Visualizing COVID-19 : an analytical model to understand and
compose continuously evolving data visualization projects

J 2022

Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects

HIMMA-KADAKAS, Marju; Pille PRUULMANN-VENGERFELDT a Signe IVASK

Základní údaje

Originální název

Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects

Autoři

HIMMA-KADAKAS, Marju; Pille PRUULMANN-VENGERFELDT a Signe IVASK

Vydání

Mediální studia / Media Studies, Praha, Fakulta sociálních věd UK, 2022, 1801-9978

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

50800 5.8 Media and communications

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Odkazy

článek - open access

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14230/22:00127717

Organizační jednotka

Fakulta sociálních studií

EID Scopus

2-s2.0-85138646785

Klíčová slova anglicky

data visualization; data journalism; data activism; data literacy; digital journalism; Covid-19

Štítky

rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 6. 3. 2023 14:27, Mgr. Blanka Farkašová

Anotace

V originále

The increased demand for information during the Covid-19 pandemic inspired projects to describe the pandemic’s progress via data visualization. Critically analyzing the published data visualization projects (DVPs) contributes to establishing a framework that supports both understanding and composing DVPs that evolve over time. Drawing upon constructed grounded 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 DVPs in the United Kingdom, Norway, Sweden and Estonia as well as DVPs created by global and local data activists. The analysis of these examples provides an understanding of (1) the implied agency standing of the authors of the visualizations, (2) the kinds of editorial layer (data, visual representation, annotation or interactivity) that inform the creation process and (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 extended period. Our model supports data visualization practitioners in making informed choices when creating data stories.

Návaznosti

EF18_053/0016952, projekt VaV

Název: Postdoc2MUNI

Přiložené soubory

Visualizing_COVID19.pdf

Citovat

HIMMA-KADAKAS, Marju; Pille PRUULMANN-VENGERFELDT a Signe IVASK. Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects. Mediální studia / Media Studies. Praha: Fakulta sociálních věd UK, 2022, roč. 16, č. 1, s. 65-91. ISSN 1801-9978.

@article{2243722,
   author = {HimmaandKadakas, Marju and PruulmannandVengerfeldt, Pille and Ivask, Signe},
   article_location = {Praha},
   article_number = {1},
   keywords = {data visualization; data journalism; data activism; data literacy; digital journalism; Covid-19},
   language = {eng},
   issn = {1801-9978},
   journal = {Mediální studia / Media Studies},
   title = {Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects},
   url = {https://medialnistudia.fsv.cuni.cz/front.file/download?file=2022%2001%2004%20kadakas.pdf},
   volume = {16},
   year = {2022}
}

TY  - JOUR
ID  - 2243722
AU  - Himma-Kadakas, Marju - Pruulmann-Vengerfeldt, Pille - Ivask, Signe
PY  - 2022
TI  - Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects
JF  - Mediální studia / Media Studies
VL  - 16
IS  - 1
SP  - 65-91
EP  - 65-91
PB  - Fakulta sociálních věd UK
SN  - 18019978
KW  - data visualization
KW  - data journalism
KW  - data activism
KW  - data literacy
KW  - digital journalism
KW  - Covid-19
UR  - https://medialnistudia.fsv.cuni.cz/front.file/download?file=2022%2001%2004%20kadakas.pdf
N2  - The increased demand for information during the Covid-19 pandemic inspired projects to describe the pandemic’s progress via data visualization. Critically analyzing the published data visualization projects (DVPs) contributes to establishing a framework that supports both understanding and composing DVPs that evolve over time. Drawing upon constructed grounded 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 DVPs in the United Kingdom, Norway, Sweden and Estonia as well as DVPs created by global and local data activists. The analysis of these examples provides an understanding of (1) the implied agency standing of the authors of the visualizations, (2) the kinds of editorial layer (data, visual representation, annotation or interactivity) that inform the creation process and (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 extended period. Our model supports data visualization practitioners in making informed choices when creating data stories.
ER  -

HIMMA-KADAKAS, Marju; Pille PRUULMANN-VENGERFELDT a Signe IVASK. Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects. \textit{Mediální studia / Media Studies}. Praha: Fakulta sociálních věd UK, 2022, roč.~16, č.~1, s.~65-91. ISSN~1801-9978.

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