Kathleen Gregory

Regina Schuster, Kathleen Gregory, Christian Knoll et al.

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.

Regina Schuster, Kathleen Gregory, Torsten Möller et al.

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.

Kathleen Gregory, Dorothea Strecker

Sustaining open data infrastructures over time is a complex puzzle, involving dynamic funding models and relationships with customers, collaborators, and competitors. Despite their importance, these mechanisms are often hidden from view, limiting their applicability to other infrastructures. In this article, we examine how Dryad, a well-known open data infrastructure, has worked toward financial sustainability by reconfiguring relationships with other actors and by strategically implementing a new business model and process of assetization. We identify four types of relationship reconfigurations with customers, collaborators, and competitors critical to Dryad's financial evolution: reinforcing, forging, positioning, and excluding. We then analyze how Dryad's strategic efforts to develop a new fee structure have changed its interpretations of value(s), community, and governance, factors important in an infrastructure's longevity. We conclude by highlighting emerging tensions that provide insight for other open infrastructures working to become financially sustainable. As a whole, our analysis focuses not just on financial mechanisms for funding open data infrastructures (although those emerge) but on the relationships which enable them.

Laura Koesten, Kathleen Gregory, Paul Groth et al.

The sharing and reuse of data are seen as critical to solving the most complex problems of today. Despite this potential, relatively little is known about a key step in data reuse: people's behaviours involved in data-centric sensemaking. We aim to address this gap by presenting a mixed-methods study combining in-depth interviews, a think-aloud task and a screen recording analysis with 31 researchers as they summarised and interacted with both familiar and unfamiliar data. We use our findings to identify and detail common activity patterns and necessary data attributes across three clusters of sensemaking activities: inspecting data, engaging with content, and placing data within broader contexts. We conclude by proposing design recommendations for tools and documentation practices which can be used to facilitate sensemaking and subsequent data reuse.