Visualizing COVID-19 : an analytical model to understand and compose continuously evolving data visualization projects
| Authors | |
|---|---|
| Year of publication | 2022 |
| Type | Article in Periodical |
| Magazine / Source | Mediální studia / Media Studies |
| MU Faculty or unit | |
| Citation | |
| web | článek - open access |
| Keywords | data visualization; data journalism; data activism; data literacy; digital journalism; Covid-19 |
| Attached files | |
| Description | 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. |
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