Chemicals in the Creek: designing a situated data physicalization of open government data with the community

Access to Interpretable Data to Support Disproportionate Health Risks from Industrial Releases: A Case Study on the Environmental Protection Agency's Datasets and Their Application to the Latinx Communities of Houston, Texas

Latinx communities face disproportionate environmental injustices and are targeted due to systematic economic and political inequities. This research evaluates the ease at which links between industrial releases and risk of adverse health effects can be defined to influence policy change in Houston, TX. The Environmental Protection Agency (EPA)'s Toxic Release Inventory (TRI) is the most comprehensive public database on industrial facilities' toxic chemical releases in the US. TRI is presented within a risk-based context through the Risk Screening Environmental Indicators (RSEI) scores. TRI and RSEI datasets for Houston in 2022 were assessed in QGIS to analyze chemical release and risk in neighborhoods using Community Tabulation Areas (CTAs), identifying demographics of communities facing disproportionate industrial releases and consequent potential health risks. Geospatial visualizations reflected Latinx communities to house the heaviest polluting industrial facilities in Houston. As a result, these communities face the highest potential risk of adverse health effects due to exposure to a multitude of chemicals-particularly 1,3-butadiene, benzene, and chromium-as reflected in cumulative RSEI scores. An analysis of TRI and RSEI datasets elucidates the burden of gathering and analyzing chemical release data in a public health context, reflecting why change beginning at the local level can be difficult for under-resourced Latinx communities facing industrial pollution. Improving the accessibility and utility of the EPA resources will provide a resource to advocate for data-driven policy change.

Affective Visualization Design: Leveraging the Emotional Impact of Data

In recent years, more and more researchers have reflected on the undervaluation of emotion in data visualization and highlighted the importance of considering human emotion in visualization design. Meanwhile, an increasing number of studies have been conducted to explore emotion-related factors. However, so far, this research area is still in its early stages and faces a set of challenges, such as the unclear definition of key concepts, the insufficient justification of why emotion is important in visualization design, and the lack of characterization of the design space of affective visualization design. To address these challenges, first, we conducted a literature review and identified three research lines that examined both emotion and data visualization. We clarified the differences between these research lines and kept 109 papers that studied or discussed how data visualization communicates and influences emotion. Then, we coded the 109 papers in terms of how they justified the legitimacy of considering emotion in visualization design (i.e., why emotion is important) and identified five argumentative perspectives. Based on these papers, we also identified 61 projects that practiced affective visualization design. We coded these design projects in three dimensions, including design fields (where), design tasks (what), and design methods (how), to explore the design space of affective visualization design.

Affective Learning Objectives for Communicative Visualizations

When designing communicative visualizations, we often focus on goals that seek to convey patterns, relations, or comparisons (cognitive learning objectives). We pay less attention to affective intents-those that seek to influence or leverage the audience's opinions, attitudes, or values in some way. Affective objectives may range in outcomes from making the viewer care about the subject, strengthening a stance on an opinion, or leading them to take further action. Because such goals are often considered a violation of perceived 'neutrality' or are 'political,' designers may resist or be unable to describe these intents, let alone formalize them as learning objectives. While there are notable exceptions-such as advocacy visualizations or persuasive cartography-we find that visualization designers rarely acknowledge or formalize affective objectives. Through interviews with visualization designers, we expand on prior work on using learning objectives as a framework for describing and assessing communicative intent. Specifically, we extend and revise the framework to include a set of affective learning objectives. This structured taxonomy can help designers identify and declare their goals and compare and assess designs in a more principled way. Additionally, the taxonomy can enable external critique and analysis of visualizations. We illustrate the use of the taxonomy with a critical analysis of an affective visualization.

What's the Situation with Situated Visualization? A Survey and Perspectives on Situatedness

Situated visualization is an emerging concept within visualization, in which data is visualized in situ, where it is relevant to people. The concept has gained interest from multiple research communities, including visualization, human-computer interaction (HCI) and augmented reality. This has led to a range of explorations and applications of the concept, however, this early work has focused on the operational aspect of situatedness leading to inconsistent adoption of the concept and terminology. First, we contribute a literature survey in which we analyze 44 papers that explicitly use the term "situated visualization" to provide an overview of the research area, how it defines situated visualization, common application areas and technology used, as well as type of data and type of visualizations. Our survey shows that research on situated visualization has focused on technology-centric approaches that foreground a spatial understanding of situatedness. Secondly, we contribute five perspectives on situatedness (space, time, place, activity, and community) that together expand on the prevalent notion of situatedness in the corpus. We draw from six case studies and prior theoretical developments in HCI. Each perspective develops a generative way of looking at and working with situatedness in design and research. We outline future directions, including considering technology, material and aesthetics, leveraging the perspectives for design, and methods for stronger engagement with target audiences. We conclude with opportunities to consolidate situated visualization research.