Lesson 16
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The Reader as User

The four waves of HCI and the ideas of Stuart Hall before briefly discussing how video games might fit into the data visualizations conversation.
Lesson Table of Contents

Video

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Lesson outline

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Lesson 16: The Reader as User

Re-imagining the role and power of the reader.

Objective

Explore different conceptual frameworks for understanding the role of the user in data visualization, moving from mechanical interaction to co-creation of meaning.

Outline

This lecture explores the relationship between author and audience through multiple lenses. Understanding different ways of thinking about the role of the user provides perspectives that can be used to understand design. Seeing visualizations from multiple perspectives helps pieces be more successful.

Audiences: Interrogating our lenses

The relationship between author and audience is mediated by the visualization itself.

  • The author makes choices about assumptions, focus, and language.
  • Stuart Hall's Reception Theory describes three ways audiences interpret media:
    • Dominant reading: accepting the intended message as presented.
    • Oppositional reading: rejecting the intended message entirely.
    • Negotiated reading: partially accepting and partially rejecting the message.

Group examines "How Covid Shook the US: Eight Charts That Capture the Last Two Years" from The Guardian through these three reading positions.

HCI Waves

Looking at the evolution of human-computer interaction through a series of waves reflecting different moments of thought.

Wave 1: Ergonomics

The user almost as a robot interpreting through a mechanical system.

  • Focus on physical interaction and ergonomic design.
  • Understanding how users mechanically interact with interfaces.
  • Examples include airplane cockpit design and door affordances.
  • Emphasis on making clear how a data visualization should be used.
  • Fine-tuning mechanisms through which a person "mechanically" interacts.

Example: fuel efficiency standards visualization showing data from 1978 to 1985.

Wave 2: Information and dialogue

The user as engaged in conversation with a series of questions completing a task.

  • Focus on information exchange and task completion.
  • User flows and supporting series of questions or tasks.
  • Multiple coordinated views and interactive exploration.
  • Think about the flow of a user (user loops).
  • Support a series of questions or tasks.
  • Enable dialogue between user and system.

Examples include Windows 98 installation interface, Asana project management, and podcast visualization.

Wave 3: Context

The user as an entity with thought interpreting work through personal and cultural lenses within a social system.

  • Recognition that users exist within social and cultural contexts.
  • Understanding how context interacts with the visualization.
  • Critically interrogating the context and how it may interact with the graphic.
  • Understanding users as thinking beings embedded in cultural and social systems, not just task-completing entities.

Examples include Global Plastics AI Policy Tool.

Wave 4: Unknown

It is still a little unclear what wave 4 will be but let's consider Media for Thought as a possible next step.

Media for thought

Visual representations as tools for thinking. Analysis of Bret Victor (https://vimeo.com/67076984?fl=pl&fe=vl).

Games: The user as co-creator

Games represent a co-created experience between the player and the technology or designer.

  • Users as co-creators of meaning.
  • The work as a way to think new thoughts.
  • Creation of sometimes uniquely individual experiences.
  • Spaces that can be activated by users to see, feel, do, and think new things.
  • Will Wright describes how games enable players to build narratives and experiences that go beyond the designer's original intention.

Reference: Jesse Schell's "The Art of Game Design: A Book of Lenses".

Take Aways

Understanding these different conceptualizations of the user suggests designers should consider multiple perspectives when creating data visualizations.

  • Make it clear how a data visualization should be used and fine-tune the mechanisms through which a person "mechanically" interacts (Wave 1).
  • Think about the flow of a user (user loops) and how we support a series of questions or tasks (Wave 2).
  • Critically interrogate the context of this visualization and how it may interact with the graphic (Wave 3).
  • Create spaces that can be activated by the user to see, feel, do, and think new things (Games and Media for Thought).

Citations

[1] M. Hoekstra, "MacPaint," Geek Technique, 2007. Available: https://www.geektechnique.org/blog/786/mac-paint.html

[2] "Reception Theory," Revision World. Available: https://revisionworld.com/a2-level-level-revision/media-studies-level-revision/reception-theory#google_vignette

[3] J. Tong, "Diagrammatic thinking and audience reading of COVID-19 data visualisations: A UK case study," Convergence, 2024. doi: 10.1177/13548565241309886.

[4] "Stuart Hall," Wikimedia Foundation, 2025. Available: https://en.wikipedia.org/wiki/Stuart_Hall_(cultural_theorist)

[5] E. Berger and A. Witherspoon, "How Covid shook the US: eight charts that capture the last two years," The Guardian, 2022. Available: https://www.theguardian.com/us-news/2022/mar/13/how-covid-shook-the-us-charts-graphs

[6] S. Harrison, P. Sengers, and D. Tatar, "The Three Paradigms of HCI," CHI 2007, 2007.

[7] "Understanding Projects," Asana. Available: https://help.asana.com/s/article/understanding-projects?language=en_US

[8] Schell, Jesse. The Art of Game Design: A Book of Lenses. CRC Press, Taylor & Francis Group, 2020.

[9] Wright, Will. "Spore, Birth of a Game." TED, Ted Conferences, 2007, https://www.ted.com/talks/will_wright_spore_birth_of_a_game.

[10] S. Dale. "Back wooden 4-Panel Door Closed," Unsplash, 2018. Available: https://unsplash.com/photos/black-wooden-4-panel-door-closed-dJycgkec2p0

[11] L. Parren, "Pilot Driving Plane During Daytime," Unsplash, 2018. Available: https://unsplash.com/photos/pilot-driving-plane-during-daytime-S3xxiedz0hE

[12] F Bezies, "Installation MS-Windows 98," Flickr, 2013. Available: https://www.flickr.com/photos/fredbezies/9136730422/

License

This lesson is part of Interactive Data Science and Visualization and is released under a CC-BY-NC 4.0 license.

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Written materials

In addition to the video, you may also:

Exercise

In this exercise, we will visualize the BART ridership dataset. For this activity, please visualize 4 variables.

Note that this project invites you to do geospatial visualization in that stations have latitudes and longitudes. However, it is not required. If you want to go this route, see the geospatial examples on the Sketchingpy examples page. To support you, please see this geojson which has the outline of the Bay Area: bayarea.geojson. If you do geospatial visualization, latitude counts for one variable and longitude counts for another. The geojson is under Public Domain.

Regardless, please use the BART 2024 ridership data I preprocessed for you or the upstream official dataset.

As we move into geospatial work, you may optionally elect to engage AI assistants. If that is of interest, check out the bonus Lesson 26 on using AI.

Note that the Zulip community is not available to this MOOC. Please consider sharing your exercise via social media such as Bluesky with the tag #OpenDataVizSciCourse.

Reading

I have selected a fairly short video for you to review digging deeper into the idea of affordances through bad doors .

Next lecture

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Works cited

This is the works cited from the lecture. Note that additional sources may be used in exercises and other supporting documentation.