Our AQI Data Literacy project was built upon the preliminary study titled “Designing a Platform for Public Exploration of Multi-Pollutant Air Quality Data,” conducted by previous researchers from the TILES lab. The study highlighted the challenges in interpreting air quality (AQ) data beyond the simplified Air Quality Index (AQI). It emphasized the difficulty for the public to engage in conversations about air pollution causes, risks, and solutions. The AQI was recognized as having been created specifically due to the complexity of AQ data, rendering it inaccessible to non-scientific audiences. The main issue identified was the gap between AQI-centric platforms, which have a low ceiling for engaging with complex data, and comprehensive platforms with too high a floor for non-experts.
The researchers conducted a two-phase survey and interview study focusing on the interpretation of AQ visualizations, including preexisting platforms and their own designs. The research questions addressed how non-expert individuals interpret AQI and AQ data representations and how multi-pollutant AQ data can be visualized to support sense-making in public informal data explorations.
The background of their work considered prior efforts in HCI design related to environmental challenges, particularly in AQ monitoring and platforms. Existing works primarily focused on either AQI or single-pollutant displays, often as informational tools to increase awareness of current conditions. The study emphasized the lack of work specifically assessing and addressing the knowledge gaps of the public regarding the AQI, its representation, and computation.
In continuation of the groundwork laid by the preliminary study conducted by previous researchers, our project aims to address the identified challenges and further enhance public understanding of multi-pollutant air quality data. Building upon the existing knowledge and shortcomings in AQI-centric platforms, our project takes a specific direction toward the design and development of a visual, interactive AQ data platform tailored for public and educational use.
Key Directions of 2024 AQI Data Literacy Project:
- Interactive Data Display: Our project will prioritize the development of an interactive data display that goes beyond the limitations of existing AQI-centric platforms. We aim to create a platform that allows users to engage meaningfully with the complexities of multi-pollutant air quality data, fostering a deeper understanding of the factors contributing to air pollution.
- User-Centered Design: Recognizing the challenges highlighted in the preliminary study regarding the accessibility of existing platforms, our project will adopt a user-centered design approach. This involves considering the needs, preferences, and limitations of non-expert users to ensure that the platform effectively communicates scientific information in an understandable and engaging manner.
- Addressing Knowledge Gaps: One of the primary goals of our project is to bridge knowledge gaps among the general public regarding AQI, its representation, and computation. We will focus on developing features that provide contextual information, historical comparisons, and disaggregated data to empower users with a comprehensive understanding of air quality.
- Education and Data Literacy: Our project aligns with the broader objective of promoting data literacy, particularly in the context of air quality and pollution. By incorporating educational elements into the platform, we aim to facilitate learning experiences for users, empowering them to make informed decisions and contribute to discussions about air pollution and environmental issues.
- Public Engagement: Our project extends beyond the development of a digital platform. We plan to showcase the interactive AQ data platform in public spaces, fostering organic and social interactions. This approach aims to spark curiosity, inspire conversations, and broaden the participation of the public in actively engaging with environmental data.
- Iterative Design Process: Throughout the project, we will adopt an iterative design-based research approach. This involves continuous refinement and enhancement of the platform based on user feedback, ensuring that the final product aligns with the needs and expectations of the target audience.