Moreira Gustavo, Hosseini Maryam, Veiga Carolina, Alexandre Lucas, Colaninno Nicola, de Oliveira Daniel, Ferreira Nivan, Lage Marcos, Miranda Fabio
IEEE Trans Vis Comput Graph. 2025 Jan;31(1):1224-1234. doi: 10.1109/TVCG.2024.3456353. Epub 2024 Nov 28.
Over the past decade, several urban visual analytics systems and tools have been proposed to tackle a host of challenges faced by cities, in areas as diverse as transportation, weather, and real estate. Many of these tools have been designed through collaborations with urban experts, aiming to distill intricate urban analysis workflows into interactive visualizations and interfaces. However, the design, implementation, and practical use of these tools still rely on siloed approaches, resulting in bespoke systems that are difficult to reproduce and extend. At the design level, these tools undervalue rich data workflows from urban experts, typically treating them only as data providers and evaluators. At the implementation level, they lack interoperability with other technical frameworks. At the practical use level, they tend to be narrowly focused on specific fields, inadvertently creating barriers to cross-domain collaboration. To address these gaps, we present Curio, a framework for collaborative urban visual analytics. Curio uses a dataflow model with multiple abstraction levels (code, grammar, GUI elements) to facilitate collaboration across the design and implementation of visual analytics components. The framework allows experts to intertwine data preprocessing, management, and visualization stages while tracking the provenance of code and visualizations. In collaboration with urban experts, we evaluate Curio through a diverse set of usage scenarios targeting urban accessibility, urban microclimate, and sunlight access. These scenarios use different types of data and domain methodologies to illustrate Curio's flexibility in tackling pressing societal challenges. Curio is available at urbantk.org/curio.
在过去十年中，已经提出了几个城市视觉分析系统和工具，以应对城市在交通、天气和房地产等不同领域面临的一系列挑战。其中许多工具是通过与城市专家合作设计的，旨在将复杂的城市分析工作流程提炼为交互式可视化和界面。然而，这些工具的设计、实施和实际使用仍然依赖于孤立的方法，导致定制系统难以复制和扩展。在设计层面，这些工具低估了城市专家丰富的数据工作流程，通常只将他们视为数据提供者和评估者。在实施层面，它们缺乏与其他技术框架的互操作性。在实际使用层面，它们往往狭隘地专注于特定领域，无意中为跨领域合作制造了障碍。为了弥补这些差距，我们提出了Curio，一个用于协作式城市视觉分析的框架。Curio使用具有多个抽象层次（代码、语法、GUI元素）的数据流模型，以促进视觉分析组件的设计和实施过程中的协作。该框架允许专家在跟踪代码和可视化来源的同时，将数据预处理、管理和可视化阶段交织在一起。通过与城市专家合作，我们通过针对城市可达性、城市微气候和阳光照射的一系列不同使用场景对Curio进行评估。这些场景使用不同类型的数据和领域方法，以说明Curio在应对紧迫社会挑战方面的灵活性。Curio可在urbantk.org/curio上获取。
