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Regina Schuster

Publications and source records attributed to Regina Schuster.

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Data journeys in popular science: Producing climate change and COVID-19 data visualizations at Scientific American

Vast amounts of (open) data are increasingly used to make arguments about crisis topics such as climate change and global pandemics. Data visualizations are central to bringing these viewpoints to broader publics. However, visualizations often conceal the many contexts involved in their production, ranging from decisions made in research labs about collecting and sharing data to choices made in editorial rooms about which data stories to tell. In this paper, we examine how data visualizations about climate change and COVID-19 are produced in popular science magazines, using Scientific American, an established English-language popular science magazine, as a case study. To do this, we apply the analytical concept of data journeys (Leonelli, 2020) in a mixed methods study that centers on interviews with Scientific American staff and is supplemented by a visualization analysis of selected charts. In particular, we discuss the affordances of working with open data, the role of collaborative data practices, and how the magazine works to counter misinformation and increase transparency. This work provides an empirical contribution by providing insight into the data (visualization) practices of science communicators and demonstrating how the concept of data journeys can be used as an analytical framework.

cs.DL

"Being Simple on Complex Issues" -- Accounts on Visual Data Communication about Climate Change

Data visualizations play a critical role in both communicating scientific evidence about climate change and in stimulating engagement and action. To investigate how visualizations can be better utilized to communicate the complexities of climate change to different audiences, we conducted interviews with 17 experts in the fields of climate change, data visualization, and science communication, as well as with 12 laypersons. Besides questions about climate change communication and various aspects of data visualizations, we also asked participants to share what they think is the main takeaway message for two exemplary climate change data visualizations. Through a thematic analysis, we observe differences regarding the included contents, the length and abstraction of messages, and the sensemaking process between and among the participant groups. On average, experts formulated shorter and more abstract messages, often referring to higher-level conclusions rather than specific details. We use our findings to reflect on design decisions for creating more effective visualizations, particularly in news media sources geared toward lay audiences. We hereby discuss the adaption of contents according to the needs of the audience, the trade-off between simplification and accuracy, as well as techniques to make a visualization attractive.

cs.HC

Practitioners' Perspectives on Designing Data Visualizations for the General Public

Public-facing data visualizations can play a vital role in making complex information clear and engaging, thereby encouraging informed public discourse and participation. However, existing work offers limited insight into how practitioners make design decisions based on their envisioned target audiences and across different media channels. To investigate this, we conducted semi-structured interviews with 21 professionals from journalistic settings, focusing on how they conceptualize their readers, translate these notions into design choices, and evaluate their work. We found that practitioners often rely on broad audience definitions, despite considering ``knowing their readers'' essential. Evaluation primarily relies on peer feedback or social metrics rather than user testing. From these accounts, we identify recurring strategies employed to reach general, often undefined publics. We discuss implications for audience-centered authoring tools, proposing features such as persona simulations and content-adaptive multi-format authoring, message-first rhetoric-aware workflows, and lightweight in-tool evaluation to better support the realities of public-facing design.

cs.HC

"The main message is that sustainability would help" -- Reflections on takeaway messages of climate change data visualizations

How do different audiences make sense of climate change data visualizations and what do they take away as a main message? To investigate this question, we are building on the results of a previous study, focusing on expert opinions regarding public climate change communication and the role of data visualizations. Hereby, we conducted semi-structured interviews with 17 experts in the fields of climate change, science communication, or data visualization. We also interviewed six lay persons with no professional background in either of these areas. With this analysis, we aim to shed light on how lay audiences arrive at an understanding of climate change data visualizations and what they take away as a main message. For two exemplary data visualizations, we compare their takeaway messages with messages formulated by experts. Through a thematic analysis, we observe differences regarding the included contents, the length and abstraction of messages, and the sensemaking process between and among the participant groups.

cs.HC

What is the message? Perspectives on Visual Data Communication

Data visualizations are widely used to communicate messages about urgent topics such as climate change and public health. However, we still know little about how these visualizations are produced and interpreted in popular science contexts. In this mixed-method study, we examine how data are visually communicated and understood in the popular science magazine Scientific American, focusing on the messages these visualizations convey. To capture this complexity, we analyze data visualizations about climate change and pandemics in Scientific American over the past fifty years from three complementary perspectives: reader, chart, and producer. From the reader's perspective, we articulate takeaway messages and document sensemaking, interpreting visualizations first without and then with textual elements. From the chart perspective, we examine how visual features and text shape interpretation. From the producer's perspective, we draw on interviews with Scientific American staff to understand message planning and compare a sample of their intended messages with those we interpreted. Using takeaway messages as our central analytic lens, we develop a message typology and show that messages vary systematically across dimensions such as granularity, articulation, and inference. A key finding is that text plays a pivotal role: approximately two-thirds of messages change when textual elements are added. While the interviews highlighted the central role of message planning in visualization production, intended and interpreted messages only partially aligned. Our findings underscore the importance of contextual clarity and audience-aware communication, and we derive recommendations for visualization designers and science communicators.

cs.HC