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Cognitive Biases in Visualizations

  • Geoffrey Ellis

Table of contents

  1. Front Matter
    Pages i-xii
  2. Geoffrey Ellis
    Pages 1-10
  3. Bias Definitions, Perspectives and Modeling

    1. Front Matter
      Pages 11-11
    2. André Calero Valdez, Martina Ziefle, Michael Sedlmair
      Pages 13-27
    3. Emily Wall, Leslie M. Blaha, Celeste Lyn Paul, Kristin Cook, Alex Endert
      Pages 29-42
    4. Joseph A. Cottam, Leslie M. Blaha
      Pages 43-58
  4. Cognitive Biases in Action

    1. Front Matter
      Pages 59-59
    2. Michael A. Bedek, Alexander Nussbaumer, Luca Huszar, Dietrich Albert
      Pages 61-73
    3. Dirk Streeb, Min Chen, Daniel A. Keim
      Pages 97-107
  5. Mitigation Strategies

About this book

Introduction

This book brings together the latest research in this new and exciting area of visualization, looking at classifying and modelling cognitive biases, together with user studies which reveal their undesirable impact on human judgement, and demonstrating how visual analytic techniques can provide effective support for mitigating key biases. A comprehensive coverage of this very relevant topic is provided though this collection of extended papers from the successful DECISIVe workshop at IEEE VIS, together with an introduction to cognitive biases and an invited chapter from a leading expert in intelligence analysis.

Cognitive Biases in Visualizations will be of interest to a wide audience from those studying cognitive biases to visualization designers and practitioners. It offers a choice of research frameworks, help with the design of user studies, and proposals for the effective measurement of biases. The impact of human visualization literacy, competence and human cognition on cognitive biases are also examined, as well as the notion of system-induced biases. The well referenced chapters provide an excellent starting point for gaining an awareness of the detrimental effect that some cognitive biases can have on users’ decision-making. Human behavior is complex and we are only just starting to unravel the processes involved and investigate ways in which the computer can assist, however the final section supports the prospect that visual analytics, in particular, can counter some of the more common cognitive errors, which have been proven to be so costly.

Keywords

Visual Analytics Information Visualisation Visual Cognition Decision Science Human Computer Interaction Cognitive Bias

Editors and affiliations

  • Geoffrey Ellis
    • 1
  1. 1.Data Analysis and Visualisation Group, Department of Computer and Information ScienceUniversity of KonstanzKonstanzGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-95831-6
  • Copyright Information Springer Nature Switzerland AG 2018
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-95830-9
  • Online ISBN 978-3-319-95831-6
  • Buy this book on publisher's site