Learning from lines: Critical COVID data visualizations and the quarantine quotidian
In response to the ubiquitous graphs and maps of COVID-19, artists, designers, data scientists, and public health officials are teaming up to create counter-plots and subaltern maps of the pandemic. In this intervention, we describe the various functions served by these projects. First, they offer t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2020-07-01
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| Series: | Big Data & Society |
| Online Access: | https://doi.org/10.1177/2053951720939236 |
| _version_ | 1818317041561501696 |
|---|---|
| author | Emily Bowe Erin Simmons Shannon Mattern |
| author_facet | Emily Bowe Erin Simmons Shannon Mattern |
| author_sort | Emily Bowe |
| collection | DOAJ |
| description | In response to the ubiquitous graphs and maps of COVID-19, artists, designers, data scientists, and public health officials are teaming up to create counter-plots and subaltern maps of the pandemic. In this intervention, we describe the various functions served by these projects. First, they offer tutorials and tools for both dataviz practitioners and their publics to encourage critical thinking about how COVID-19 data is sourced and modeled—and to consider which subjects are not interpellated in those data sets, and why not. Second, they demonstrate how the pandemic’s spatial logics inscribe themselves in our immediate material landscapes. And third, they remind us of our capacity to personalize and participate in the creation of meaningful COVID visualizations—many of which represent other scales and dimensions of the pandemic, especially the quarantine quotidian. Together, the official maps and counter-plots acknowledge that the pandemic plays out differently across different scales: COVID-19 is about global supply chains and infection counts and TV ratings for presidential press conferences, but it is also about local dynamics and neighborhood mutual aid networks and personal geographies of mitigation and care. |
| first_indexed | 2024-12-13T09:31:01Z |
| format | Article |
| id | doaj.art-04a1b0e3090f4fd1955971aa0c0ab964 |
| institution | Directory Open Access Journal |
| issn | 2053-9517 |
| language | English |
| last_indexed | 2024-12-13T09:31:01Z |
| publishDate | 2020-07-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Big Data & Society |
| spelling | doaj.art-04a1b0e3090f4fd1955971aa0c0ab9642022-12-21T23:52:30ZengSAGE PublishingBig Data & Society2053-95172020-07-01710.1177/2053951720939236Learning from lines: Critical COVID data visualizations and the quarantine quotidianEmily BoweErin SimmonsShannon MatternIn response to the ubiquitous graphs and maps of COVID-19, artists, designers, data scientists, and public health officials are teaming up to create counter-plots and subaltern maps of the pandemic. In this intervention, we describe the various functions served by these projects. First, they offer tutorials and tools for both dataviz practitioners and their publics to encourage critical thinking about how COVID-19 data is sourced and modeled—and to consider which subjects are not interpellated in those data sets, and why not. Second, they demonstrate how the pandemic’s spatial logics inscribe themselves in our immediate material landscapes. And third, they remind us of our capacity to personalize and participate in the creation of meaningful COVID visualizations—many of which represent other scales and dimensions of the pandemic, especially the quarantine quotidian. Together, the official maps and counter-plots acknowledge that the pandemic plays out differently across different scales: COVID-19 is about global supply chains and infection counts and TV ratings for presidential press conferences, but it is also about local dynamics and neighborhood mutual aid networks and personal geographies of mitigation and care.https://doi.org/10.1177/2053951720939236 |
| spellingShingle | Emily Bowe Erin Simmons Shannon Mattern Learning from lines: Critical COVID data visualizations and the quarantine quotidian Big Data & Society |
| title | Learning from lines: Critical COVID data visualizations and the quarantine quotidian |
| title_full | Learning from lines: Critical COVID data visualizations and the quarantine quotidian |
| title_fullStr | Learning from lines: Critical COVID data visualizations and the quarantine quotidian |
| title_full_unstemmed | Learning from lines: Critical COVID data visualizations and the quarantine quotidian |
| title_short | Learning from lines: Critical COVID data visualizations and the quarantine quotidian |
| title_sort | learning from lines critical covid data visualizations and the quarantine quotidian |
| url | https://doi.org/10.1177/2053951720939236 |
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