1887
image of Designing participatory data physicalization as cultural connectors
for a Quantified Us
USD
Buy:$35.00 + Taxes

Abstract

Abstract

This paper examines participatory data physicalization as a mode of public engagement. Building on the shift from the to a , the study investigates how data can enable shared meaning-making and intercultural dialogue beyond individual reflection. Culture is understood here as encompassing identity differences, knowledge perspectives, symbolic associations, and lived contexts of interpretation.

Using a Research through Design methodology, nine wellness-focused installations deployed in university campus public spaces revealed five recurring design dimensions: material affordances and metaphors, participation framing, interpretive flexibility and situated meaning, peer visibility and intercultural encounter, and publicness as cultural care.

Findings show that participatory data physicalization can serve as civic infrastructure, where data is not only represented but also co-authored, negotiated, and encountered as a living communal resource. Shared concerns around identity, community, and emotion foster resonance across differences while sustaining plurality and ambiguity. This work contributes to the cultural turn in information design by positioning participatory data engagement as a practice of recognition, solidarity, and civic connection.

Loading

Article metrics loading...

/content/journals/10.1075/idj.25011.she
2026-01-30
2026-02-17
Loading full text...

Full text loading...

References

  1. Ajana, B.
    (2017) Digital health and the biopolitics of the Quantified Self. DIGITAL HEALTH, , 2055207616689509. 10.1177/2055207616689509
    https://doi.org/10.1177/2055207616689509 [Google Scholar]
  2. Beyer, H., & Holtzblatt, K.
    (1999) Contextual design. Interactions, (), –. 10.1145/291224.291229
    https://doi.org/10.1145/291224.291229 [Google Scholar]
  3. Cazacu, S., Panagiotidou, G., Steenberghen, T., & Moere, A. V.
    (2025) Disentangling the Power Dynamics in Participatory Data Physicalisation. 10.48550/ARXIV.2503.13018
    https://doi.org/10.48550/ARXIV.2503.13018 [Google Scholar]
  4. Choe, E. K., Lee, N. B., Lee, B., Pratt, W., & Kientz, J. A.
    (2014) Understanding quantified-selfers’ practices in collecting and exploring personal data. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, –. 10.1145/2556288.2557372
    https://doi.org/10.1145/2556288.2557372 [Google Scholar]
  5. Crawford, K., Lingel, J., & Karppi, T.
    (2015) Our metrics, ourselves: A hundred years of self-tracking from the weight scale to the wrist wearable device. European Journal of Cultural Studies, (), –. 10.1177/1367549415584857
    https://doi.org/10.1177/1367549415584857 [Google Scholar]
  6. Desmet, P., Overbeeke, K., & Tax, S.
    (2001) Designing Products with Added Emotional Value: Development and Appllcation of an Approach for Research through Design. The Design Journal, (), –. 10.2752/146069201789378496
    https://doi.org/10.2752/146069201789378496 [Google Scholar]
  7. D’Ignazio, C., & Klein, L. F.
    (2020) Data feminism. The MIT Press. 10.7551/mitpress/11805.001.0001
    https://doi.org/10.7551/mitpress/11805.001.0001 [Google Scholar]
  8. Dourish, P.
    (2006) Implications for design. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, –. 10.1145/1124772.1124855
    https://doi.org/10.1145/1124772.1124855 [Google Scholar]
  9. Elsden, C., Kirk, D. S., & Durrant, A. C.
    (2016) A Quantified Past: Toward Design for Remembering With Personal Informatics. Human–Computer Interaction, (), –. 10.1080/07370024.2015.1093422
    https://doi.org/10.1080/07370024.2015.1093422 [Google Scholar]
  10. Elsden, C., Kirk, D., Selby, M., & Speed, C.
    (2015) Beyond Personal Informatics: Designing for Experiences with Data. Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems, –. 10.1145/2702613.2702632
    https://doi.org/10.1145/2702613.2702632 [Google Scholar]
  11. Gaver, W.
    (2012) What should we expect from research through design?Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, –. 10.1145/2207676.2208538
    https://doi.org/10.1145/2207676.2208538 [Google Scholar]
  12. Geertz, C., & Darnton, R.
    (2017) The interpretation of cultures: Selected essays (3rd edition). Basic Books.
    [Google Scholar]
  13. Haimson, O. L., & Hoffmann, A. L.
    (2016) Constructing and enforcing “authentic” identity online: Facebook, real names, and non-normative identities. First Monday. 10.5210/fm.v21i6.6791
    https://doi.org/10.5210/fm.v21i6.6791 [Google Scholar]
  14. Heinström, J.
    (2010) From fear to flow: Personality and information interaction. Chandos Pub. 10.1533/9781780630366
    https://doi.org/10.1533/9781780630366 [Google Scholar]
  15. Hofstede, G.
    (2001) Culture’s Consequences: Comparing Values, Behaviors, Institutions and … — Geert Hofstede — Google Books. SAGE Publications.
    [Google Scholar]
  16. Hornecker, E., Hogan, T., Hinrichs, U., & Van Koningsbruggen, R.
    (2024) A Design Vocabulary for Data Physicalization. ACM Transactions on Computer-Human Interaction, (), –. 10.1145/3617366
    https://doi.org/10.1145/3617366 [Google Scholar]
  17. Huron, S., Carpendale, S., Thudt, A., Tang, A., & Mauerer, M.
    (2014) Constructive visualization. Proceedings of the Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques, DIS, –. 10.1145/2598510.2598566
    https://doi.org/10.1145/2598510.2598566 [Google Scholar]
  18. Huron, S., Nagel, T., Oehlberg, L., & Willett, W.
    (Eds.) (2023) Making with data: Physical design and craft in a data-driven world (First edition). CRC Press.
    [Google Scholar]
  19. Jacobson, R. E.
    (Ed.) (2000) Information design (1. MIT Press paperback ed). MIT Press.
    [Google Scholar]
  20. Jansen, Y., Dragicevic, P., Isenberg, P., Alexander, J., Karnik, A., Kildal, J., Subramanian, S., & Hornbæk, K.
    (2015) Opportunities and Challenges for Data Physicalization. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, –. 10.1145/2702123.2702180
    https://doi.org/10.1145/2702123.2702180 [Google Scholar]
  21. Jordan, M., & Pfarr
    (2014, April4). Forget the Quantified Self. We Need to Build the Quantified Us. Wired. https://www.wired.com/2014/04/forget-the-quantified-self-we-need-to-build-the-quantified-us/
    [Google Scholar]
  22. Keck, M., & Probst, K.
    (2024) Getting in Touch: Engaging Public Event Visitors through Participatory Data Physicalization. Proceedings of the 2024 International Conference on Advanced Visual Interfaces, –. 10.1145/3656650.3656736
    https://doi.org/10.1145/3656650.3656736 [Google Scholar]
  23. Kersten — Van Dijk, E. T., & IJsselsteijn, W. A.
    (2016) Design Beyond the Numbers: Sharing, Comparing, Storytelling and the Need for a Quantified Us. Interaction Design and Architecture(s), , –. 10.55612/s‑5002‑029‑006
    https://doi.org/10.55612/s-5002-029-006 [Google Scholar]
  24. Levordashka, A., & Utz, S.
    (2016) Ambient awareness: From random noise to digital closeness in online social networks. Computers in Human Behavior, , –. 10.1016/j.chb.2016.02.037
    https://doi.org/10.1016/j.chb.2016.02.037 [Google Scholar]
  25. Li, I., Dey, A., & Forlizzi, J.
    (2010) A stage-based model of personal informatics systems. Conference on Human Factors in Computing Systems — Proceedings, , –. 10.1145/1753326.1753409
    https://doi.org/10.1145/1753326.1753409 [Google Scholar]
  26. Löwgren, J., & Stolterman, E.
    (2007) Thoughtful interaction design: A design perspective on information technology. The MIT Press.
    [Google Scholar]
  27. Lupton, D.
    (2016) The Quantified Self: A Sociology of Self-Tracking. Polity Press.
    [Google Scholar]
  28. (2020) Data selves: More-than-human perspectives. Polity.
    [Google Scholar]
  29. Marcus, A., & Gould, E. W.
    (2000) Crosscurrents: Cultural dimensions and global Web user-interface design. Interactions, (), –. 10.1145/345190.345238
    https://doi.org/10.1145/345190.345238 [Google Scholar]
  30. Moats, D., & Seaver, N.
    (2019) “You Social Scientists Love Mind Games”: Experimenting in the “divide” between data science and critical algorithm studies. Big Data & Society, (), 2053951719833404. 10.1177/2053951719833404
    https://doi.org/10.1177/2053951719833404 [Google Scholar]
  31. Moore, J., Goffin, P., Wiese, J., & Meyer, M.
    (2022) Exploring the Personal Informatics Analysis Gap: “There’s a Lot of Bacon.” IEEE Transactions on Visualization and Computer Graphics, (), –. 10.1109/TVCG.2021.3114798
    https://doi.org/10.1109/TVCG.2021.3114798 [Google Scholar]
  32. Neff, G., & Nafus, D.
    (2016) Self-Tracking. The MIT Press. 10.7551/mitpress/10421.001.0001
    https://doi.org/10.7551/mitpress/10421.001.0001 [Google Scholar]
  33. Norman, D. A.
    (2023) Design for a Better World: Meaningful, Sustainable, Humanity Centered. MIT Press.
    [Google Scholar]
  34. Offenhuber, D.
    (2019) Data by Proxy — Material Traces as Autographic Visualizations (Version 1). arXiv. 10.48550/ARXIV.1907.05454
    https://doi.org/10.48550/ARXIV.1907.05454 [Google Scholar]
  35. Rooksby, J., Rost, M., Morrison, A., & Chalmers, M.
    (2014) Personal tracking as lived informatics. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, –. 10.1145/2556288.2557039
    https://doi.org/10.1145/2556288.2557039 [Google Scholar]
  36. Ruckenstein, M.
    (2014) Visualized and Interacted Life: Personal Analytics and Engagements with Data Doubles. Societies, (), –. 10.3390/soc4010068
    https://doi.org/10.3390/soc4010068 [Google Scholar]
  37. Ruckenstein, M., & Pantzar, M.
    (2017) Beyond the Quantified Self: Thematic exploration of a dataistic paradigm. New Media & Society, (), –. 10.1177/1461444815609081
    https://doi.org/10.1177/1461444815609081 [Google Scholar]
  38. Shapiro, L.
    (2019) Embodied Cognition (2nd ed.). Routledge. 10.4324/9781315180380
    https://doi.org/10.4324/9781315180380 [Google Scholar]
  39. Sharon, T.
    (2017) Self-Tracking for Health and the Quantified Self: Re-Articulating Autonomy, Solidarity, and Authenticity in an Age of Personalized Healthcare. Philosophy & Technology, (), –. 10.1007/s13347‑016‑0215‑5
    https://doi.org/10.1007/s13347-016-0215-5 [Google Scholar]
  40. Sharon, T., & Zandbergen, D.
    (2017) From data fetishism to quantifying selves: Self-tracking practices and the other values of data. New Media & Society, (), –. 10.1177/1461444816636090
    https://doi.org/10.1177/1461444816636090 [Google Scholar]
  41. Shen, Y., & Scott, D.
    (2025, May12). Tangible Patterns in Material-based Data Visualizations for the Quantified-Self. EKSIG 2025: DATA AS EXPERIENTIAL KNOWLEDGE AND EMBODIED PROCESSES. EKSIG 2025: DATA AS EXPERIENTIAL KNOWLEDGE AND EMBODIED PROCESSES. 10.21606/eksig2025.115
    https://doi.org/10.21606/eksig2025.115 [Google Scholar]
  42. Swan, M.
    (2013) The Quantified Self: Fundamental Disruption in Big Data Science and Biological Discovery. Big Data, (), –. 10.1089/big.2012.0002
    https://doi.org/10.1089/big.2012.0002 [Google Scholar]
  43. Till, C.
    (2014) Exercise as Labour: Quantified Self and the Transformation of Exercise into Labour. Societies, (), –. 10.3390/soc4030446
    https://doi.org/10.3390/soc4030446 [Google Scholar]
  44. Yan, D., Bourgeois, J., Hsu, Y.-C., & Kortuem, G.
    (2025) PAIRcolator: Pair Collaboration for Sensemaking and Reflection on Personal Data. Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, –. 10.1145/3706598.3713332
    https://doi.org/10.1145/3706598.3713332 [Google Scholar]
  45. Zimmerman, J., Stolterman, E., & Forlizzi, J.
    (2010) An analysis and critique of Research through Design: Towards a formalization of a research approach. Proceedings of the 8th ACM Conference on Designing Interactive Systems, –. 10.1145/1858171.1858228
    https://doi.org/10.1145/1858171.1858228 [Google Scholar]
/content/journals/10.1075/idj.25011.she
Loading
/content/journals/10.1075/idj.25011.she
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error