Introductory description

In this module students will learn about the opportunities and challenges opened up by the growing role of data visualisation in contemporary science, culture and public policy. It will introduce key concepts for understanding the importance of data visualisation as a form of knowledge, communication, persuasion and engagement as well as state-of-the-art approaches to using data visualisation as a way of knowing and intervening in the world and in society - such as ethnography, design research and inventive methods. Student learning will be supported through the exploration of real-world examples: by reviewing paradigmatic cases, such as the Blue Marble (images of planet earth as seen from space), topographic maps of disputed territories, and visualisations of air pollution, students will learn to reflect on the wider impact of data visualisation on public understanding, cultural awareness, policy and decision-making and societal change.

The module consists of two parts, with the first part offering lectures and seminars introducing guiding ideas from social, cultural and political theory, science and technology studies, as well as digital and environmental humanities on the key importance of visualisation in science, culture and democracy. The second part will focus on the introduction of specific methodological approaches to the use of data visualisation in social, creative, participatory and policy research. Throughout the module, and linking the two parts, students will be engaging with cultural, social and public issues through real-world examples of data visualisation. The module then combines lectures, seminars and assignment-based work, which together will equip students to recognise, analyse and appreciate the wider affordances of data visualisation for knowledge, intervention and change.

To sum up, the module will introduce concepts, methods and empirical cases key to understanding the affordances, power and limitations of data visualisation in science, culture, and public policy, with student engagement with the empirical cases providing continuity throughout the module: supported by group assignments, students will be exploring both concepts and methods by applying and thinking these through in relation to the cases. This will form the basis of the group presentations in the last week.

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

The module will start with an overview of key issues raised by data visualisation in contemporary science, culture and public policy:

The next 4 weeks (Part 1) will review key concepts and guiding ideas developed in 20th Century social, cultural and political theory, science studies, environmental humanities, digital humanities and artistic practice to understand the privileged role of visualisation in contemporary society and culture: the primacy of vision in contemporary science, art and democracy; visualisation as modus operandi in technoscience; the rise of visual culture in the 20th Century; visualisation as device for public communication, activism and engagement with science, nature, society and culture.

After reading week, sessions will introduce state-of-the-art approaches to using data visualisation in research, intervention and engagement: visualisation as ethnography, data visualisation as participatory method, and visual methods in public policy, decision-making and advocacy (Part 2).

This will be supported by group work on a small project, in which students will review and explore empirical cases of the use of data visualisation in science, culture and public policy in the light of key concepts and approaches introduced throughout the module. Case studies will include several of the following: Snow’s Cholera Map, the Blue Marble (Earth seen from space), Maps of disputed territories, Visualisations of Air Pollution, Tufte’s Challenger Disaster Critique, the Hockey stick visualisation of global temperatures, and Covid Maps.

Week 1: Introduction: Data, Visualisation & Culture Now
Week 2: Vision as Knowledge, Culture and Democracy
Week 3: Social Studies of Visualisation: Science, Power, Intervention
Week 4: Visualisation across Culture/Nature
Week 5: Data Visualisation’s Publics and Counter-Publics
Week 6: READING WEEK
Week 7: Data Visualisation and Ethnography
Week 8: Data Visualisation as Engagement
Week 9: Data Visualisation in Public Policy, Decision-making and Advocacy
Week 10: Module Review and Final Presentations

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate a conceptual understanding of the importance of data visualisation as an instrument of inquiry, advocacy, decision-making, and engagement in contemporary science, culture and public policy.
• Evaluate the usefulness of different methodologies for using data visualisation in the creation of knowledge, the facilitatation of participation, to support decision-making and enable social and cultural change.
• Demonstrate an empirical understanding of how data visualisation has enabled new knowledge, engagement, awareness and change through the discussion of real-world examples.
• Provide an account of the role of data visualisation in the development of innovative forms of inquiry, policymaking, intervention and engagement, and of the potential of data visualisation to transform the relationship between science, culture and democracy.

Indicative reading list

Arnheim, R. (1980). A plea for visual thinking. Critical Inquiry, 6(3), 489-497.

Calvillo, N. (2019). Digital Visualizations for Thinking with the Environment. Digital STS: A Field Guide for Science & Technology Studies, 61.

Dávila, P. (2019) Diagrams of Power, Eindhoven: Onomatopee 168,

Drucker, J. (2020) Visualization and Interpretation: Humanistic Approaches to Display, Cambridge: MIT Press.

Engebretsen, M. and Kennedy, H. (2020) Data Visualization in Society, Amsterdam: Amsterdam University Press

Ezrahi, Y. (2012). Imagined democracies: Necessary political fictions. Cambridge University Press.

Guggenheim, M. (2015). The media of sociology: tight or loose translations? The British journal of sociology, 66(2), 345-372.

Hall, P. A. (2014). Counter-mapping and globalism. Design in the borderlands. Abingdon: Routledge, 132-50.

Haraway, D. (1984). Teddy bear patriarchy: Taxidermy in the garden of Eden, New York City, 1908-1936. Social Text, (11), 20-64.

Healy, K. (2018). Data visualization: a practical introduction. Princeton University Press.

d’Ignazio, C., & Klein, L. F. (2016). Feminist data visualization. Workshop on Visualization for the Digital Humanities (VIS4DH), Baltimore. IEEE..

Jay, M., & Ramaswamy, S. (Eds.). (2014). Empires of vision: A reader. Duke University Press.

Kennedy, H., & Allen, W. (2016). Data visualisation as an emerging tool for online research. The Sage handbook of online research methods, 307-326.

Kennedy, H and Hill, RL (2018) The Feeling of Numbers: emotions in everyday engagements with data and their visualisation. Sociology, 52 (4). pp. 830-848.

Kimbell, L., & Bailey, J. (2017). Prototyping and the new spirit of policy-making. CoDesign, 13(3), 214-226.

Kimbell, L. (2015). Applying design approaches to policy making: discovering policy lab. Discussion Paper. University of Brighton,

Toscano, A., & Kinkle, J. (2015). Cartographies of the Absolute. John Hunt Publishing.

Kurgan, L. (2013) Close up at a distance, New York: Zone books

Latour, B. (1986) Visualisation and Cognition: Drawing Things Together» in H. Kuklick (editor) Knowledge and Society Studies in the Sociology of Culture Past and Present, Jai Press vol. 6, pp. 1-40

Marres, N., & de Rijcke, S. (2020). From indicators to indicating interdisciplinarity: A participatory mapping methodology for research communities in-the-making. Quantitative Science Studies, 1(3), 1041-1055.

Masud, L., Valsecchi, F., Ciuccarelli, P., Ricci, D., & Caviglia, G. (2010, July). From data to knowledge-visualizations as transformation processes within the data-information-knowledge continuum. In 2010 14th international conference information visualisation (pp. 445-449). IEEE.

Mitchell, W. T. (1995). Picture theory: Essays on verbal and visual representation. Chicago: University of Chicago Press.

Mitchell, C., De Lange, N., & Moletsane, R. (2017). Participatory visual methodologies: Social change, community and policy. London and New York: Sage.

Moats, D and J. Perriam (2017). ‘How Does it Feel to be Visualized: Redistributing Ethics’ in Internet Research Ethics for the Social Age: New Cases and Challenges. Zimmer, M and Kinder-Kurlanda, K eds, New York: Peter Lang

Niederer, S. and G. Colombo (2019):. "Visual methodologies for networked images: Designing visualizations for collaborative research, cross-platform analysis, and public participation." 40-67.

Pink, S. (2021). Doing visual ethnography. New York and London: Sage.

Pitkin, H. F. (1967). The concept of representation (Vol. 75). Univ of California Press.

Ricci, D. (2010). Seeing what they are saying: Diagrams for socio-technical controversies.

Rorty, R. (1979). Philosophy and the Mirror of Nature. Princeton: Princeton university press.

Rose, G. (2016). Visual methodologies: An introduction to researching with visual materials. New York and London: Sage.

Scott, J. C. (2020). Seeing like a state: How certain schemes to improve the human condition have failed. New Haven: Yale University Press.

Wolin, S. S. (2016). Politics and Vision: Continuity and Innovation in Western Political Thought-Expanded Edition. Princeton: Princeton University Press.

Interdisciplinary

Approaches visualisation from an interdisciplinary perspective through state-of-the-art approaches to using data visualisation as a way of knowing and intervening in the world - such as visual sociology, inventive methods and design research.

Subject specific skills

• Ability to discuss the role of visualisations in science, culture and public policy
• Ability to apply abstract concepts to historical and contemporary uses of data visualisation
• Ability to extend from historical case studies of data visualisation to contemporary challenges
• Ability to describe the contexts of application of visualisation as a research methodology and as a form of public engagement
• Understand and appreciate future professional challenges relating to the use of visualisation in applied contexts in society
• Knowledge of state-of-the-art applications of the use of data visualisation in research and engagement

Transferable skills

• Think critically, creatively and independently in relation to a topic provided each week;
• Make productive links between theoretical ideas, methods and practical phenomena;
• Demonstrate written and oral communication skills: to articulate arguments orally and through well-argued essay writing, supported by wide reading and research.
• Participate in class discussions and collaborative group work