Volume 27, Issue 3
  • ISSN 0142-5471
  • E-ISSN: 1569-979X



The datafication process transforming society enables us to witness the pandemic from a global perspective. This article provides an example of immersive architecture in which coronavirus-related scientific literature was revealed during Ars Electronica 2021. Like a starry sky, a network visualization representing more than 600,000 articles was showcased in the Deep Space 8K theater, where spectators were accompanied in reading insights. The case study of 3D Cartography of COVID-19 illustrates a novel way to present data in public spaces to foster conversations and reflects on how can be addressed in museums.

Available under the CC BY 4.0 license.

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  1. Arnheim, R.
    (1969) Visual thinking. University of California Press.
    [Google Scholar]
  2. Ars Electronica
    Ars Electronica (2021, September9). 3D Cartography of COVID-19 Research. Ars Electronica, a New Digital Deal. https://ars.electronica.art/newdigitaldeal/en/cartography-covid-19-research/
  3. Balazka, D., & Rodighiero, D.
    (2020) Big data and the little big bang: An epistemological (r)evolution. Frontiers in Big Data, 31, 31. 10.3389/fdata.2020.00031
    https://doi.org/10.3389/fdata.2020.00031 [Google Scholar]
  4. Börner, K.
    (2010) Atlas of science: Visualizing what we know. MIT Press.
    [Google Scholar]
  5. Börner, K., Maltese, A., Balliet, R. N., & Heimlich, J.
    (2016) Investigating aspects of data visualization literacy using 20 information visualizations and 273 science museum visitors. Information Visualization, 15(3), 198–213. 10.1177/1473871615594652
    https://doi.org/10.1177/1473871615594652 [Google Scholar]
  6. Bostock, M., Ogievetsky, V., & Heer, J.
    (2011) D3: Data-Driven Documents. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2301–2309. 10.1109/TVCG.2011.185
    https://doi.org/10.1109/TVCG.2011.185 [Google Scholar]
  7. Coleman, N.
    (2021, February21). On the front page, a wall of grief. The New York Times. https://www.nytimes.com/2021/02/21/insider/covid-500k-front-page.html
    [Google Scholar]
  8. Cooper, M.
    (1989) Computers and Design. Design Quarterly, 1421, 1. 10.2307/4091189
    https://doi.org/10.2307/4091189 [Google Scholar]
  9. D’Ignazio, C.
    (2017) Creative data literacy: Bridging the gap between the data-haves and data-have nots. Information Design Journal, 23(1), 6–18. 10.1075/idj.23.1.03dig
    https://doi.org/10.1075/idj.23.1.03dig [Google Scholar]
  10. D’Ignazio, C., & Bhargava, R.
    (2015) Approaches to building big data literacy. Proceedings of the Bloomberg Data for Good Exchange Conference.
    [Google Scholar]
  11. Dondis, D. A.
    (1975) A primer of visual literacy. MIT Press. (Original work published 1973)
    [Google Scholar]
  12. Feng, D., de Vlas, S. J., Fang, L.-Q., Han, X.-N., Zhao, W.-J., Sheng, S., Yang, H., Jia, Z.-W., Richardus, J. H., & Cao, W.-C.
    (2009) The SARS epidemic in mainland China: Bringing together all epidemiological data. Tropical Medicine & International Health, 141, 4–13. 10.1111/j.1365‑3156.2008.02145.x
    https://doi.org/10.1111/j.1365-3156.2008.02145.x [Google Scholar]
  13. Freire, P.
    (2000) Pedagogy of the oppressed (M. Bergman Ramos, Trans.; 30th-anniversary edition ed.). Continuum. (Original work published 1970)
    [Google Scholar]
  14. Galison, P.
    (Director) (2020) Black holes: The edge of all we know [Documentary]. Netflix. https://www.imdb.com/title/tt11863046
    [Google Scholar]
  15. Gray, J., Gerlitz, C., & Bounegru, L.
    (2018) Data infrastructure literacy. Big Data & Society, 5(2), 205395171878631–13. 10.1177/2053951718786316
    https://doi.org/10.1177/2053951718786316 [Google Scholar]
  16. Hocking, J., & Schell, J.
    (2022) Unity in action: Multiplatform game development in C# (Third edition). Manning Publications Co.
    [Google Scholar]
  17. Jandsl, M., & Stocker, G.
    (Eds.) (2021) Ars Electronica 2021. Festival for art, technology and society. Hatje Cantz Verlag.
    [Google Scholar]
  18. Kanas, N.
    (2012) Star maps: History, artistry, and cartography (Second edition). Springer. 10.1007/978‑1‑4614‑0917‑5
    https://doi.org/10.1007/978-1-4614-0917-5 [Google Scholar]
  19. Kaplan, F., & Lenardo, I. di.
    (2017) Big data of the past. Frontiers in Digital Humanities, 41, 769. 10.3389/fdigh.2017.00012
    https://doi.org/10.3389/fdigh.2017.00012 [Google Scholar]
  20. Kenderdine, S.
    (2010) Immersive visualization architectures and situated embodiments of culture and heritage. 14th International Conference Information Visualisation, 408–414. 10.1109/IV.2010.63
    https://doi.org/10.1109/IV.2010.63 [Google Scholar]
  21. Kenderdine, S., Mason, I., & Hibberd, L.
    (2021) Computational archives for experimental museology. 3–18. 10.1007/978‑3‑030‑83647‑4_1
    https://doi.org/10.1007/978-3-030-83647-4_1 [Google Scholar]
  22. Kitchin, R.
    (2014) The data revolution: Big data, open data, data infrastructures and their consequences. SAGE Publications.
    [Google Scholar]
  23. Latour, B.
    (2005) From realpolitik to dingpolitik: Or how to make the things public. InB. Latour & P. Weibel (Eds.), Making things public: Atmospheres of democracy. MIT Press.
    [Google Scholar]
  24. Latour, B., & Weibel, P.
    (Eds.) (2005) Making things public: Atmospheres of democracy. MIT Press.
    [Google Scholar]
  25. Loukissas, Y. A.
    (2019) All data are local: Thinking critically in a data-driven society. https://ieeexplore.ieee.org/document/8709369. 10.7551/mitpress/11543.001.0001
  26. Maaten, L. van der, & Hinton, G.
    (2008) Visualizing data using t-SNE. Journal of Machine Learning Research, 9(86), 2579–2605. jmlr.org/papers/v9/vandermaaten08a.html
    [Google Scholar]
  27. Manning, C. D., & Schütze, H.
    (1999) Foundations of statistical natural language processing. MIT Press.
    [Google Scholar]
  28. Manovich, L.
    (2008) Data visualization as new abstraction and anti-sublime. InB. Hawk, D. M. Rieder, & O. O. Oviedo (Eds.), Small tech: The culture of digital tools. University of Minnesota Press.
    [Google Scholar]
  29. Meirelles, I.
    (2013) Design for information: An introduction to the histories, theories, and best practices behind effective information visualizations. Rockport.
    [Google Scholar]
  30. Moon, C. Y. E., & Rodighiero, D.
    (2020) Mapping as a contemporary instrument for orientation in conferences. Atti Del IX Convegno Annuale AIUCD. 10.5281/zenodo.3611340
    https://doi.org/10.5281/zenodo.3611340 [Google Scholar]
  31. Papaki, E.
    (2020, December10). DARIAH theme call 2020/2021: Meet the winning projects. DARIAH. https://www.dariah.eu/2020/12/10/dariah-theme-call-2020-2021-meet-the-winning-projects/
    [Google Scholar]
  32. Petrovich, E.
    (2020) Science mapping. Encyclopedia of Knowledge Organization. https://www.isko.org/cyclo/science_mapping
    [Google Scholar]
  33. Rigal, A., & Joseph-Goteiner, D.
    (2021) The globalization of an interaction ritual chain: “Clapping for carers” during the conflict against COVID-19. Sociology of Religion, 82(4), 471–493. 10.1093/socrel/srab044
    https://doi.org/10.1093/socrel/srab044 [Google Scholar]
  34. Rodighiero, D., & Romele, A.
    (2022, February4). Reading network diagrams by using contour lines and word clouds. Proceeding of Graphs and Networks in the Humanities. 10.31235/osf.io/3g7bt
    https://doi.org/10.31235/osf.io/3g7bt [Google Scholar]
  35. Rodighiero, D., Wandl-Vogt, E., & Carsenat, E.
    (2021) Making visible the invisible work of scientists during the COVID-19 pandemic. Visual Culture Studies, 21, 143–165. 10.31235/osf.io/m4uht
    https://doi.org/10.31235/osf.io/m4uht [Google Scholar]
  36. (2022) A visual translation of the pandemic. Leonardo, 55(3), 297–303. 10.1162/leon_a_02203
    https://doi.org/10.1162/leon_a_02203 [Google Scholar]
  37. Sick-Leitner, M.
    (2015, November8). Deep Space 8K: the next generation. Ars Electronica Blog. https://ars.electronica.art/aeblog/en/2015/08/11/deep-space-8k/
    [Google Scholar]
  38. Sismondo, S.
    (2010) An introduction to science and technology studies (Second edition). Wiley-Blackwell. (Original work published 2004)
    [Google Scholar]
  39. Van Der Spuy, R.
    (2015) Learn Pixi.js. Apress. 10.1007/978‑1‑4842‑1094‑9
    https://doi.org/10.1007/978-1-4842-1094-9 [Google Scholar]
  40. Van Dijck, J.
    (2014) Datafication, dataism and dataveillance: Big data between scientific paradigm and ideology. Surveillance & Society, 12(2), 197–208. 10.24908/ss.v12i2.4776
    https://doi.org/10.24908/ss.v12i2.4776 [Google Scholar]
  41. Vanderplas, J. T.
    (2016) Python data science handbook: Essential tools for working with data. O’Reilly Media.
    [Google Scholar]
  42. Wang, L. L., Lo, K., Chandrasekhar, Y., Reas, R., Yang, J., Burdick, D., Eide, D., Funk, K., Katsis, Y., Kinney, R., Li, Y., Liu, Z., Merrill, W., Mooney, P., Murdick, D., Rishi, D., Sheehan, J., Shen, Z., Stilson, B., … Kohlmeier, S.
    (2020) CORD-19: The COVID-19 Open Research Dataset. Proceedings of the Workshop on NLP for COVID-19 at ACL 2020. https://arxiv.org/abs/2004.10706
    [Google Scholar]
  43. Wilkinson, M. D., Dumontier, M., Aalbersberg, Ij. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., Santos, L. B. da S., Bourne, P. E., Bouwman, J., Brookes, A. J., Clark, T., Crosas, M., Dillo, I., Dumon, O., Edmunds, S., Evelo, C. T., Finkers, R., … Mons, B.
    (2016) The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3(1), e1002295–10. 10.1038/sdata.2016.18
    https://doi.org/10.1038/sdata.2016.18 [Google Scholar]

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  • Article Type: Research Article
Keyword(s): Ars Electronica; COVID-19; data literacy; dialogic practice; visual literacy
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