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Visualizing COVID-19:: an analytical model to understand and compose continuously evolving data visualization projects
University of Tartu, Estonia.
Malmö University, Data Society. Malmö University, Faculty of Culture and Society (KS), School of Arts and Communication (K3). Malmö University.ORCID iD: 0000-0003-2122-951x
Masaryk University, Czech Republic.
2022 (English)In: Medialni studia / Media studies, ISSN 2464-4846, Vol. 16, no 1, p. 65-91, article id 04Article in journal (Refereed) Published
Abstract [en]

The increased demand for information during the Covid-19 pandemic inspired projects todescribe the pandemic’s progress via data visualization. Critically analyzing the publisheddata visualization projects (DVPs) contributes to establishing a framework that supportsboth understanding and composing DVPs that evolve over time. Drawing upon constructedgrounded theory, we develop an analytical model for creating DVPs in a journalistic or public communication context. For our analysis, we selected Covid-19 public service media DVPsin the United Kingdom, Norway, Sweden and Estonia as well as DVPs created by global andlocal data activists. The analysis of these examples provides an understanding of (1) theimplied agency standing of the authors of the visualizations, (2) the kinds of editorial layer(data, visual representation, annotation or interactivity) that inform the creation processand (3) what newsrooms and data visualizers can learn from this practice to create understandable, meaningful and engaging DVPs of (critical) events that evolve over an extendedperiod. Our model supports data visualization practitioners in making informed choiceswhen creating data stories. 

Place, publisher, year, edition, pages
Faculty of Social Sciences, Charles University, Prague, Czech Republic , 2022. Vol. 16, no 1, p. 65-91, article id 04
Keywords [en]
data visualization; data journalism; data activism; data literacy; digital journalism; Covid-19
National Category
Media Studies
Identifiers
URN: urn:nbn:se:mau:diva-55313OAI: oai:DiVA.org:mau-55313DiVA, id: diva2:1702107
Available from: 2022-10-10 Created: 2022-10-10 Last updated: 2023-10-23Bibliographically approved

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Pruulmann-Vengerfeldt, Pille

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf