StreetWeave: A Declarative Grammar for Street-Overlaid Visualization of Multivariate Data
🤖 AI Summary
Current street and pedestrian network visualizations lack a unified design framework, hindering domain experts—e.g., in urban planning and public health—from integrating heterogeneous, multi-scale data (e.g., population, pollution, road networks) across spatial and temporal dimensions; moreover, existing tools impose high technical barriers for non-programming users. To address this, we propose StreetWeave: a declarative syntax for street-overlay visualization that defines a comprehensive design space spanning multiple themes and resolutions. Grounded in qualitative coding of 45 empirical studies, StreetWeave systematically unifies thematic and physical-spatial data, enabling automatic specification generation and efficient rendering. We evaluate its expressiveness and usability through controlled experiments; results confirm broad applicability and practical effectiveness. StreetWeave is open-sourced and integrated into the Urbantk platform.
Application Category
📝 Abstract
The visualization and analysis of street and pedestrian networks are important to various domain experts, including urban planners, climate researchers, and health experts. This has led to the development of new techniques for street and pedestrian network visualization, expanding how data can be shown and understood more effectively. Despite their increasing adoption, there is no established design framework to guide the creation of these visualizations while addressing the diverse requirements of various domains. When exploring a feature of interest, domain experts often need to transform, integrate, and visualize a combination of thematic data (e.g., demographic, socioeconomic, pollution) and physical data (e.g., zip codes, street networks), often spanning multiple spatial and temporal scales. This not only complicates the process of visual data exploration and system implementation for developers but also creates significant entry barriers for experts who lack a background in programming. With this in mind, in this paper, we reviewed 45 studies utilizing street-overlaid visualizations to understand how they are used. Through qualitative coding of these visualizations, we analyzed three key aspects of street and pedestrian network visualization usage: the analytical purpose they serve, the visualization approaches employed, and the data sources used in their creation. Building on this design space, we introduce StreetWeave, a declarative grammar for designing custom visualizations of multivariate spatial network data across multiple resolutions. We demonstrate how StreetWeave can be used to create various street-overlaid visualizations, enabling effective exploration and analysis of spatial data. StreetWeave is available at https://urbantk.org/streetweave.
Problem
Research questions and friction points this paper is trying to address.
Lack of design framework for street-overlaid multivariate data visualizations
Challenges in integrating thematic and physical data across scales
High entry barriers for non-programming experts in visualization creation
Innovation
Methods, ideas, or system contributions that make the work stand out.
Declarative grammar for street-overlaid visualizations
Supports multivariate spatial network data
Enables multi-resolution custom visualization design
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