DOCSLIB.ORG

The Mantra of Visual Information Seeking

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
The Mantra of Visual Information Seeking Overview www.wiley.com/wires/compstats FIGURE 8| A screenshot of GeoTime. as our perception and cognition are concerned, the another. The proximity and similarity principles can whole is more than the sum of parts. Most commonly be used simultaneously to reinforce each other. known Gestalt principles are proximity, similarity, continuity, closure, figure and ground, and symmetry. The Mantra of Visual Information Seeking A comprehensive explanation of these principles and The most widely known visual information seeking a rich set of examples can be found in How Maps 41 mantra is given by Ben Shneiderman, University Work in the context of cartography, that is, the of Maryland: Overview first, zoom and filter, design of geographically based thematic maps. then details-on-demand.44 This mantra insightfully The proximity principle says that we tend to see summarizes the essential elements of interacting with groupings of individual items in a visual arrangement graphically presented information. based on the proximity between these items. Items Designers of visual overviews commonly capi- that are relatively close to one another tend to give us talize on metaphors that can give users a sense of a sense of similarity. In other words, we see individual intuitiveness and familiarity. Naturally, metaphors items in groups of some underlying similarity. This of an information space are particularly popular, principle has been adapted by the information visu- especially in 1990s, ranging from two-dimensional alization community from the early stage. Algorithms maps, three-dimensional landscape views and con- that can arrange information items in this fashion tours, to star fields and galaxies of information. An tap into the proximity principle. Some interesting important function of an overview is to depict inter- examples include Bead42 and Information Mural.43 relationships among units of information. Units of The similarity principle from Gestalt psychology textual information include words, sentences, docu- says that visual attributes such as the shape, color, and ments, and collections of documents such as websites. texture are cues for us to group items, for example, Units of visual information include scenes, episodes, all the circles in one group and all the triangles in and libraries of videos. 394 2010 John Wiley & Sons, Inc. Volume 2, July/August 2010 WIREs Computational Statistics Information visualization Information space metaphors naturally invite the context of scientific discovery in cognitive science, navigational operations such as zoom, pan, tilt, and psychology, and history of science. Few connections rotate. One of the earlier claims and design goals of have been established so far between the study of information visualization is that good information insight in other disciplines and the field of information visualization should present information to users intu- visualization. An intriguing introduction to some itively. Many filtering operations have been adapted of the recent understanding of the brain activities to enable users interact with dynamic information that lead to insights can be found in a New Yorker visualization, including brushing, linking, dynamic article The Eureka Hunt.45 The Nature of Insight is queries, and coordinated views. a comprehensive collection of studies of insight.46 In 1996, Shneiderman offered a taxonomy for In a recently developed explanatory and com- visual information seeking.44 The taxonomy divides putational theory of scientific discovery, the nature general visual information seeking into seven data of insight is characterized by a brokerage mech- types and seven tasks. This taxonomy is one of anism and a burst function of recognition.47 The the earliest and most influential contributions to the brokerage mechanism echoes what is described in information visualization field. the Eureka Hunt in that one arrives at insights by linking previously unconnected thoughts. The theory Seven Data Types is computational and it is possible to formulate the • one-dimensional data; search for insights as a problem of searching for the • potential linkage between even the most unthinkable two-dimensional data; relations. Initial studies of transformative discoveries • three-dimensional data; such as Nobel Prize winning discoveries are particu- • temporal data; larly promising. This approach is particularly relevant • multidimensional data; to visual analytics and insight-based evaluative stud- • ies because they can characterize insightful patterns in tree data; terms of structural and temporal properties. • network data. Within the information visualization commu- nity, notable efforts on characterizing and measuring Seven Tasks insights include exploratory approaches as opposed 9 • overview; to benchmark-based experimental studies, lessons learned from the first 3 years of InfoVis contests,48 • zoom; and more recent reflection in the context of visual • filter; analytics.8 An interesting framework of evaluating • details-on-demand; interactive visualizations is proposed recently in • relate; Ref 49. The framework is built on top of a generic conceptual model in human–computer interaction, • history; namely Don Norman’s Seven Stages of Action.50 • extract. According to the Seven Stages of Action, two stages of interacting with computer interfaces are particularly The data type by task taxonomy has influenced problematic: execution and evaluation. The gulf of a generation of information visualization researchers. execution and the gulf of evaluation are used to refer Other notable efforts include the data state reference to these problematic stages. The gulf of execution, model.3 for example, should be narrowed so that users can accomplish their tasks smoothly and seamlessly. The gulf of evaluation should be narrowed so that users The Pursuit of Insights can judge their progress accurately. Reflections on insight-centric evaluation are moti- Much of the discussions in information visu- vated by the increasing concern of how to establish alization on insights primarily address practical and the effectiveness of interacting with information visu- methodological issues concerning how evaluative alization interfaces. On the one hand, it is almost a studies should be designed to capture the effectiveness community-wide consensus that insight is the ultimate of an information visualization design in terms of goal of information visualization. On the other hand, insights. The types of insights that are relevant the definition of insight in the information visualiza- to information visualization and evaluative studies tion literature per se has been vague and ambiguous. have theoretical and practical implications. We The nature of insight has been extensively studied in found two meta-analysis studies of information Volume 2, July/August 2010 2010 John Wiley & Sons, Inc. 395 Overview www.wiley.com/wires/compstats visualization.51,52 Given the growing calls for level, scalability issues remain to be a long-lasting theoretical foundations in the field, this is expected to challenge.55 Some of the algorithms developed for be a significant topic of research. clustering large-scale data sets in machine learning are particularly appealing, such as Refs 56,57 and one Theoretical Frameworks can expect these algorithms will soon find their ways to information visualizations. The general consensus, as reported by a recent workshop and a few other public presentations, was that information visualization currently lacks Edge Bundling 53 adequate theoretical foundations. As a result, many Edge bundling is an emerging strategy to solve a com- approaches are ad hoc in nature. A week-long sem- mon problem in visualizing a densely connected graph inar took place at Dagstuhl, Germany in mid-2007, due to cluttered images caused by overlapping edges. for example, addressed four potential directions for Avoiding edge crossings has been long recognized as developing new theories. The lack of theories becomes one of the constraints that could improve the clarity of particularly prominent in information visualization resultant visualizations. Recently, an interesting strat- courses and when designing empirical and evaluative egy has emerged—that is the use of edge bundling tech- studies. niques in a variety of graph visualizations to increase The search for theoretical foundations increas- the clarity of visualized patterns. Bundling reduces ingly introduces and adopts theories and conceptual visual clutter. Visualizations with bundled edges make frameworks from other fields and disciplines. For it easier for viewers to see underlying patterns than example, distributed cognition in human–computer non-bundled versions,58 for example, as shown in Fig- interaction is seen as a potential candidate for a the- ure 9. Edge bundling is a generic technique in nature 54 oretical framework for information visualization. because it can be applied virtually to all node-and-link Norman’s Seven Stages of Action, also in human–com- diagrams regardless the underlying layout algorithms. puter interaction, provides a new insight into inter- In this sense, it is similar to other generic display tech- acting with information visualizations, specifically on niques such as fisheye views. A geometry-based edge 49 the gulf of execution and the gulf of evaluation. bundling example appears recently, showing promi- Many information visualizations lack a quanti- nent patterns of migration in the USA59 (Figure 10). tative measure that could indicate the overall
Load more

Recommended publications
  • An Interview with Visualization Pioneer Ben Shneiderman
    6/23/2020 The purpose of visualization is insight, not pictures: An interview with visualization pioneer Ben Shneiderman The purpose of visualization is insight, not pictures: An interview with visualization pioneer Ben Shneiderman Jessica Hullman Follow Mar 12, 2019 · 13 min read Few people in visualization research have had careers as long and as impactful as Ben Shneiderman. We caught up with Ben over email in between his travels to get his take on visualization research, what’s worked in his career, and his advice for practitioners and researchers. Enjoy! Multiple Views: One of the main purposes of this blog is to explain to people what visualization research is to practitioners and, possibly, laypeople. How would you answer the question “what is visualization research”? Ben S: First let me define information visualization and its goals, then I can describe visualization research. Information visualization is a powerful interactive strategy for exploring data, especially when combined with statistical methods. Analysts in every field can use interactive information visualization tools for: more effective detection of faulty data, missing data, unusual distributions, and anomalies deeper and more thorough data analyses that produce profounder insights, and richer understandings that enable researchers to ask bolder questions. Like a telescope or microscope that increases your perceptual abilities, information visualization amplifies your cognitive abilities to understand complex processes so as to support better decisions. In our best
    [Show full text]
  • Treemap Art Project
    EVERY ALGORITHM HAS ART IN IT Treemap Art Project By Ben Shneiderman Visit Exhibitions @ www.cpnas.org 2 tree-structured data as a set of nested rectangles) which has had a rippling impact on systems of data visualization since they were rst conceived in the 1990s. True innovation, by denition, never rests on accepted practices but continues to investigate by nding new In his book, “Visual Complexity: Mapping Patterns of perspectives. In this spirit, Shneiderman has created a series Information”, Manuel Lima coins the term networkism which of prints that turn our perception of treemaps on its head – an he denes as “a small but growing artistic trend, characterized eort that resonates with Lima’s idea of networkism. In the by the portrayal of gurative graph structures- illustrations of exhibition, Every AlgoRim has ART in it: Treemap Art network topologies revealing convoluted patterns of nodes and Project, Shneiderman strips his treemaps of the text labels to links.” Explaining networkism further, Lima reminds us that allow the viewer to consider their aesthetic properties thus the domains of art and science are highly intertwined and that laying bare the fundamental property that makes data complexity science is a new source of inspiration for artists and visualization eective. at is to say that the human mind designers as well as scientists and engineers. He states that processes information dierently when it is organized visually. this movement is equally motivated by the unveiling of new In so doing Shneiderman seems to daringly cross disciplinary is exhibit is a project of the knowledge domains as it is by the desire for the representation boundaries to wear the hat of the artist – something that has Cultural Programs of the National Academy of Sciences of complex systems.
    [Show full text]
  • The Eyes Have It: a Task by Data Type Taxonomy for Information Visualizations
    The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations Ben Shneiderman Department of Computer Science, Human-Computer Interaction Laboratory, and Institute for Systems Research University of Maryland College Park, Maryland 20742 USA ben @ cs.umd.edu keys), are being pushed aside by newer notions of Abstract information gathering, seeking, or visualization and data A useful starting point for designing advanced graphical mining, warehousing, or filtering. While distinctions are user interjaces is the Visual lnformation-Seeking Mantra: subtle, the common goals reach from finding a narrow set overview first, zoom and filter, then details on demand. of items in a large collection that satisfy a well-understood But this is only a starting point in trying to understand the information need (known-item search) to developing an rich and varied set of information visualizations that have understanding of unexpected patterns within the collection been proposed in recent years. This paper offers a task by (browse) (Marchionini, 1995). data type taxonomy with seven data types (one-, two-, Exploring information collections becomes three-dimensional datu, temporal and multi-dimensional increasingly difficult as the volume grows. A page of data, and tree and network data) and seven tasks (overview, information is easy to explore, but when the information Zoom, filter, details-on-demand, relate, history, and becomes the size of a book, or library, or even larger, it extracts). may be difficult to locate known items or to browse to gain an overview, Designers are just discovering how to use the rapid and Everything points to the conclusion that high resolution color displays to present large amounts of the phrase 'the language of art' is more information in orderly and user-controlled ways.
    [Show full text]
  • Christopher L. North – Curriculum Vitae (Updated Sept 2014)
    Christopher L. North – Curriculum Vitae (updated Sept 2014) Department of Computer Science (540) 231-2458 114 McBryde Hall (540) 231-9218 fax Virginia Tech north @ vt . edu Blacksburg, VA 24061-0106 http://www.cs.vt.edu/~north/ Google Scholar: • http://scholar.google.com/citations?user=yBZ7vtkAAAAJ • h-index = 35 Short Bio: Dr. Chris North is a Professor of Computer Science at Virginia Tech. He is Associate Director of the Discovery Analytics Center, and leads the Visual Analytics research group. He is principle architect of the GigaPixel Display Laboratory, one of the most advanced display and interaction facilities in the world. He also participates in the Center for Human-Computer Interaction, and the Hume Center for National Security, and is a member of the DHS supported VACCINE Visual Analytics Center of Excellence. He was awarded Faculty Fellow of the College of Engineering in 2007, and the Dean’s Award for Research Excellence in 2014. He earned his Ph.D. at the University of Maryland, College Park, in 2000. He has served as General Co-Chair of IEEE VisWeek 2009, and as Papers Chair of the IEEE Information Visualization (InfoVis) and IEEE Visual Analytics Science and Technology (VAST) Conferences. He has served on the editorial boards of IEEE Transactions on Visualization and Computer Graphics (TVCG), the Information Visualization journal, and Foundations and Trends in HCI. He has been awarded over $6M in grants, co-authored over 100 peer-reviewed publications, and delivered 3 keynote addresses at symposia in the field. He has graduated 8 Ph.D. and 14 M.S. thesis students, 4 receiving outstanding research awards at Virginia Tech, and advised over 70 undergraduate research students including several award winners at Virginia Tech’s annual undergraduate research symposium.
    [Show full text]
  • Human-Centered Artificial Intelligence: Three Fresh Ideas
    AIS Transactions on Human-Computer Interaction Volume 12 Issue 3 Article 1 9-30-2020 Human-Centered Artificial Intelligence: Three Fresh Ideas Ben Shneiderman University of Maryland, [email protected] Follow this and additional works at: https://aisel.aisnet.org/thci Recommended Citation Shneiderman, B. (2020). Human-Centered Artificial Intelligence: Three Fresh Ideas. AIS Transactions on Human-Computer Interaction, 12(3), 109-124. https://doi.org/10.17705/1thci.00131 DOI: 10.17705/1thci.00131 This material is brought to you by the AIS Journals at AIS Electronic Library (AISeL). It has been accepted for inclusion in AIS Transactions on Human-Computer Interaction by an authorized administrator of AIS Electronic Library (AISeL). For more information, please contact [email protected]. Transactions on Human-Computer Interaction 109 Transactions on Human-Computer Interaction Volume 12 Issue 3 9-2020 Human-Centered Artificial Intelligence: Three Fresh Ideas Ben Shneiderman Department of Computer Science and Human-Computer Interaction Lab, University of Maryland, College Park, [email protected] Follow this and additional works at: http://aisel.aisnet.org/thci/ Recommended Citation Shneiderman, B. (2020). Human-centered artificial intelligence: Three fresh ideas. AIS Transactions on Human- Computer Interaction, 12(3), pp. 109-124. DOI: 10.17705/1thci.00131 Available at http://aisel.aisnet.org/thci/vol12/iss3/1 Volume 12 pp. 109 – 124 Issue 3 110 Transactions on Human-Computer Interaction Transactions on Human-Computer Interaction Research Commentary DOI: 10.17705/1thci.00131 ISSN: 1944-3900 Human-Centered Artificial Intelligence: Three Fresh Ideas Ben Shneiderman Department of Computer Science and Human-Computer Interaction Lab, University of Maryland, College Park [email protected] Abstract: Human-Centered AI (HCAI) is a promising direction for designing AI systems that support human self-efficacy, promote creativity, clarify responsibility, and facilitate social participation.
    [Show full text]
  • Geotime for a Patrol
    GeoTime Visualization for Peace Support Operations William Wright and Thomas Kapler Oculus Info Inc. Toronto, Canada [email protected] 1. INTRODUCTION Visualization display techniques allow people to see, use and interact with large amounts of multi- dimensional data in a natural and easy manner, particularly in complex, time sensitive situations. Information visualization techniques amplify cognition by increasing human mental resources, reducing search times, improving recognition of patterns, increasing inference making, and increasing monitoring scope [1, 6]. These benefits translate into significant system and task related performance objectives [7]. As more information is available, from more sources, commanders with advanced visualization capabilities will be able to make the most of this data without being overwhelmed. Operational and planning tasks are both amenable to visualization support. Previous work with DARPA’s Command Post of the Future program has shown the importance of multiple, shared, tailored views rather than one common operational picture, and has demonstrated significant progress for Force-on-Force scenarios [3, 7]. There is an opportunity to explore potential high payoff, leap ahead tailored visualization techniques suitable for the unique demands of Peace Support Operations (PSO) and that build on the success to date. This paper reports on one new concept for geo-temporal visualization conceived during a research project sponsored by DRDC in 2002. The term Operations Other than War (OOTW) covers a wide range of activities, for example domestic operations in Canada (Ice Storm 98), humanitarian assistance abroad (Honduran earthquake), or peace support operations (Bosnia). In order to focus the initial work, the investigation and analysis was confined to peace support operations.
    [Show full text]
  • Empirical Studies in Information Visualization: Seven Scenarios Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale
    Empirical Studies in Information Visualization: Seven Scenarios Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale To cite this version: Heidi Lam, Enrico Bertini, Petra Isenberg, Catherine Plaisant, Sheelagh Carpendale. Empirical Studies in Information Visualization: Seven Scenarios. IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, 2012, 18 (9), pp.1520–1536. 10.1109/TVCG.2011.279. hal-00932606 HAL Id: hal-00932606 https://hal.inria.fr/hal-00932606 Submitted on 17 Jan 2014 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. JOURNAL SUBMISSION 1 Empirical Studies in Information Visualization: Seven Scenarios Heidi Lam Enrico Bertini Petra Isenberg Catherine Plaisant Sheelagh Carpendale Abstract—We take a new, scenario based look at evaluation in information visualization. Our seven scenarios, evaluating visual data analysis and reasoning, evaluating user performance, evaluating user experience, evaluating environments and work practices, evaluating communication through visualization, evaluating visualization algorithms, and evaluating collaborative data analysis were derived through an extensive literature review of over 800 visualization publications. These scenarios distinguish different study goals and types of research questions and are illustrated through example studies. Through this broad survey and the distillation of these scenarios we make two contributions.
    [Show full text]
  • Beyond Animation: Interactive Visualization Techniques for Big Transportation Data
    Beyond Animation: Interactive Visualization Techniques for Big Transportation Data Michael L. Pack Univ. of Maryland CATT Laboratory Traditional Modeling & Simulation Outputs Things we all care about • Solving problems • Analyzing data • See what we study actually get used by others! Things we all NEED to care MORE about • Showcasing our work to others • Getting people excited about our work • Getting people who have the power to fund our work willing to fund MORE of our work! • COMMUNICATING RESULTS! Changing our mindset • Is an animation always appropriate? • What other options do I have? • Should this be difficult? • Do we have the tools we need? • Goal: “Effectively communicating our results to get better results.” How much data are we getting today? • RITIS Today • Traffic events: 40,000 records per day: 0.001 Gb/day • Traffic detectors: 35,000,000 records per day: 5 Gb/day • Probe vehicle data: 4,200,000,000 records per day: 550 Gb/day • CCTV, weather, radio, etc: NO,STA,TSK,EPT records per day: ??? Tb/day • V2X & Automation data: ?,???,???,???,??? records per day: ??? ?b/day Our Challenge • Our mission is to make ALL of this data • easily accessible, • usable, and • understandable to end users and ITS applications… How do we attempt to do this? 7 © 2013 Michael L. Pack, UMD CATT Laboratory Visual Analytics • Not just about pics and graphs… • Traditional querying (or analysis) demands that you • Know what question to ask • know how to ask it (SQL or other language) • Visual Analytics provide the freedom to: - Explore data in new ways - Ask meaningful questions that you wouldn’t have normally thought to ask - Develop new hypothesis - and realize new solutions 8 Why Visualization? • Visual bandwidth is enormous • Human perceptual skills are remarkable • Trend, cluster, gap, outlier..
    [Show full text]
  • Ben Shneiderman Presented by Dinah Coops, Bella Chiu, and Kyle Thomas
    Ben Shneiderman Presented by Dinah Coops, Bella Chiu, and Kyle Thomas Ben Shneiderman at the TreeMap Art Project exhibit, 2013 HCDE 501 - January 22, 2019 https://treemapart.wo rdpress.com Presenters Dinah Bella Kyle Career Trajectory Hypertext Research Direct Manipulation, and dev. of HyperTIES Spotfire From Keyword Search BS, MS & PHD + + to Exploration Teaching Founding Director Reading in Information + Professor at of HCI Lab Visualization: Using Analyzing Social Media University of MD University of Maryland Vision to think Networks with Node XL 1963- 1970- 1997- 2002- 2010- 2015- 1983 1986 2018 1973 1999 2003 2011 2018 Software The Eight Golden Rules Leonardo’s Laptop Node XL Psychology of Interface Design + + + + Craft of Information The New ABC’s Nassi-Shneiderman Designing the Visualizations of Research Diagrams User Interface + + Treemaps Rock the Research Scope of Influence: Theory and Frameworks 5 USES OF HCI THEORY TREE- HCI MAPPING THEORY INFORMATION VISUALIZATION SOFTWARE PSYCHOLOGY DESIGNING THE USER NASSI- SHNEIDERMA N INTERFACE DIAGRAMS 6 REVISIONS SPOTFIRE DIRECT EIGHT GOLDEN MANIPULATION RULES OF INTERFACE DESIGN HYPER- LINKS Honorary degrees Honorary Doctorate Honorary Doctorate Honorary Doctorate University of Stony Brook University, Swansea University, Guelph, Canada United States Wales, UK 2002- 1995 2010 2015 2017 2018 2003 Honorary Doctorate Honorary Doctorate Honorary Doctorate University of of Engineering University of Pretoria, Castile-La Mancha, University of South Africa Spain Melbourne, Australia Achievements 2001 ACM SIGCHI Lifetime Achievement Award Ben ACM SIGCHI is the premier international society President for professionals, academics and students who are interested in human-technology and human-computer interaction (HCI). The CHI Lifetime Achievement Award is the most prestigious award SIGCHI gives.
    [Show full text]
  • List of Readings
    http://wednesdaysmnlove.blogspot.com/2008/10/list-of-readings.html TUESDAY, OCTOBER 7, 2008 List of readings Here are some of the readings I'm hoping to go through during the residency. This is going to be an evolving list. How-To's / Visualization for Beginners 1. “Tactical Technology Collective,” http://www.tacticaltech.org/. 2. John Emerson, “Visualizing Information for Advocacy: An Introduction to Information Design” (Tactical Technology Collective, January 2008), http://www.tacticaltech.org/infodesign. 3. “The Work of Edward Tufte and Graphics Press,” http://www.edwardtufte.com/tufte/index. 4. “Flickr Photo Download: periodic table of visualization methods,” http://flickr.com/photos/colby/352895722/sizes/o/. Books 1. Edward R. Tufte, Beautiful Evidence (Graphics Press, 2006). 2. Edward R. Tufte, Envisioning Information (Graphics Press, 1990). 3. Franco Moretti, Graphs, Maps, Trees, 2005. 4. “Graphs, Maps, Trees - Franco Moretti: an overview of the reviews and critical reactions,” http://www.complete-review.com/reviews/morettif/graphs.htm. 5. Stephen Few, Information Dashboard Design: The Effective Visual Communication of Data (O'Reilly Media, Inc., 2006). 6. Robert L. Harris, Information Graphics: A Comprehensive Illustrated Reference, 1st ed. (Oxford University Press, USA, 2000). 7. Colin Ware, Information Visualization, Second Edition: Perception for Design, 2nd ed. (Morgan Kaufmann, 2004). 8. Ira Greenberg, Processing: Creative Coding and Computational Art, 1st ed. (friends of ED, 2007). 9. Edward R. Tufte, The Visual Display of Quantitative Information, 2nd edition, 2nd ed. (Graphics Press, 2001). 10. Edward R. Tufte, Visual Explanations: Images and Quantities, Evidence and Narrative (Graphics Press, 1997). 11. Paul Mijksenaar, Visual Function: an Introduction to Information Design (010 Publishers, 1997).
    [Show full text]
  • Visualization Viewpoints Pathways for Theoretical Advances in Visualization
    Editor: Visualization Viewpoints Theresa-Marie Rhyne Pathways for Theoretical Advances in Visualization Min Chen Jessie Kennedy University of Oxford Edinburgh Napier University Georges Grinstein Melanie Tory University of Massachusetts Tableau Software Chris R. Johnson University of Utah ore than a decade ago, Chris Johnson Visualization theory is commonly viewed as a re- proposed the “Theory of Visualization” search focus for only a few individual researchers. as one of the top research problems in Its outcomes, perhaps in the form of theorems or Mvisualization.1 Since then, there have been several laws, are perceived as too distant from practice to be theory-focused events, including three workshops useful. Perhaps inspired by well-known theoretical and three panels at IEEE Visualization (VIS) Con- breakthroughs in the history of science, visualiza- ferences. Together, these events have produced a tion researchers may unconsciously have high ex- set of convincing arguments: pectations for the originality, rigor, and significance of the theoretical advancements to be made in a ■ As in all scientific and scholarly subjects, theo- research project or presented in a research paper. retical development in visualization is a neces- On the contrary, although textbooks tend to sary and integral part of the progression of the attribute major breakthroughs to single pioneers subject itself. at specific times and places, in most cases, such ■ Theoretical developments in visualization can breakthroughs generally take years or even decades draw on theoretical advances in many disci- and are usually the product of numerous incremen- plines, including, for example, mathematics, tal developments, including a substantial number computer science, engineering science, psychol- of erroneous solutions suggested by the pioneers ogy, neuroscience, and the social sciences.
    [Show full text]
  • Martin Gardner Papers SC0647
    http://oac.cdlib.org/findaid/ark:/13030/kt6s20356s No online items Guide to the Martin Gardner Papers SC0647 Daniel Hartwig & Jenny Johnson Department of Special Collections and University Archives October 2008 Green Library 557 Escondido Mall Stanford 94305-6064 [email protected] URL: http://library.stanford.edu/spc Note This encoded finding aid is compliant with Stanford EAD Best Practice Guidelines, Version 1.0. Guide to the Martin Gardner SC064712473 1 Papers SC0647 Language of Material: English Contributing Institution: Department of Special Collections and University Archives Title: Martin Gardner papers Creator: Gardner, Martin Identifier/Call Number: SC0647 Identifier/Call Number: 12473 Physical Description: 63.5 Linear Feet Date (inclusive): 1957-1997 Abstract: These papers pertain to his interest in mathematics and consist of files relating to his SCIENTIFIC AMERICAN mathematical games column (1957-1986) and subject files on recreational mathematics. Papers include correspondence, notes, clippings, and articles, with some examples of puzzle toys. Correspondents include Dmitri A. Borgmann, John H. Conway, H. S. M Coxeter, Persi Diaconis, Solomon W Golomb, Richard K.Guy, David A. Klarner, Donald Ervin Knuth, Harry Lindgren, Doris Schattschneider, Jerry Slocum, Charles W.Trigg, Stanislaw M. Ulam, and Samuel Yates. Immediate Source of Acquisition note Gift of Martin Gardner, 2002. Information about Access This collection is open for research. Ownership & Copyright All requests to reproduce, publish, quote from, or otherwise use collection materials must be submitted in writing to the Head of Special Collections and University Archives, Stanford University Libraries, Stanford, California 94304-6064. Consent is given on behalf of Special Collections as the owner of the physical items and is not intended to include or imply permission from the copyright owner.
    [Show full text]