Intro
Preface
Contents
About the Editors
List of Contributors
Part I: Exciting Data and Representation
1: A Multimodal Social Semiotics Perspective on Teaching and Learning Using Biomedical Visualisations
1.1 Introduction
1.2 The Functional Roles, Power, and Positionality of Visual Representations
1.3 A Multimodal Social Semiotics Perspective of Language
1.3.1 Disciplinary Communities as Discourses
1.3.2 Multimodality
1.4 A Multimodal Perspective of Biomedical Visualisation Practices

1.4.1 Affordances and Limitations of Multimodal Biomedical Visualisation Practices
1.4.2 Virtual Learning Environments
1.5 Teaching and Learning Discoursal Fluency in the Biomedical Sciences
1.5.1 Modal Literacy and Discoursal Fluency
1.5.2 Acquiring the Discourse
1.5.3 The Hidden Curriculum
1.5.4 Mobilising the Hidden Curriculum Teaching for Multimodal Visual Fluency
1.5.5 Seeing for Meaning
1.6 Conclusion
1.7 Postscript
References
2: Reasons for Knocking at an Empty House: Visualisation, Representation and Dissemination of Health-Related Public Engagement ...

2.1 Introduction
2.2 Not a Drama Queen: Setting the Scene for the TB Problem in South Africa
2.3 Eh!woza: The Mechanisms and Growth of a Public Engagement Programme
2.3.1 Core Eh!woza Programmes
2.3.2 Situationally Relevant Capacity Development
2.4 We Pulled Ourselves up by the Bootstraps. How Come You Dont́ Have Any Boots?
2.4.1 How the COVID-19 Pandemic Exposed and Exacerbated Existing Inequalities
2.4.1.1 Films Uncovering Fears Associated with a New and Unknown Disease
2.4.1.2 Films Documenting the Pre-existing Housing Insecurity Exacerbated by COVID-19

2.4.1.3 Skills Development While Producing COVID-19 Films Led to Increased Teaching Capacity
2.5 Algorithms and Echo Chambers: Challenges Around Effective Dissemination of Public Engagement Media
2.6 Conclusions
References
3: The Evolution of Scientific Visualisations: A Case Study Approach to Big Data for Varied Audiences
3.1 Introduction
3.2 Visualisation Case Study: Animal Cognition
3.2.1 How Linear Regressions Are Visualised
3.2.1.1 Context: Measuring Brains
3.2.1.2 Position of Visualisations Within the Article
3.2.1.3 Data Point Identification

3.2.1.4 Figure Legends
3.2.2 Known Issues with Brain Size-Body Size Approaches to Intelligence
3.2.3 How Linear Regressions Are Visualised (Continued)
3.2.3.1 Figure Axes Titles
3.2.3.2 Statistics
3.2.3.3 The Use of Colour
3.2.4 Cortical Neuron Count as a Biological Proxy for Intelligence
3.2.5 Points of Interest and Print/Disability Friendly Figures
3.2.5.1 Flagging Points of Interest
3.2.5.2 Print and Disability Friendly Figures
3.2.6 The Evolution of Cognitive Abilities and Brain-Body Mass Visualisations
3.3 Approaching Visualisation Differently