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.