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New Challenges for Data Design.

By: Material type: TextPublisher: London : Springer London, Limited, 2015Copyright date: ©2015Edition: 1st edDescription: 1 online resource (441 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781447165965
Subject(s): Genre/Form: DDC classification:
  • 005.743
Online resources:
Contents:
Intro -- Preface -- Acknowledgments -- Contents -- Contributors -- Part IDepicting Data in Graphical Form -- 1 Show, Don't Tell -- Abstract -- 1.1 Between Worlds -- 1.2 My Life in Data -- 1.3 Money Troubles -- 1.4 A Story to Behold -- 1.5 Playing with Data -- 1.6 Shifts in Power -- 1.7 A Familiar Tune -- 1.8 The Missing Link -- References -- 2 Giving Shape to Data -- Abstract -- 2.1 Introduction -- 2.2 Designing Data -- 2.2.1 Data Relationship Dynamics -- 2.2.1.1 Action and Perception -- 2.2.1.2 Enaction and Environment -- 2.3 Giving Shape and Meaning to B̀̀ig Data'' -- 2.3.1 The Appearance and Shape of Massive Datasets -- 2.3.1.1 Perception and Sensation -- 2.3.1.2 The Role of Aesthetic Perception -- 2.3.2 Moving Toward Concrete Data Design -- 2.3.2.1 Clarity is Aesthetics -- 2.3.2.2 Data Gestaltung -- 2.4 Conclusion -- Part IIVisually Representingand Explaining Data -- 3 The New Aesthetic of Data Narrative -- Abstract -- 3.1 La Lettura, Visual Data -- 3.1.1 Story! Catchy, and Layered -- 3.1.2 Constraints, as a Resource -- 3.1.3 Visual Models and Metaphors: Pushing Forward, Always -- 3.1.4 And, the Readers? -- 3.2 A Method from Practice -- 3.3 Which Came First, the Question or the Dataset (or the Visualization Itself)? -- 3.3.1 Visual-driven Approach -- 3.3.1.1 Ẁ̀hy Don't We Visualize This: Like This---?'' -- Divergent Times: Atlases of World Histories -- 3.3.2 Data-driven Approach -- 3.3.2.1 Painters in the Making -- 3.4 The Importance of Inspiration from Different Contexts -- 3.4.1 Before I Think I Draw -- 3.4.2 Theory in Practice -- 3.4.2.1 The Brain Drain and a Visit to Moma's Inventing Abstraction Exhibition -- 3.4.2.2 Nobel Prizes and Laureates and John Cage -- 3.5 Conclusion -- Credit and Acknowledgments -- References -- 4 A Process Dedicated to Cognition and Memory -- Abstract -- 4.1 Introduction -- 4.2 Esthetics as a Tool.
4.3 Imagery and Cognition -- 4.4 Case Study: Invisible Montpellier -- 4.4.1 Approach -- 4.4.2 Challenges -- 4.4.3 Process of Visualizing the Data -- 4.4.4 Iteration -- 4.4.5 Final Result -- References -- 5 Graphics Lies, Misleading Visuals -- Abstract -- 5.1 Introduction -- 5.2 Becoming a Good Liar -- 5.2.1 Hiding Relevant Data to Highlight What Benefits Us -- 5.2.2 Displaying Too Much Data to Obscure Reality -- 5.2.3 Using Graphic Forms in Inappropriate Ways (Distorting the Data) -- 5.3 The Ignorance of Evidence-Driven Communicators -- 5.4 Conclusion: Fighting Noise with Knowledge -- References -- Part IIIMapping and Visualizing Data -- 6 atNight: Nocturnal Landscapes and Invisible Networks -- Abstract -- 6.1 An Approach to the Intangible Aspects of the City -- 6.1.1 The Agency of Mapping -- 6.2 Nocturnal Landscapes: Uncharted Territories Approach -- 6.3 Urban Analysis -- 6.3.1 Data and Workflow -- 6.3.2 Cartographies of Invisible Networks -- 6.3.2.1 Visual Structure -- Territorial Framework and Identity -- Night-Time and Daytime -- Visible City, Living City -- 6.3.2.2 Mobility Patterns -- Activity and Usage -- 6.4 Conclusion -- References -- 7 Visualizing Ambiguity in an Era of Data Abundance and Very Large Software Systems -- Abstract -- 7.1 Introduction -- 7.2 Asking the Right Question Is Half the Answer -- 7.3 Reducing Ambiguity -- 7.4 Making the Takeaways More Meaningful -- 7.5 Choosing the Right Metaphor -- 7.6 Displaying the Results -- 7.7 An Opportunity Worth Capitalizing On -- 7.8 Forthcoming Challenges -- References -- Part IVInteracting with Data -- 8 Living Networks -- Abstract -- 8.1 Networks Are Dynamic -- 8.1.1 Dynamic Systems -- 8.1.2 Dynamic Networks -- 8.2 Visualizing Networks -- 8.2.1 Lostalgic -- 8.2.2 Newk -- 8.2.3 SYM -- 8.3 Conclusion -- References -- 9 Epiphanies Through Interactions with Data -- Abstract.
9.1 Imagining Data -- 9.2 On Disbelief -- 9.2.1 Bias -- 9.2.2 Skepticism -- 9.3 Revealing Truth -- 9.3.1 Truth in Numbers -- 9.3.2 Respect -- 9.3.3 Raw Data -- 9.4 Interactive Data -- 9.5 Journeys, not Stories -- 9.6 Epiphanies -- 9.7 Summary -- References -- Part VExploring and Manipulating Data -- 10 Sketching with Data -- Abstract -- 10.1 Introduction -- 10.1.1 A Vision that Became Reality -- 10.1.2 Societal Implications -- 10.1.3 Methodological Implications -- 10.1.4 A Multidisciplinary Process -- 10.2 The Practice of Sketching -- 10.3 The Tools -- 10.3.1 Redefining Work with Data -- 10.3.2 Reducing the Barriers of Data Manipulation -- 10.3.3 Creating a Coherent Language -- 10.3.4 Taking Advantage of an Ecosystem of Great Tools -- 10.4 The Virtues of Sketching with Data -- 10.4.1 Share a Common Language -- 10.4.2 Qualify the Results -- 10.4.3 Innovate with Data -- 10.4.3.1 Checking the Sanity of the Data -- 10.4.3.2 Defining a Clear Focus -- 10.5 Conclusions -- References -- 11 Information Visualizations and Interfaces in the Humanities -- Abstract -- 11.1 The Digital and the Humanities -- 11.2 Designing (in) the Digital Humanities -- 11.3 The Nature of Data -- 11.4 Visualizations and Interfaces -- 11.5 Bringing Design Practices in the Humanities -- 11.6 Conclusions -- References -- Part VITranslating and HandlingLarge Datasets -- 12 Big Data, Big Stories -- Abstract -- 12.1 Big Data -- 12.2 Representing Big Data -- 12.3 Case Study: The Deleted City -- 12.3.1 The Deleted City, a Digital Archeology -- 12.3.1.1 Geocities -- 12.3.1.2 The Rise and Fall -- 12.3.1.3 The Archive -- 12.3.1.4 The Installation -- 12.3.1.5 Perspective -- 12.4 Conclusion -- 13 Dispositif Mapping -- Abstract -- 13.1 Introduction -- 13.1.1 Wicked Problems -- 13.1.2 Dispositif -- 13.1.3 Mapping the European Debt Crisis -- 13.1.4 Data Propaganda Explained by the Dispositif Map.
13.2 Mapping Influence -- 13.2.1 Germany's Shareholder Structure -- 13.2.2 Mapping Lobbying -- 13.3 Conclusion -- References -- Part VIIExperiencing Data ThroughMultiple Modalities -- 14 Sustainability: Visualized -- Abstract -- 14.1 Introduction -- 14.2 What Is Sustainability? And How Does It Relate to Info Design? -- 14.3 [Info] Designing for Sustainability -- 14.3.1 Challenges: Communicating Sustainability -- 14.3.1.1 Lack of C̀̀ontext Connection'' -- 14.3.1.2 Data Deluge -- 14.3.1.3 Being Human -- 14.4 Opportunities -- 14.4.1 Visual Storytelling -- 14.4.2 Systems Thinking and Communicating Life Cycle -- 14.4.3 In-context Connections -- 14.4.4 Bridging the Gap: Science and Emotion -- 14.4.5 Key Practices -- 14.4.6 Start with the Individual -- 14.4.7 Involve Emotions -- 14.4.8 Present Positively -- 14.4.9 Layer Information -- 14.4.10 Audiences Make Their Own Decisions -- 14.4.11 Enable Interaction -- 14.4.12 Provide Access to Supporting Data -- 14.5 Data Design for Sustainability---and Beyond -- References -- 15 Encoding Memories -- Abstract -- 15.1 Meshu -- 15.1.1 The Balkanization of Personal Data -- 15.1.2 Visualizing Personal Histories -- 15.1.3 Fractured Memories -- 15.1.4 Meshu's Matter Battle -- 15.1.5 Readymades as Handholds -- 15.1.6 The Shock of Launch -- 15.1.7 A Living Project -- 15.1.8 Hiding in Plain Sight -- 16 Changing Minds to Changing the World -- Abstract -- 16.1 Get Started -- 16.2 Common Ground -- 16.3 Mapping the Field -- 16.3.1 Avenues of Practice -- 16.3.2 Contexts -- 16.3.3 Media -- 16.3.4 Conceptual Structures -- 16.3.5 Goals -- 16.4 Making Meaning from All This -- 16.5 Common Elements -- 16.6 The Value of Interdisciplinary Practice -- 16.7 Future Challenges -- 16.8 Nature of Tools -- References -- Part VIIIInterviews -- 17 Beauty in Data -- Andy Cameron's Interview with Jonathan Harris -- 18 Tracing My Life.
David Bihanic's Interview with Nicholas Felton -- 19 Multidisciplinary Design in the Age of Data -- David Bihanic's Interview with Stephan Thiel, Steffen Fiedler and Jonas Loh -- 20 Designing for Small and Large Datasets -- David Bihanic's Interview with Jan Willem Tulp -- 21 Process and Progress: A Practitioner's Perspective on the How, What and Why of Data Visualization -- David Bihanic's Interview with Moritz Stefaner -- 22 The Art &amp -- Craft of Portraying Data -- David Bihanic's Interview with Stefanie Posavec -- 23 From Experience to Understanding -- David Bihanic's Interview with Benjamin Wiederkehr -- Author Index.
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Intro -- Preface -- Acknowledgments -- Contents -- Contributors -- Part IDepicting Data in Graphical Form -- 1 Show, Don't Tell -- Abstract -- 1.1 Between Worlds -- 1.2 My Life in Data -- 1.3 Money Troubles -- 1.4 A Story to Behold -- 1.5 Playing with Data -- 1.6 Shifts in Power -- 1.7 A Familiar Tune -- 1.8 The Missing Link -- References -- 2 Giving Shape to Data -- Abstract -- 2.1 Introduction -- 2.2 Designing Data -- 2.2.1 Data Relationship Dynamics -- 2.2.1.1 Action and Perception -- 2.2.1.2 Enaction and Environment -- 2.3 Giving Shape and Meaning to B̀̀ig Data'' -- 2.3.1 The Appearance and Shape of Massive Datasets -- 2.3.1.1 Perception and Sensation -- 2.3.1.2 The Role of Aesthetic Perception -- 2.3.2 Moving Toward Concrete Data Design -- 2.3.2.1 Clarity is Aesthetics -- 2.3.2.2 Data Gestaltung -- 2.4 Conclusion -- Part IIVisually Representingand Explaining Data -- 3 The New Aesthetic of Data Narrative -- Abstract -- 3.1 La Lettura, Visual Data -- 3.1.1 Story! Catchy, and Layered -- 3.1.2 Constraints, as a Resource -- 3.1.3 Visual Models and Metaphors: Pushing Forward, Always -- 3.1.4 And, the Readers? -- 3.2 A Method from Practice -- 3.3 Which Came First, the Question or the Dataset (or the Visualization Itself)? -- 3.3.1 Visual-driven Approach -- 3.3.1.1 Ẁ̀hy Don't We Visualize This: Like This---?'' -- Divergent Times: Atlases of World Histories -- 3.3.2 Data-driven Approach -- 3.3.2.1 Painters in the Making -- 3.4 The Importance of Inspiration from Different Contexts -- 3.4.1 Before I Think I Draw -- 3.4.2 Theory in Practice -- 3.4.2.1 The Brain Drain and a Visit to Moma's Inventing Abstraction Exhibition -- 3.4.2.2 Nobel Prizes and Laureates and John Cage -- 3.5 Conclusion -- Credit and Acknowledgments -- References -- 4 A Process Dedicated to Cognition and Memory -- Abstract -- 4.1 Introduction -- 4.2 Esthetics as a Tool.

4.3 Imagery and Cognition -- 4.4 Case Study: Invisible Montpellier -- 4.4.1 Approach -- 4.4.2 Challenges -- 4.4.3 Process of Visualizing the Data -- 4.4.4 Iteration -- 4.4.5 Final Result -- References -- 5 Graphics Lies, Misleading Visuals -- Abstract -- 5.1 Introduction -- 5.2 Becoming a Good Liar -- 5.2.1 Hiding Relevant Data to Highlight What Benefits Us -- 5.2.2 Displaying Too Much Data to Obscure Reality -- 5.2.3 Using Graphic Forms in Inappropriate Ways (Distorting the Data) -- 5.3 The Ignorance of Evidence-Driven Communicators -- 5.4 Conclusion: Fighting Noise with Knowledge -- References -- Part IIIMapping and Visualizing Data -- 6 atNight: Nocturnal Landscapes and Invisible Networks -- Abstract -- 6.1 An Approach to the Intangible Aspects of the City -- 6.1.1 The Agency of Mapping -- 6.2 Nocturnal Landscapes: Uncharted Territories Approach -- 6.3 Urban Analysis -- 6.3.1 Data and Workflow -- 6.3.2 Cartographies of Invisible Networks -- 6.3.2.1 Visual Structure -- Territorial Framework and Identity -- Night-Time and Daytime -- Visible City, Living City -- 6.3.2.2 Mobility Patterns -- Activity and Usage -- 6.4 Conclusion -- References -- 7 Visualizing Ambiguity in an Era of Data Abundance and Very Large Software Systems -- Abstract -- 7.1 Introduction -- 7.2 Asking the Right Question Is Half the Answer -- 7.3 Reducing Ambiguity -- 7.4 Making the Takeaways More Meaningful -- 7.5 Choosing the Right Metaphor -- 7.6 Displaying the Results -- 7.7 An Opportunity Worth Capitalizing On -- 7.8 Forthcoming Challenges -- References -- Part IVInteracting with Data -- 8 Living Networks -- Abstract -- 8.1 Networks Are Dynamic -- 8.1.1 Dynamic Systems -- 8.1.2 Dynamic Networks -- 8.2 Visualizing Networks -- 8.2.1 Lostalgic -- 8.2.2 Newk -- 8.2.3 SYM -- 8.3 Conclusion -- References -- 9 Epiphanies Through Interactions with Data -- Abstract.

9.1 Imagining Data -- 9.2 On Disbelief -- 9.2.1 Bias -- 9.2.2 Skepticism -- 9.3 Revealing Truth -- 9.3.1 Truth in Numbers -- 9.3.2 Respect -- 9.3.3 Raw Data -- 9.4 Interactive Data -- 9.5 Journeys, not Stories -- 9.6 Epiphanies -- 9.7 Summary -- References -- Part VExploring and Manipulating Data -- 10 Sketching with Data -- Abstract -- 10.1 Introduction -- 10.1.1 A Vision that Became Reality -- 10.1.2 Societal Implications -- 10.1.3 Methodological Implications -- 10.1.4 A Multidisciplinary Process -- 10.2 The Practice of Sketching -- 10.3 The Tools -- 10.3.1 Redefining Work with Data -- 10.3.2 Reducing the Barriers of Data Manipulation -- 10.3.3 Creating a Coherent Language -- 10.3.4 Taking Advantage of an Ecosystem of Great Tools -- 10.4 The Virtues of Sketching with Data -- 10.4.1 Share a Common Language -- 10.4.2 Qualify the Results -- 10.4.3 Innovate with Data -- 10.4.3.1 Checking the Sanity of the Data -- 10.4.3.2 Defining a Clear Focus -- 10.5 Conclusions -- References -- 11 Information Visualizations and Interfaces in the Humanities -- Abstract -- 11.1 The Digital and the Humanities -- 11.2 Designing (in) the Digital Humanities -- 11.3 The Nature of Data -- 11.4 Visualizations and Interfaces -- 11.5 Bringing Design Practices in the Humanities -- 11.6 Conclusions -- References -- Part VITranslating and HandlingLarge Datasets -- 12 Big Data, Big Stories -- Abstract -- 12.1 Big Data -- 12.2 Representing Big Data -- 12.3 Case Study: The Deleted City -- 12.3.1 The Deleted City, a Digital Archeology -- 12.3.1.1 Geocities -- 12.3.1.2 The Rise and Fall -- 12.3.1.3 The Archive -- 12.3.1.4 The Installation -- 12.3.1.5 Perspective -- 12.4 Conclusion -- 13 Dispositif Mapping -- Abstract -- 13.1 Introduction -- 13.1.1 Wicked Problems -- 13.1.2 Dispositif -- 13.1.3 Mapping the European Debt Crisis -- 13.1.4 Data Propaganda Explained by the Dispositif Map.

13.2 Mapping Influence -- 13.2.1 Germany's Shareholder Structure -- 13.2.2 Mapping Lobbying -- 13.3 Conclusion -- References -- Part VIIExperiencing Data ThroughMultiple Modalities -- 14 Sustainability: Visualized -- Abstract -- 14.1 Introduction -- 14.2 What Is Sustainability? And How Does It Relate to Info Design? -- 14.3 [Info] Designing for Sustainability -- 14.3.1 Challenges: Communicating Sustainability -- 14.3.1.1 Lack of C̀̀ontext Connection'' -- 14.3.1.2 Data Deluge -- 14.3.1.3 Being Human -- 14.4 Opportunities -- 14.4.1 Visual Storytelling -- 14.4.2 Systems Thinking and Communicating Life Cycle -- 14.4.3 In-context Connections -- 14.4.4 Bridging the Gap: Science and Emotion -- 14.4.5 Key Practices -- 14.4.6 Start with the Individual -- 14.4.7 Involve Emotions -- 14.4.8 Present Positively -- 14.4.9 Layer Information -- 14.4.10 Audiences Make Their Own Decisions -- 14.4.11 Enable Interaction -- 14.4.12 Provide Access to Supporting Data -- 14.5 Data Design for Sustainability---and Beyond -- References -- 15 Encoding Memories -- Abstract -- 15.1 Meshu -- 15.1.1 The Balkanization of Personal Data -- 15.1.2 Visualizing Personal Histories -- 15.1.3 Fractured Memories -- 15.1.4 Meshu's Matter Battle -- 15.1.5 Readymades as Handholds -- 15.1.6 The Shock of Launch -- 15.1.7 A Living Project -- 15.1.8 Hiding in Plain Sight -- 16 Changing Minds to Changing the World -- Abstract -- 16.1 Get Started -- 16.2 Common Ground -- 16.3 Mapping the Field -- 16.3.1 Avenues of Practice -- 16.3.2 Contexts -- 16.3.3 Media -- 16.3.4 Conceptual Structures -- 16.3.5 Goals -- 16.4 Making Meaning from All This -- 16.5 Common Elements -- 16.6 The Value of Interdisciplinary Practice -- 16.7 Future Challenges -- 16.8 Nature of Tools -- References -- Part VIIIInterviews -- 17 Beauty in Data -- Andy Cameron's Interview with Jonathan Harris -- 18 Tracing My Life.

David Bihanic's Interview with Nicholas Felton -- 19 Multidisciplinary Design in the Age of Data -- David Bihanic's Interview with Stephan Thiel, Steffen Fiedler and Jonas Loh -- 20 Designing for Small and Large Datasets -- David Bihanic's Interview with Jan Willem Tulp -- 21 Process and Progress: A Practitioner's Perspective on the How, What and Why of Data Visualization -- David Bihanic's Interview with Moritz Stefaner -- 22 The Art &amp -- Craft of Portraying Data -- David Bihanic's Interview with Stefanie Posavec -- 23 From Experience to Understanding -- David Bihanic's Interview with Benjamin Wiederkehr -- Author Index.

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