1887
Volume 27, Issue 3
  • ISSN 0142-5471
  • E-ISSN: 1569-979X

Abstract

Abstract

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.
Loading

Article metrics loading...

/content/journals/10.1075/idj.22016.rod
2022-12-02
2025-04-28
Loading full text...

Full text loading...

/deliver/fulltext/idj.22016.rod.html?itemId=/content/journals/10.1075/idj.22016.rod&mimeType=html&fmt=ahah

References

  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
    https://doi.org/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]
/content/journals/10.1075/idj.22016.rod
Loading
/content/journals/10.1075/idj.22016.rod
Loading

Data & Media loading...

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