the information at hand.
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PPT - Data & Information Visualization PowerPoint Presentation

Data - PowerPoint Slideshow by fay ... Data & Information Visualization. Lecture 1: Data, Information, Knowledge and Their Presentations.
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PPT – Data Visualization PowerPoint presentation | free ...

Title: Data Visualization 1 Data Visualization. Lecture 13 ; Information Visualization ; Part 1; 2 What is Visualization? Generally ; The use of computer ...
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Visualization in presentations - Presentation Process ...

Why use visualization in presentations? To answer that, I want you to look at the following two slides. Both of them present the same information.
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PPT – Information Visualization PowerPoint presentation ...

The presentation will start after a short (15 second) video ad from one of our sponsors. Hot tip: Video ads won’t appear to registered users who are ...
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i247: Information Visualization and Presentation

Welcome. Welcome to the course website for i247, Information Visualization and Presentation. Instructor . Cecilia Aragon 5 South Hall, 510-486-4106
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