Toward Visualization for Games
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Toward Visualization for Games

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Slides from T.J. Jankun-Kelly's IEEE VisWeek 2012 presentation on visualization for games. Electronic games are starting to incorporate in-game telemetry that collects data about player, team, and ...

Slides from T.J. Jankun-Kelly's IEEE VisWeek 2012 presentation on visualization for games. Electronic games are starting to incorporate in-game telemetry that collects data about player, team, and community
performance on a massive scale, and as data begins to accumulate, so does the demand for effectively analyzing this data. We use examples from both old and new games of different genres to explore the theory and design space of visualization for games. Drawing on these examples, we define a design space for this novel research topic and use it to formulate design patterns for how to best apply visualization technology to games. We then discuss the implications that this new framework will
potentially have on the design and development of game and visualization technology in the future.

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  • \n
  • I lead a double life. I’m a visualization scientist, with all that entails.\n
  • But I’m also a gamer. I teach video games. I play video games. Maybe more than I should.\n
  • So get on Farmtown on Facebook and talk to my neighors Brian & Niklas, who are really into games themselves. They bring up the idea that we might want to do a paper on where our two interests combine\n
  • Can this be serious? Talk about huge data problem/source. Roughly 19 million registered players in BLOPs, 10s of thousands of active players still. Information about movements, kills, deaths, etc.\n
  • Angry Birds: Over 200k years have been played. Lots of potential user data to be visualized: Different choices of paths, bird types, etc.\n
  • Mass Effect 3 had 40,000 lines of recorded dialog to be able to handle all the permutations of 1000+ variables that affect the state of the game from its previous installments. BioWare had to write its own dialog/variable visualization system to keep track of all the permutations during writing and development. Developers use visualization too.\n
  • Every game is a massive set of data that needs to be visualized. Can we do it?\n
  • Some vis already in games. Give a few examples of simple to complex: Healthbars in WoW, Charts of win/loss in multiplayer games, to cloropleth maps all the way back in 1989. Paper goes through many more examples in different gaming genres; please see it for more info\n
  • Some vis already in games. Give a few examples of simple to complex: Healthbars in WoW, Charts of win/loss in multiplayer games, to cloropleth maps all the way back in 1989. Paper goes through many more examples in different gaming genres; please see it for more info\n
  • Some vis already in games. Give a few examples of simple to complex: Healthbars in WoW, Charts of win/loss in multiplayer games, to cloropleth maps all the way back in 1989. Paper goes through many more examples in different gaming genres; please see it for more info\n
  • Some vis already in games. Give a few examples of simple to complex: Healthbars in WoW, Charts of win/loss in multiplayer games, to cloropleth maps all the way back in 1989. Paper goes through many more examples in different gaming genres; please see it for more info\n
  • Some vis already in games. Give a few examples of simple to complex: Healthbars in WoW, Charts of win/loss in multiplayer games, to cloropleth maps all the way back in 1989. Paper goes through many more examples in different gaming genres; please see it for more info\n
  • Some vis already in games. Give a few examples of simple to complex: Healthbars in WoW, Charts of win/loss in multiplayer games, to cloropleth maps all the way back in 1989. Paper goes through many more examples in different gaming genres; please see it for more info\n
  • What this talk is vs what this talk is not: A framework for vis in games and design patterns of common usage; gamification, no. (See other talks at VisWeek)\n
  • What this talk is vs what this talk is not: A framework for vis in games and design patterns of common usage; gamification, no. (See other talks at VisWeek)\n
  • What this talk is vs what this talk is not: A framework for vis in games and design patterns of common usage; gamification, no. (See other talks at VisWeek)\n
  • Our framework takes the 30+ examples we cite in the paper and our knowledge of others and distills them into five separate orthogonal design dimensions. I overview them next.\n
  • 5 Part categorization: Primary Purpose/Target Audience/Temporal Usage/Visual Complexity/Immersion or Integration. Primary Purpose: Why is it done? Communicate status or debugging info for example. Target audience: The player, an observer, or the developer during testing. Visual complexity is how advanced the vis is: Bars vis chloropleth maps. Immersion/Integration measures is the vis in the game or out of it (informative or immersive/integrated or separate); it is in the game space or interrupts it. We look at temporal usage in depth.\n
  • What is the visualization for? Status, Training (retrospective theater, optimal lines), Progression, Communication, Debugging/Developing\n
  • Who is it for? Player, developer, observer. \n
  • Continuous: Always on, always updating. Health bars is a common example. In the SimCity games, various statistics such as approval rating of your “mayor” and the demand for different types of zoning is updated in real time, providing continuous information.\n
  • Intermittent: Shown on demand or when the game requires it. Health bars in more recent games only show occasionally if at all. Tech trees from games like Civ which show choices in development in a complex graph structure also apply.\n
  • Retrospective includes summaries or similar (Boneyard). Replay theaters, common in multiplayer games, fall here: They replay games, with possible summarization or different data to assist. Racing games providing “best-line” indicators or “phantom cars” of best paths fall here. In this example from the fast forward, we look at player kill and player death locations in a multiplayer map via a heatmap. We can take use a difference image as a retrospective analysis of where it is “saftest” for a player—whiter areas are more likely to result in the player defeating their opponent than the other way around.\n
  • Retrospective includes summaries or similar (Boneyard). Replay theaters, common in multiplayer games, fall here: They replay games, with possible summarization or different data to assist. Racing games providing “best-line” indicators or “phantom cars” of best paths fall here. In this example from the fast forward, we look at player kill and player death locations in a multiplayer map via a heatmap. We can take use a difference image as a retrospective analysis of where it is “saftest” for a player—whiter areas are more likely to result in the player defeating their opponent than the other way around.\n
  • Retrospective includes summaries or similar (Boneyard). Replay theaters, common in multiplayer games, fall here: They replay games, with possible summarization or different data to assist. Racing games providing “best-line” indicators or “phantom cars” of best paths fall here. In this example from the fast forward, we look at player kill and player death locations in a multiplayer map via a heatmap. We can take use a difference image as a retrospective analysis of where it is “saftest” for a player—whiter areas are more likely to result in the player defeating their opponent than the other way around.\n
  • Retrospective includes summaries or similar (Boneyard). Replay theaters, common in multiplayer games, fall here: They replay games, with possible summarization or different data to assist. Racing games providing “best-line” indicators or “phantom cars” of best paths fall here. In this example from the fast forward, we look at player kill and player death locations in a multiplayer map via a heatmap. We can take use a difference image as a retrospective analysis of where it is “saftest” for a player—whiter areas are more likely to result in the player defeating their opponent than the other way around.\n
  • Retrospective includes summaries or similar (Boneyard). Replay theaters, common in multiplayer games, fall here: They replay games, with possible summarization or different data to assist. Racing games providing “best-line” indicators or “phantom cars” of best paths fall here. In this example from the fast forward, we look at player kill and player death locations in a multiplayer map via a heatmap. We can take use a difference image as a retrospective analysis of where it is “saftest” for a player—whiter areas are more likely to result in the player defeating their opponent than the other way around.\n
  • Retrospective includes summaries or similar (Boneyard). Replay theaters, common in multiplayer games, fall here: They replay games, with possible summarization or different data to assist. Racing games providing “best-line” indicators or “phantom cars” of best paths fall here. In this example from the fast forward, we look at player kill and player death locations in a multiplayer map via a heatmap. We can take use a difference image as a retrospective analysis of where it is “saftest” for a player—whiter areas are more likely to result in the player defeating their opponent than the other way around.\n
  • Prospective: Predict what is going to happen, provide player info on decision consequences. Tech trees do this, as to glyphs indicating effect of game conversation. In strategy game, such as XCOM: EU, we can also visualize spatial cues as the extent of movement but also other indicators such as how much protection a movement will provide (indicated by the blue shields). \n
  • 5 Part categorization: Primary Purpose/Target Audience/Temporal Usage/Visual Complexity/Immersion or Integration\n
  • 5 Part categorization: Primary Purpose/Target Audience/Temporal Usage/Visual Complexity/Immersion or Integration\n
  • Design patterns: We give five in the paper, discussing common uses and how they fit into our framework. Here, I discuss a two examples\n
  • Heads-up displays (or HUDs) are ubiquitous in gaming: They are graphics which summarize a large portion of information about the game world state on top of the rendering of the game world itself. They are primarily for status, showing information that is updated constantly. The visualizations tend to be basic (bars, lines, some glyphs maybe). The depiction is always part of the game, and often shown in a manner consistent with other artifacts in the game world if immersive; otherwise, it is informative.\n
  • Basic HUD in id’s DOOM. \n
  • HUD in Angry Birds even. I could spend the entire talk showing HUD examples\n
  • This HUD not only shows information about a time trial run (a race against time) in the game Mirrors Edge, it also demonstrates a ludophasmas: A “ghost” version of the player in a previous run as a comparison. Driver’s lines drawn onto the world in racing games are another type of HUD element that can be used in a similar vein. \n
  • Data in time are representations of game data (integrated with the game or otherwise) that are primarily for training or communicating aspects of the game to players or observers. Often, as we are summarizing time, these use more intermediate graphical representations such as bar charts or other graphics such as this event time-line of when different features were built during a session of the Starcraft game. Civ 3 uses a retrospective stacked area chart to show the amount of influence over time (a spatialized view also shows data in space, another one of our categories)\n
  • Data in time are representations of game data (integrated with the game or otherwise) that are primarily for training or communicating aspects of the game to players or observers. Often, as we are summarizing time, these use more intermediate graphical representations such as bar charts or other graphics such as this event time-line of when different features were built during a session of the Starcraft game. Civ 3 uses a retrospective stacked area chart to show the amount of influence over time (a spatialized view also shows data in space, another one of our categories)\n
  • Data in time are representations of game data (integrated with the game or otherwise) that are primarily for training or communicating aspects of the game to players or observers. Often, as we are summarizing time, these use more intermediate graphical representations such as bar charts or other graphics such as this event time-line of when different features were built during a session of the Starcraft game. Civ 3 uses a retrospective stacked area chart to show the amount of influence over time (a spatialized view also shows data in space, another one of our categories)\n
  • Some final implications of our work\n
  • In this work, we have outlined a 5 part categorical decomposition of the space of visualization in games. In addition, we provided several examples showing common design patterns of vis in games and how our framework describes them. We feel this work has two major set of implications: One for games, and one for vis. For players, visualization is used to better understand game state, make better decisions, or communicate their success/failure to others. For observers, visualizations could better inform and entertain them. Finally, for developers, visualization can help detect bugs, find game balance issues, or be inspired by player activity. \n
  • In this work, we have outlined a 5 part categorical decomposition of the space of visualization in games. In addition, we provided several examples showing common design patterns of vis in games and how our framework describes them. We feel this work has two major set of implications: One for games, and one for vis. For players, visualization is used to better understand game state, make better decisions, or communicate their success/failure to others. For observers, visualizations could better inform and entertain them. Finally, for developers, visualization can help detect bugs, find game balance issues, or be inspired by player activity. \n
  • In this work, we have outlined a 5 part categorical decomposition of the space of visualization in games. In addition, we provided several examples showing common design patterns of vis in games and how our framework describes them. We feel this work has two major set of implications: One for games, and one for vis. For players, visualization is used to better understand game state, make better decisions, or communicate their success/failure to others. For observers, visualizations could better inform and entertain them. Finally, for developers, visualization can help detect bugs, find game balance issues, or be inspired by player activity. \n
  • For Vis, there are several potential application or research benefits. First, with over 60 mil game consoles in the US alone, that is a huge potential audience for informative (if not complex) visualization either as part of a game, outside of the game, or for developers (potential for large impact). In addition, gamers have been shown to have a high degree of visual literacy and spatial reasoning, and thus are an untapped population to demonstrate advanced methods. Finally, as implicated, there is a sea of data that has interesting problems to address that may require novel methods to develop, a key task in any research endeavor. \n
  • For Vis, there are several potential application or research benefits. First, with over 60 mil game consoles in the US alone, that is a huge potential audience for informative (if not complex) visualization either as part of a game, outside of the game, or for developers (potential for large impact). In addition, gamers have been shown to have a high degree of visual literacy and spatial reasoning, and thus are an untapped population to demonstrate advanced methods. Finally, as implicated, there is a sea of data that has interesting problems to address that may require novel methods to develop, a key task in any research endeavor. \n
  • For Vis, there are several potential application or research benefits. First, with over 60 mil game consoles in the US alone, that is a huge potential audience for informative (if not complex) visualization either as part of a game, outside of the game, or for developers (potential for large impact). In addition, gamers have been shown to have a high degree of visual literacy and spatial reasoning, and thus are an untapped population to demonstrate advanced methods. Finally, as implicated, there is a sea of data that has interesting problems to address that may require novel methods to develop, a key task in any research endeavor. \n
  • \n
  • \n

Toward Visualization for Games Toward Visualization for Games Presentation Transcript

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AND COMPUTER GRAPHICS, VOL. XX, NO. Y, MONTH 2012 14 on, “Tracking real-time user experience (TRUE): [71] Bullfrog, Populous. Electronic Arts, 1989. ive instrumentation solution for complex sys- [72] ——, Populous II: Trials of the Olympian Gods. EA, 1991. eedings of the ACM Conference on Human Factors [73] id Software, Wolfenstein 3D. Apogee Software, 1992. otball games,” http://www. Systems, 2008, pp. 443–452. [60] ——, Mass Effect 2. ——, Doom. Arts, 2010. [74] Electronic id Software, 1993. Toward Visualization for ools, “Telemetry profiling system,” Maxis,http: [75] Westwood Studios, Dune II: Battle for Arrakis. Virgin, 1992. viz/, 2008. [61] 2010, Spore. Electronic Arts, 2008. metools.com/telemetry.htm. [62] Splash Damage, Wolfenstein: Enemy Territory. Humans. Blizzard, 1994.wards gameplay analysis via [76] Blizzard, Warcraft: Orcs & Activision, 2003. logging: Data collection on the high seas,” Games, Dead Space 2. Electronic Arts, 2011. of the International MindTrek [63] Visceral in [77] ——, StarCraft. Blizzard, 1998. the Game Developers Conference, 2007. Blizzard, World of Warcraft. Blizzard, 2004.of Liberty. Blizzard, 2010. [64] [78] ——, StarCraft II: Wings , S. Shodhan, and M. Twardos, [65] Valve Corporation, S2 Games, Heroes of Newerth. 2003. Games, 2010. ot.com/. “Spore API: ac- [79] Steam. Valve Corporation, S2 ue database of player creativity,” in SIGGRAPH Halo: Reach. Microsoft of Camelot. Mythic Entertainment, 2001. ng,” http://nonoba.com/ [66] Bungie, Inc., [80] Mythic, Dark Age Game Studios, 2010. [67] EA Canada, FIFA 10. EA Sports, 2009. [81] ——, Warhammer Online: Age of Reckoning. EA Games, 2008. m/. data,” http://thevioletpiece.com/spore/. [82] CCP Games, War. Online. CCP Games, 2003. Spore [68] Treyarch, Call of Duty: World at EVE Activision, 2008. d M. Masuch, “Action summary forMicroProse, Civilization. MicroProse, 1991. 11. EA Sports, 2010.p://www.kontagent.com/. [69] computer [83] EA Tiburon, Madden NFL Games: B. Phillips, R.spectator modes and summaries,” [84] MicroProse, Formula One Grand Prix. MicroProse, 1992. ing action for J. Pagulayan, [70] Firaxis Games, Civilization III. Infogrames, 2001. methe International Conference on Application and [85] Criterion Games, Need for Speed: Hot Pursuit. EA Games, 2010. of user experience (TRUE): [71] Bullfrog, Populous. Electronic Arts, 1989. Computer for complex pp. 124–132. ——, Populous[86]Trials of the Olympian Gods. EA, 1991.1996. solution Games, 2003, sys- [72] II: id Software, Quake. GT Interactive,G. Humphreys, and M. Agrawala, “Visualizing Wolfenstein 3D. Dragon Age II. Electronic Arts, 2011. Conference on Human Factors [73] id Software, [87] Bioware, Apogee Software, 1992. [74] ——, Doom. [88] Blizzard North, Diablo II. Blizzard, 2001.43–452. in multi-user virtual environments,” in id Software, 1993.ehaviors the IEEE Conference on Visualization, 2004, pp. Studios,Infinity Ward, Call of Duty: Modern Warfare 2. Activision, 2009. ofiling system,” 2010, http: [75] Westwood [89] Dune II: Battle for Arrakis. Virgin, 1992. etry.htm. [76] Blizzard, Warcraft: Orcs & Battlefield: Bad Company 2. Electronic Arts, 2010. [90] DICE, Humans. Blizzard, 1994. ction on the highIeronutti, “VU-Flow: A StarCraft. Blizzard, 1998. Fit. Nintendo, 2007. . Ranon, and L. seas,” in [77] ——, visu- [91] Nintendo, Wii Theory, Design Space, and for analyzing navigation in virtual environ- Conference, 2007. [78] ——, StarCraft II: Wings of Liberty. Blizzard, 2010.M. Twardos, on Visualization and Computer Graph- Heroes of Newerth. S2 Games, 2010. Transactions “Spore API: ac- [79] S2 Games, er6, pp. 1475–1485, Nov./Dec. 2006. Mythic, Dark Age of Camelot. Mythic Entertainment, 2001. . creativity,” in SIGGRAPH [80] s and K. Iizuka, “Visualization[81]online-game of ——, Warhammer Online: Age of Reckoning. EA Games, 2008. on their action behaviors,”/thevioletpiece.com/spore/. International Journal EVE Online. CCP Games, 2003. [82] CCP Games, Brian Bowman is a senior undergraduate ion Technology, 2008. amessummary for computer [83] EA Tiburon, Madden NFL 11. EA Sports, 2010.Computer Engineering at Purdue student in s, M. Kurashige, and K.-T. Chen, “Detection of Formula One Grand Prix.University in West Lafayette, IN, USA. He willator modes and summaries,” [84] MicroProse, MicroProse, 1992. clustering of online-game players,” InternationalConference on Application and [85] Criterion Games, Need for Speed: Hot Pursuit. EA Games, 2010. in Spring 2012. be graduating from Purdueual Reality, vol. 6, no. 3, pp. 11–16, 2007.Software, Quake. GT Interactive, He is a member of IEEE-HKN. He probably003, pp. 124–132. [86] id 1996. A. Brown, and P. Drennan, “The[87] Bioware, Dragon Age II. Electronic Arts, 2011. M. Agrawala, “Visualizing gameplay visu- plays too many video games. Brian Bowman, Niklas Elmqvist, T.J. Jankun-Kelly er virtual environments,” in and visualization festo: a framework for logging [88] Blizzard North, Diablo II. Blizzard, 2001. eeplay data,” Computers in Entertainment, vol.Ward, Call of Duty: Modern Warfare 2. Activision, 2009. on Visualization, 2004, pp. [89] Infinity 5, [90] DICE, Battlefield: Bad Company 2. Electronic Arts, 2010. ayer dossiers: Analyzing gameplay data as a re-Wii Fit. Nintendo, 2007. ronutti, “VU-Flow: A visu- [91] Nintendo, igation in virtual environ- Research, vol. 11, tional Journal of Computer Game11.lization and Computer Graph-os, F. Kivran-Swaine, and M. Naaman, “Playable Nov./Dec. 2006. rizing the design space of game-y infographics,”Visualization of online-game aviors,” ACM Conference on Human Factors in of the International Journal Brian Bowman is Niklas Elmqvist is an assistant professor a senior undergraduate tems, 2011. 8. “Leaderboards “Detection of student in Computer Engineering at Purdue in the School of Electrical and Computer d K.-T. Chen, can suck it! five better ideas for University in West Lafayette, IN, USA. He willUniversity in West Engineering at Purdue me data,” in Proceedings of -game players,” Internationalthe Game Developers10.3, pp. 11–16, 2007. be graduating fromLafayette,inIN, USA. He was previously a Purdue Spring 2012.o. He is a member ofpostdoctoral He probablyat INRIA in Paris, IEEE-HKN. researcher M. Wattenberg, “Stacked graphs - geometry ennan, “The gameplay visu- IEEE Transactions on Visualization and Computer plays too many video games. France. He received his Ph.D. in 2006 or logging and visualization from Chalmers University of Technology in 14, no. Entertainment, vol. 5, ters in 6, pp. 1245–1252, 2008. amers mimic the season’s ups and downs,” The ¨ Goteborg, Sweden. He is a member of the s, Feb. 2011. IEEE and the Computer Society. In another zing gameplay data as a re- life, he is a wizard, assassin, or knight indputer Game Research,structure of the information J. Mackinlay, “The vol. 11,design space,” in Proceedings of the IEEE Sympo- whatever game currently takes his fancy.,ation M. Naaman, “Playable 92–99. and Visualization, 1997, pp.ologie graphique: Les diagrammes - Les r´seaux - Lesace of game-y infographics,” erance, on Human Factors in rence 1967. S. Ishakawa, and M. Silverstein, A Pattern Niklas Elmqvist is an assistant professorns, Buildings,better ideas for New York: Oxford T.J. Jankun-Kelly is an associate Professor in the School of Electrical and Computersuck it! five Construction. ss, 1977.dings of the Game Developers Engineering at Purdue University in West engineering within of computer science andm, http://www.machinima.com/. Lafayette, IN, USA. He was previously a College of En- the James Worth Bagley gineering, Mississippi State University, MS, postdoctoral researcher at INRIA in Paris,Stacked graphs - geometryn Visualization and Computer France. He received his Ph.D. in 2006at at the intersec- USA. His research lies
  • 41 2102 HTNOM ,Y .ON ,XX .LOV ,SCIHPARG RETUPMOC DNA NOITAZILAUSIV NO SNOITCASNART EEE .0102 ,strA cinortcelE .2 tceffE ssaM ,—— ]06[ .www//:ptth ”,semag llabtoof LFN gnizilausiV“ ,yelaeH .G .C ]03 .8002 ,strA cinortcelE .eropS ,sixaM ]16[ .8002 ,/ziv LFN/yelaeh/ytlucaf/ude.uscn.csc .3002 ,noisivitcA .yrotirreT ymenE :nietsnefloW ,egamaD hsalpS ]26[ aiv sisylana yalpemag sdrawoT“ ,assonaC .A dna nehcarD .A ]13IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, VOL. XX, NO. Y, MONTH 2012 14 .1102 ,strA cinortcelE .2 ecapS daeD ,semaG larecsiV ]36[ kerTdniM lanoitanretnI eht fo sgnideecorP ni ”,scirtem yalpemag .4002 ,drazzilB .tfarcraW fo dlroW ,drazzilB ]46[ .902–202 .pp ,9002 ,ecnerefnoC .3002 ,noitaroproC evlaV .maetS ,noitaroproC evlaV ]56[ ./moc.tobihcom.www//:ptth ”,tobihcoM“ ]23 .0102 ,soidutS emaG tfosorciM .hcaeR :olaH ,.cnI ,eignuB ]66[ /moc.abonon//:ptth ”,gnikcart & scitsitatS :abonoN“ ]33[30] C. G. Healey, “Visualizing NFL football games,” http://www. [60] ——, Mass Effect 2. Electronic Arts, 2010. .9002 ,stropS AE .01 AFIF ,adanaC AE ]76[ .scitsitats/srepoleved csc.ncsu.edu/faculty/healey/NFL viz/, 2008. [61] Maxis, Spore. Electronic Arts, 2008. .8002 ,noisivitcA .raW ta dlroW :ytuD fo llaC ,hcrayerT ]86[ ./moc.cimotyalp//:ptth ”,cimotyalP“ ]43[31] A. Drachen and A. Canossa, “Towards gameplay analysis via [62] Splash Damage, Wolfenstein: Enemy Territory. Activision,orciM .noitaziliviC ,esorPorciM .1991 ,esorP 2003. ]96[ ./moc.tnegatnok.www//:ptth ”,scitylana laicoS :tnegatnoK“ ]53 gameplay metrics,” in Proceedings of the International MindTrek [63] Visceral Games, Dead Space 2. Electronic1002 ,semargofnI .III noitaziliviC ,semaG sixariF . Arts, 2011. ]07[ ,nayalugaP .J .R ,spillihP .B ,huhcS .E ,nnuG .V .D ,miK .H .J ]63 .9891 ,strA cinortcelE .suolupoP ,gorflluB ]17[ :)EURT( ecneirepxe resu emit-laer gnikcarT“ ,noxiW .R .D dna Conference, 2009, pp. 202–209. [64] Blizzard, World of Warcraft. Blizzard,92004. .sdoG naipmylO eht fo slairT :II suolupoP ,—— .19 1 ,AE ]27[ -sys xelpmoc rof noitulos noitatnemurtsni evisneherpmoc a[32] “Mochibot,” http://www.mochibot.com/. [65] Valve Corporation, Steam. Valve Corporation, tfoS eegopA .D3 nietsnefloW ,erawtfoS di .2991 ,eraw 2003. ]37[ srotcaF namuH no ecnerefnoC MCA eht fo sgnideecorP ni ”,smet[33] “Nonoba: Statistics & tracking,” http://nonoba.com/ [66] Bungie, Inc., Halo: Reach. Microsoft Game Studios, 2010. 91 ,erawtfoS di .mooD ,—— .39 ]47[ .254–344 .pp ,8002 ,smetsyS gnitupmoC ni developers/statistics. [67] EA Canada, FIFA 10. EA Sports,92009.griV .sikarrA rof elttaB :II enuD ,soidutS doowtseW .2 91 ,ni ]57[ :ptth ,0102 ”,metsys gnilfiorp yrtemeleT“ ,slooT emaG DAR ]73[34] “Playtomic,” http://playtomic.com/. [68] Treyarch, Call of Duty: World at War. Activision,il2008. a.m99H ,&rscrzilBtfartfrarWradSa,zzi— .4991 ,drazz B .sn u 8 1 d az O: ca , r . C t — lB ]67[ ]77[ .mth.yrtemelet/moc.slootemagdar.www// ni ”,saes hgih eht no noitcelloc ataD :gniggolF“ ,giwduL .J ]83[35] “Kontagent: Social analytics,” http://www.kontagent.com/. [69] MicroProse, Civilization. MicroProse, 1991.2 ,drazzilB .ytrebiL fo sgniW :II tfarCratS ,—— .010 ]87[ .7002 ,ecnerefnoC srepoleveD emaG eht fo sgnideecorP[36] J. H. Kim, D. V. Gunn, E. Schuh, B. Phillips, R. J. Pagulayan, [70] Firaxis Games, Civilization III. Infogrames,0102 ,semaG 2S .htreweN fo seoreH ,semaG 2S . 2001. ]97[ -ca :IPA eropS“ ,sodrawT .M dna ,nahdohS .S ,ztiwoksoM .D ]93 and D. R. Wixon, “Tracking real-time user experience (TRUE): [71] Bullfrog, Populous. 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[74] ——, Doom. id Software, 1993. .2991 ,esorPorciM .xirP dnarG enO alumroF ,esorPorciM ]48[ ”,seirammus dna sedom rotatceps rof noitca gnitcartxE :semag[37] RAD Game Tools, “Telemetry profiling system,” 2010, http: [75] Westwood Studios, Dune II: Battle 2 ,semaG AE .tiVirgin,H :deepS rof deeN ,semaG noiretirC .010 for Arrakis. usruP to 1992. ]58[ dna noitacilppA no ecnerefnoC lanoitanretnI eht fo sgnideecorP ni //www.radgametools.com/telemetry.htm. [76] Blizzard, Warcraft: Orcs & Humans. Blizzard, 1994. ,evitcaretnI TG .ekauQ ,erawtfoS di .6991 ]68[ .231–421 .pp ,3002 ,semaG retupmoC fo tnempoleveD[38] J. Ludwig, “Flogging: Data collection on the high seas,” in [77] ——, StarCraft. Blizzard, 1998. .1102 ,strA cinortcelE .II egA nogarD ,erawoiB ]78[ gnizilausiV“ ,alawargA .M dna ,syerhpmuH .G ,relbooH .N ]24 .1002 ,drazzilB .II olbaiD ,htroN drazzilB ]88[ ni ”,stnemnorivne lautriv resu-itlum ni sroivaheb evititepmoc Proceedings of the Game Developers Conference, 2007. [78] ——, StarCraft II: Wings of Liberty. 2 ,noisivitcA .2010. aW nredoM :ytuD fo llaC ,draW ytinfinI .900 Blizzard, 2 erafr ]98[ .pp ,4002 ,noitazilausiV no ecnerefnoC EEEI eht fo sgnideecorP[39] D. Moskowitz, S. Shodhan, and M. Twardos, “Spore API: ac- [79] S2 Games, Heroes of Newerth. S2 Games,st2010. ortcelE .2 ynapmoC daB :dlefielttaB ,ECID .0102 , rA cin ]09[ .071–361 cessing a unique database of player creativity,” in SIGGRAPH [80] Mythic, Dark Age of Camelot. Mythic Entertainment, 002 ,odnetniN .tiF iiW ,odnetniN .7 2001. ]19[ -usiv A :wolF-UV“ ,ittunoreI .L dna ,nonaR .R ,orattihC .L ]34 Talks, 2009. [81] ——, Warhammer Online: Age of Reckoning. EA Games, 2008. -norivne lautriv ni noitagivan gnizylana rof loot noitazila[40] M. Twardos, “Spore data,” http://thevioletpiece.com/spore/. [82] CCP Games, EVE Online. CCP Games, 2003. -hparG retupmoC dna noitazilausiV no snoitcasnarT EEEI ”,stnem .6002 .ceD/.voN ,5841–5741 .pp ,6 .on ,21 .lov ,sci[41] N. Halper and M. Masuch, “Action summary for computer [83] EA Tiburon, Madden NFL 11. EA Sports, 2010. emag-enilno fo noitazilausiV“ ,akuziI .K dna samnowahT .R ]44 games: Extracting action for spectator modes and summaries,” [84] MicroProse, Formula One GrandetPrix.rgrednu roines a 1992.mwoB nairB auda MicroProse, si na lanruoJ lanoitanretnI ”,sroivaheb noitca rieht no desab sreyalp in Proceedings of the International Conference on Application and [85] Criterion Games, Need for Speed:eHot P ta gnireenignE retupmo2010.neduts udru Pursuit. EA Games, C ni t .8002 ,ygolonhceT semaG retupmoC fo Development of Computer Games, 2003, pp. 124–132. [86] id Software, Quake. GT Interactive, .1996.NI ,etteyafaL tseW ni ytisrevinU lliw eH ASU , fo noitceteD“ ,nehC .T-.K dna ,egihsaruK .M ,samnowahT .R ]54 [87] Bioware, Dragon Age II. Electronic Arts, 2011.druP morf gnitaudarg eb lanoitanretnI ”,sreyalp emag-enilno fo gniretsulc rof skramdnal[42] N. Hoobler, G. Humphreys, and M. Agrawala, “Visualizing .2102 gnirpS ni eu .7002 ,61–11 .pp ,3 .on ,6 .lov ,ytilaeR lautriV fo lanruoJ competitive behaviors in multi-user virtual environments,” in [88] Blizzard North, Diablo II. Blizzard, r2001..NKH-EEEI fo rebmem a si eH ylbabo p eH -usiv yalpemag ehT“ ,nannerD .P dna ,nworB .A .R ,nilsoJ .S .S ]64 Proceedings of the IEEE Conference on Visualization, 2004, pp. [89] Infinity Ward, Call of Duty: Modern Warfare 2..semag oediv yn2009. t syalp Activision, am oo noitazilausiv dna gniggol rof krowemarf a :otsefinam noitazila 163–170. [90] DICE, Battlefield: Bad Company 2. Electronic Arts, 2010. ,5 .lov ,tnemniatretnE ni sretupmoC ”,atad yalpemag enilno fo[43] L. Chittaro, R. Ranon, and L. Ieronutti, “VU-Flow: A visu- [91] Nintendo, Wii Fit. Nintendo, 2007. .7002 -er a sa atad yalpemag gnizylanA :sreissod reyalP“ ,reldeM .B ]74 alization tool for analyzing navigation in virtual environ- ,11 .lov ,hcraeseR emaG retupmoC fo lanruoJ lanoitanretnI ”,draw ments,” IEEE Transactions on Visualization and Computer Graph- .1102 .beF ,1 .on ics, vol. 12, no. 6, pp. 1475–1485, Nov./Dec. 2006. elbayalP“ ,namaaN .M dna ,eniawS-narviK .F ,soluopokaiD .N ]84[44] R. Thawonmas and K. Iizuka, “Visualization of online-game ”,scihpargofni y-emag fo ecaps ngised eht gniziretcarahC :atad players based on their action behaviors,” International Journal ni srotcaF namuH no ecnerefnoC MCA eht fo sgnideecorP ni Brian Bowmanseforp tseniora undergraduatesalkiN ros is a natsiss na si tsivqmlE .1102 ,smetsyS gnitupmoC of Computer Games Technology, 2008. student in Computer Engineering ato Purdue eht ni retupmoC dna lacirtcelE f loohcS rof saedi retteb evfi !ti kcus nac sdraobredaeL“ ,ttuchtroN .T ]94[45] R. Thawonmas, M. Kurashige, and K.-T. Chen, “Detection of University in West uniivytrip revinU eeuUSA. tHeI n,ieeteniafnE tseW Lafayette, IN, druSU aNg will ey g aL s P r srepoleveD emaG eht fo sgnideecorP ni ”,atad emag gnizilausiv landmarks for clustering of online-game players,” International a yls o e saw H .A , t .0102 ,ecnerefnoC be graduatingsifromniPurduetainreSpring r2012.odtsop , raP AIRNI hcraese larotc Journal of Virtual Reality, vol. 6, no. 3, pp. 11–16, 2007. yrtemoeg - shparg dekcatS“ ,grebnettaW .M dna noryB .L ]05 He is a member2ofnIEEE-HKN. devieprobablyecnarF 600 i .D.hP sih He cer eH . retupmoC dna noitazilausiV no snoitcasnarT EEEI ”,scitehtsea &[46] S. S. Joslin, R. A. Brown, and P. 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Kivran-Swaine, and M. Naaman, “Playable nrettaP A ,nietsrevliS .M dna ,awakahsI .S ,rednaxelA .C ]45 data: Characterizing the design space of game-y infographics,” rosseforP etaicossa na si ylleK-nuknaJ .J.T drofxO :kroY weN .noitcurtsnoC ,sgnidliuB ,snwoT :egaugnaL nihtiw gnireenigne dna ecneics retupmoc fo .7791 ,sserP ytisrevinU in Proceedings of the ACM Conference on Human Factors in Computing Systems, 2011. Niklas Elmqvist fo eanlloassistant ht roW semaJ eht -nE is ge C yelgaB professor ./moc.aminihcam.www//:ptth ,moc.aminihcaM ]55 ,SM ,ytisrevinU etatS ippississiM ,gnireenig[49] T. Northcutt, “Leaderboards can suck it! five better ideas for in the SchoolceofetElectricala and hComputer .ASU - sr ni eht ta t seil craeser siH Engineering atoitPurdue nUniversityna cfiiWest fo noit .n azilausiv oitamrofni d in tneics visualizing game data,” in Proceedings of the Game Developers Lafayette, IN,o USA. inU ehwas rf previously viacer eH SELPMAXE EMA Conference, 2010. f ytisrev He t mo DhP sih de e[50] L. Byron and M. Wattenberg, “Stacked graphs - geometry postdoctoral rebmem a si data INRIAi ,sivaD ,ainrofilaC researcher n 3002 n in Paris, .9891 ,dnubredørB .ytiCmiS ,erawtfoS sixaM ]65 France. He ,receivedteicoS retupmoCinht 2006 EEI fo oot ,eH .y his Ph.D. e dna E .0102 ,noisivitcA .spO kcalB :ytuD fo llaC ,hcrayerT ]75
  • Call of Duty: Black Ops—50k
  • Angry Birds—200,000 yrs of
  • Mass Effect3
  • Every game you play is a source of data
  • World of Warcraft2004
  • COD: Black Ops2010
  • SimCity1989
  • Framework of Vis inGames
  • Framework of Vis in Design Patterns inGames Games
  • Framework of Vis in Design Patterns inGames Games
  • The Vis in Games Framework
  • Primary PurposeTarget AudienceTemporal UsageVisual ComplexityImmersion/Integration
  • Primary PurposeTarget AudienceTemporal UsageVisual ComplexityImmersion/Integration
  • Temporal UsageContinuous SimCity 4
  • Temporal UsageIntermittent Civ 5
  • Temporal UsageRetrospective Halo: Player Kills Reach
  • Temporal UsageRetrospective Player Deaths Halo: Reach
  • Temporal UsageRetrospective Kills - Deaths Halo: Reach
  • Temporal UsageProspective XCOM: EU
  • Design Patterns for Vis in Gaming
  • Heads-Up Display Dragon Age 2Primary Purpose: Status Target Audience: Player Temporal Usage: ContinuouVisual Complexity: Basic Immersion/Integration: Immersive or Informative/
  • Heads-Up Display Doom 2Primary Purpose: Status Target Audience: Player Temporal Usage: ContinuouVisual Complexity: Basic Immersion/Integration: Immersive or Informative/
  • Heads-Up Display Angry BirdsPrimary Purpose: Status Target Audience: Player Temporal Usage: ContinuouVisual Complexity: Basic Immersion/Integration: Immersive or Informative/
  • Heads-Up DisplayMirrorsEdge Primary Purpose: Status Target Audience: Player Temporal Usage: Continuou Visual Complexity: Basic Immersion/Integration: Immersive or Informative/
  • Data in TimePrimary Purpose: Train/Comm. Target Audience: Player/Observer TemporalUsage: Retrospective Visual Complexity: Intermediate Immersion/Integration
  • Data in Time StarcraftPrimary Purpose: Train/Comm. Target Audience: Player/Observer TemporalUsage: Retrospective Visual Complexity: Intermediate Immersion/Integration
  • Data in Time Starcraft Civilization 3Primary Purpose: Train/Comm. Target Audience: Player/Observer TemporalUsage: Retrospective Visual Complexity: Intermediate Immersion/Integration
  • Data in Time StarcraftCOD:BlOps Civilization 3 Primary Purpose: Train/Comm. Target Audience: Player/Observer Temporal Usage: Retrospective Visual Complexity: Intermediate Immersion/Integration
  • Implications
  • Benefits for Gaming
  • Benefits for Gaming
  • Benefits for Gaming
  • Benefits for Gaming
  • Benefits for Vis Research
  • Benefits for Vis Research
  • Benefits for Vis Research
  • Benefits for Vis Research
  • “Visualizing NFL football games,” http://www. [60] ——, Mass Effect 2. Electronic Arts, 2010. aculty/healey/NFL viz/, 2008. [61] Maxis, Spore. Electronic Arts, 2008.nd A. Canossa, “Towards gameplay analysis via [62] Splash Damage, Wolfenstein: Enemy Territory. Activision, 2003. rics,” in Proceedings of the International MindTrek [63] Visceral Games, Dead Space 2. Electronic Arts, 2011.09, pp. 202–209. [64] Blizzard, World of Warcraft. Blizzard, 2004. ttp://www.mochibot.com/. [65] Valve Corporation, Steam. Valve Corporation, 2003. atistics & tracking,” http://nonoba.com/ [66] Bungie, Inc., Halo: Reach. Microsoft Game Studios, 2010. atistics. [67] EA Canada, FIFA 10. EA Sports, 2009.http://playtomic.com/. [68] Treyarch, Call of Duty: World at War. Activision, 2008. ocial analytics,” http://www.kontagent.com/. [69] MicroProse, Civilization. MicroProse, 1991. V. Gunn, E. Schuh, B. Phillips, R. J. Pagulayan, [70] Firaxis Games, Civilization III. Infogrames, 2001. AND COMPUTER GRAPHICS, VOL. XX, NO. Y, MONTH 2012 14 on, “Tracking real-time user experience (TRUE): [71] Bullfrog, Populous. Electronic Arts, 1989. ive instrumentation solution for complex sys- [72] ——, Populous II: Trials of the Olympian Gods. EA, 1991. eedings of the ACM Conference on Human Factors [73] id Software, Wolfenstein 3D. Apogee Software, 1992. otball games,” http://www. Systems, 2008, pp. 443–452. [60] ——, Mass Effect 2. ——, Doom. Arts, 2010. [74] Electronic id Software, 1993. Toward Visualization for ools, “Telemetry profiling system,” Maxis,http: [75] Westwood Studios, Dune II: Battle for Arrakis. Virgin, 1992. viz/, 2008. [61] 2010, Spore. Electronic Arts, 2008. metools.com/telemetry.htm. [62] Splash Damage, Wolfenstein: Enemy Territory. Humans. Blizzard, 1994.wards gameplay analysis via [76] Blizzard, Warcraft: Orcs & Activision, 2003. logging: Data collection on the high seas,” Games, Dead Space 2. Electronic Arts, 2011. of the International MindTrek [63] Visceral in [77] ——, StarCraft. Blizzard, 1998. the Game Developers Conference, 2007. Blizzard, World of Warcraft. Blizzard, 2004.of Liberty. Blizzard, 2010. [64] [78] ——, StarCraft II: Wings , S. Shodhan, and M. Twardos, [65] Valve Corporation, S2 Games, Heroes of Newerth. 2003. Games, 2010. ot.com/. “Spore API: ac- [79] Steam. Valve Corporation, S2 ue database of player creativity,” in SIGGRAPH Halo: Reach. Microsoft of Camelot. Mythic Entertainment, 2001. ng,” http://nonoba.com/ [66] Bungie, Inc., [80] Mythic, Dark Age Game Studios, 2010. [67] EA Canada, FIFA 10. EA Sports, 2009. [81] ——, Warhammer Online: Age of Reckoning. EA Games, 2008. m/. data,” http://thevioletpiece.com/spore/. [82] CCP Games, War. Online. CCP Games, 2003. Spore [68] Treyarch, Call of Duty: World at EVE Activision, 2008. d M. Masuch, “Action summary forMicroProse, Civilization. MicroProse, 1991. 11. EA Sports, 2010.p://www.kontagent.com/. [69] computer [83] EA Tiburon, Madden NFL Games: B. Phillips, R.spectator modes and summaries,” [84] MicroProse, Formula One Grand Prix. MicroProse, 1992. ing action for J. Pagulayan, [70] Firaxis Games, Civilization III. Infogrames, 2001. methe International Conference on Application and [85] Criterion Games, Need for Speed: Hot Pursuit. EA Games, 2010. of user experience (TRUE): [71] Bullfrog, Populous. Electronic Arts, 1989. Computer for complex pp. 124–132. ——, Populous[86]Trials of the Olympian Gods. EA, 1991.1996. solution Games, 2003, sys- [72] II: id Software, Quake. GT Interactive,G. Humphreys, and M. Agrawala, “Visualizing Wolfenstein 3D. Dragon Age II. Electronic Arts, 2011. Conference on Human Factors [73] id Software, [87] Bioware, Apogee Software, 1992. [74] ——, Doom. [88] Blizzard North, Diablo II. Blizzard, 2001.43–452. in multi-user virtual environments,” in id Software, 1993.ehaviors the IEEE Conference on Visualization, 2004, pp. Studios,Infinity Ward, Call of Duty: Modern Warfare 2. Activision, 2009. ofiling system,” 2010, http: [75] Westwood [89] Dune II: Battle for Arrakis. Virgin, 1992. etry.htm. [76] Blizzard, Warcraft: Orcs & Battlefield: Bad Company 2. Electronic Arts, 2010. [90] DICE, Humans. Blizzard, 1994. ction on the highIeronutti, “VU-Flow: A StarCraft. Blizzard, 1998. Fit. Nintendo, 2007. . Ranon, and L. seas,” in [77] ——, visu- [91] Nintendo, Wii Theory, Design Space, and for analyzing navigation in virtual environ- Conference, 2007. [78] ——, StarCraft II: Wings of Liberty. Blizzard, 2010.M. Twardos, on Visualization and Computer Graph- Heroes of Newerth. S2 Games, 2010. Transactions “Spore API: ac- [79] S2 Games, er6, pp. 1475–1485, Nov./Dec. 2006. Mythic, Dark Age of Camelot. Mythic Entertainment, 2001. . creativity,” in SIGGRAPH [80] s and K. Iizuka, “Visualization[81]online-game of ——, Warhammer Online: Age of Reckoning. EA Games, 2008. on their action behaviors,”/thevioletpiece.com/spore/. International Journal EVE Online. CCP Games, 2003. [82] CCP Games, Brian Bowman is a senior undergraduate ion Technology, 2008. amessummary for computer [83] EA Tiburon, Madden NFL 11. EA Sports, 2010.Computer Engineering at Purdue student in s, M. Kurashige, and K.-T. Chen, “Detection of Formula One Grand Prix.University in West Lafayette, IN, USA. He willator modes and summaries,” [84] MicroProse, MicroProse, 1992. clustering of online-game players,” InternationalConference on Application and [85] Criterion Games, Need for Speed: Hot Pursuit. EA Games, 2010. in Spring 2012. be graduating from Purdueual Reality, vol. 6, no. 3, pp. 11–16, 2007.Software, Quake. GT Interactive, He is a member of IEEE-HKN. He probably003, pp. 124–132. [86] id 1996. A. Brown, and P. Drennan, “The[87] Bioware, Dragon Age II. Electronic Arts, 2011. M. Agrawala, “Visualizing gameplay visu- plays too many video games. Brian Bowman, Niklas Elmqvist, T.J. Jankun-Kelly er virtual environments,” in and visualization festo: a framework for logging [88] Blizzard North, Diablo II. Blizzard, 2001. eeplay data,” Computers in Entertainment, vol.Ward, Call of Duty: Modern Warfare 2. Activision, 2009. on Visualization, 2004, pp. [89] Infinity 5, [90] DICE, Battlefield: Bad Company 2. Electronic Arts, 2010. ayer dossiers: Analyzing gameplay data as a re-Wii Fit. Nintendo, 2007. ronutti, “VU-Flow: A visu- [91] Nintendo, igation in virtual environ- Research, vol. 11, tional Journal of Computer Game11.lization and Computer Graph-os, F. Kivran-Swaine, and M. Naaman, “Playable Nov./Dec. 2006. rizing the design space of game-y infographics,”Visualization of online-game aviors,” ACM Conference on Human Factors in of the International Journal Brian Bowman is Niklas Elmqvist is an assistant professor a senior undergraduate tems, 2011. 8. “Leaderboards “Detection of student in Computer Engineering at Purdue in the School of Electrical and Computer d K.-T. Chen, can suck it! five better ideas for University in West Lafayette, IN, USA. He willUniversity in West Engineering at Purdue me data,” in Proceedings of -game players,” Internationalthe Game Developers10.3, pp. 11–16, 2007. be graduating fromLafayette,inIN, USA. He was previously a Purdue Spring 2012.o. He is a member ofpostdoctoral He probablyat INRIA in Paris, IEEE-HKN. researcher M. Wattenberg, “Stacked graphs - geometry ennan, “The gameplay visu- IEEE Transactions on Visualization and Computer plays too many video games. France. He received his Ph.D. in 2006 or logging and visualization from Chalmers University of Technology in 14, no. Entertainment, vol. 5, ters in 6, pp. 1245–1252, 2008. amers mimic the season’s ups and downs,” The ¨ Goteborg, Sweden. He is a member of the s, Feb. 2011. IEEE and the Computer Society. In another zing gameplay data as a re- life, he is a wizard, assassin, or knight indputer Game Research,structure of the information J. Mackinlay, “The vol. 11,design space,” in Proceedings of the IEEE Sympo- whatever game currently takes his fancy.,ation M. Naaman, “Playable 92–99. and Visualization, 1997, pp.ologie graphique: Les diagrammes - Les r´seaux - Lesace of game-y infographics,” erance, on Human Factors in rence 1967. S. Ishakawa, and M. Silverstein, A Pattern Niklas Elmqvist is an assistant professorns, Buildings,better ideas for New York: Oxford T.J. Jankun-Kelly is an associate Professor in the School of Electrical and Computersuck it! five Construction. ss, 1977.dings of the Game Developers Engineering at Purdue University in West engineering within of computer science andm, http://www.machinima.com/. Lafayette, IN, USA. He was previously a College of En- the James Worth Bagley gineering, Mississippi State University, MS, postdoctoral researcher at INRIA in Paris,Stacked graphs - geometryn Visualization and Computer France. He received his Ph.D. in 2006at at the intersec- USA. His research lies
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Naaman, “Playable Nov./Dec. 2006. rizing the design space of game-y infographics,”Visualization of online-game aviors,” ACM Conference on Human Factors in of the International Journal Brian Bowman is Niklas Elmqvist is an assistant professor a senior undergraduate tems, 2011. 8. “Leaderboards “Detection of student in Computer Engineering at Purdue in the School of Electrical and Computer d K.-T. Chen, can suck it! five better ideas for University in West Lafayette, IN, USA. He willUniversity in West Engineering at Purdue me data,” in Proceedings of -game players,” Internationalthe Game Developers10.3, pp. 11–16, 2007. be graduating fromLafayette,inIN, USA. He was previously a Purdue Spring 2012.o. He is a member ofpostdoctoral He probablyat INRIA in Paris, IEEE-HKN. researcher M. Wattenberg, “Stacked graphs - geometry ennan, “The gameplay visu- IEEE Transactions on Visualization and Computer plays too many video games. France. He received his Ph.D. in 2006 or logging and visualization from Chalmers University of Technology in 14, no. Entertainment, vol. 5, ters in 6, pp. 1245–1252, 2008. amers mimic the season’s ups and downs,” The ¨ Goteborg, Sweden. He is a member of the s, Feb. 2011. IEEE and the Computer Society. In another zing gameplay data as a re- life, he is a wizard, assassin, or knight indputer Game Research,structure of the information J. Mackinlay, “The vol. 11, whatever game currently takes his fancy.design space,” in Proceedings of the IEEE Sympo-,ation M. Naaman, “Playable 92–99. and Visualization, 1997, pp.ologie graphique: Les diagrammes - Les r´seaux - Les e Watched a (fun) talk!ace of game-y infographics,”rance, on Human Factors in rence 1967. S. Ishakawa, and M. Silverstein, A Pattern Niklas Elmqvist is an assistant professorns, Buildings,better ideas for New York: Oxford T.J. Jankun-Kelly is an associate Professor in the School of Electrical and Computersuck it! five Construction. ss, 1977.dings of the Game Developers Engineering at Purdue University in West engineering within of computer science andm, http://www.machinima.com/. Lafayette, IN, USA. He was previously a College of En- the James Worth Bagley gineering, Mississippi State University, MS, postdoctoral researcher at INRIA in Paris,Stacked graphs - geometryn Visualization and Computer France. He received his Ph.D. in 2006at at the intersec- USA. His research lies