Course Home Page Course Design Course Structure main source reading-intensive course lectures/readings readings, lecture slides, all information reading front-loaded in first 9 weeks weeks 1-9 (no classes week 8) (less than in past: using new textbook draft) I lecture Lecture 1: Introduction reload frequently, updates common! oral presentations 2-3 core readings required, further readings optional permanent URL Information Visualization submit questions for each lecture (19%) major presentation http://www.cs.ubc.ca/ ∼ tmm/courses/533-11 CPSC 533C, Fall 2011 discussion (3%) project update, project final presentations (25%) writing weeks 10-13 Tamara Munzner questions, proposal, final report student presentations programming only presenter does topic readings UBC Computer Science project course (unless do analysis option) discussion (3%) time management critical: staged development project (50%) Wed, 7 September 2011 no problem sets or exams weeks 6-14 schedule meetings, proposal, update, final no classes week of VisWeek (Oct 24, 26) http://www.cs.ubc.ca/ ∼ tmm/courses/533-11/structure.html 1 / 62 2 / 62 3 / 62 4 / 62 Course Mark Breakdown Required Readings Prerequisites Participation class participation: 25% Munzner 6%: discussions in class no courses required questions 75%, discussion 25% Information Visualization: Principles, Methods, and both lectures and student presentations HCI very useful presentation: 25% Practice 19%: questions for each required reading computer graphics useful pre-publication draft details later two for longer draft book chapters no graphics background: constraint on project choices chapters posted one week before reading is due project: 50% one for shorter papers grads from other departments welcome many papers due at 11am Mon/Wed for day’s reading proposal 10% if no programming background: do analysis/survey color PDF downloads from page attendance expected interim update presentation 10% project some are DL links; use library EZproxy final presentation 10% tell me in advance if you know you’ll miss class final written report 20% no required textbook to buy question credit still possible if submitted in advance project content 50% optional reading: Ware, Tufte tell me when you recover if you were ill 5 / 62 6 / 62 7 / 62 8 / 62 Questions Question Examples: Poor Question Examples: OK Question Examples: Good questions or comments Well, what exactly Pad++ is? Is it a progarmming library This seems like something fun to play around with, are It would be interesting to compare the approach in this or a set of API or a programming language? how can we there any real implementations of this? Has a good paper to some other less-mathematically-thought-out fine to be less formal than written report use it in our systems, for xample may be programming in application for this type of zooming been found? Is there zoom and pan solutions to see if it is really better. correct grammar and spelling expected nevertheless TCL or OpenGL may be ? still a real need for this now that scroll wheels have Sometimes ”faking it” is perceived to be just as good (or be concise: a few sentences good, one paragraph max! become prevailent and most people don’t even use the better) by users. should be thoughtful, show you’ve read and reflected I learned some from this paper and got some ideas of my scroll bar anymore? project. The space-scale diagrams provided a clear intuition of poor to ask something trivial to look up ok to ask for clarification of genuinely confusing section Playing with the applet, I find I like half of their why zooming out, panning then zooming in is a superior approach. It’s nice to zoom out as my scroll speed navigation technique. However, I found the diagram too book vs paper comments increases, but then I don’t like the automatic zoom in cumbersome for practical use, especially for objects with best: substantive comments on material when I stop scrolling. Searching the overview I found the zoom-dependent representations (Figure 11). also useful: order of explanation, undefined words you didn’t know location I wanted, but while I paused and looked at the not enough: typos/grammar (but fine to mention) overview, I fell back in to the closeup. I think they need grading into buckets: to significantly dampen their curve. great 100%, good 89%, ok 78%, poor 67%, zero 0% 9 / 62 10 / 62 11 / 62 12 / 62 Question Examples: Great Presentations Presentation Topics Projects second half of class choice 1: programming I’m curious as to what would have happened if the authors http://www.cs.ubc.ca/ ∼ tmm/courses/533- had simply preselected the values of the free parameters for sign up by Oct 21 11/presentations.html common case the participants in their user study, and then had the users material (exact numbers TBD, depending on enrollment) I will only consider supervising students who do compare their technique to the standard magnification tools 1 paper from my suggested list programming projects present in a ’normal’ application (much like the space-scale 2 papers your choice choice 2: analysis folks did). Could it be that the users are ‘manufacturing’ a talk use existing tools on dataset large standard deviation in the free parameter specifications slides required detailed domain survey by settling for values that merely produce a local summary important, but also have your own thoughts particularly suitable for non-CS students improvement in their ability to manipulate the interface, critical points of papers comparison and critique choice 3: survey instead of actively searching for an optimal valuation scheme? grading In a related vein, the speed-dependent automatic zooming very detailed domain survey per-paper: summary 70%, critique 30% met with mixed success on some applications. Isn’t this particularly suitable for non-CS students synthesis: critique/synthesis 100% success related to how ”compressible” some information is? general: presentation style 50%, content prep 50% i.e. because zooming must necessarily throw out some information, it isn’t obvious which information to keep around balance between 3 pieces depends on num papers to preserve the navigable structure. assigned 13 / 62 14 / 62 15 / 62 16 / 62
Projects: More Course Goals and Feedback Office Hours Reserve Books stages twofold goal 5-6 Wed after class, or by appointment Information Visualization: Perception for Design, Colin meetings with me for approval by Oct 11-21 (at latest) specific: teach you some infovis office in X661, ICICS/CS X-Wing Ware (2nd ed) proposal due Fri Oct 28 generic: teach you how to be a better researcher Envisioning Information, Edward R. Tufte, Graphics Press update presentations Nov 14/16/21 detailed written comments on writing and presenting 1990 final presentations Mon Dec 12 2-5 both content and style The Visual Display of Quantitative Information, Edward final report Wed Dec 14 noon at level of paper review for your final project R. Tufte, Graphics Press 1983 resources goal: within a week or so Visual Explanations, Edward R. Tufte, Graphics Press before updates, for early presentations software 1997 data fast grading for reading questions project ideas Readings in Information Visualization: Using Vision To great 100%, good 89%, ok 78%, poor 67%, zero 0% goal: turn around by next class Think; Card, Mackinlay, and Shneiderman, eds; Morgan http://www.cs.ubc.ca/ ∼ tmm/courses/533-11/resources.html Kaufmann 1999. one week at most The Visualization Toolkit, 3rd edition; Schroeder, Martin and Lorensen; Kitware Inc. 2004 17 / 62 18 / 62 19 / 62 20 / 62 Information Visualization Interactivity Information Visualization Information Visualization visual representation of abstract data static images visual representation of abstract data visual representation of abstract data computer-generated, often interactive 10,000 years computer-generated, often interactive computer-generated, can be interactive art, graphic design help human perform some task more effectively help human perform some task more effectively moving images bridging many fields 150 years graphics: drawing in realtime cinematography cognitive psych: finding appropriate representation HCI: using task to guide design and evaluation interactive graphics 30 years computer graphics, human-computer interaction 21 / 62 22 / 62 23 / 62 24 / 62 Information Visualization External Representation: multiplication External Representation: multiplication External Representation: multiplication visual representation of abstract data paper mental buffer paper mental buffer paper mental buffer computer-generated, can be interactive 5 help human perform some task more effectively 57 57 57 bridging many fields x 48 x 48 [ 7*8=56] x 48 [ 7*8=56] graphics: drawing in realtime —- —- —- cognitive psych: finding appropriate representation HCI: using task to guide design and evaluation 6 external representation reduces load on working memory offload cognition familiar example: multidigit multiplication 25 / 62 26 / 62 27 / 62 28 / 62 External Representation: multiplication External Representation: multiplication External Representation: multiplication External Representation: multiplication paper mental buffer paper mental buffer paper mental buffer paper mental buffer 5 5 57 57 57 57 x 48 x 48 [5*8=40 + 5 = 45] x 48 x 48 [7*4=28] —- —- —- —- 6 456 456 456 29 / 62 30 / 62 31 / 62 32 / 62
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