4 Screenshot of 3D depth pointcloud data of museum visitors gesturing to select datasets to view within the installation. Courtesy NOIRFLUX.

4 Screenshot of 3D depth pointcloud data of museum visitors gesturing to select datasets to view within the installation. Courtesy NOIRFLUX.

Contexts in source publication

Context 1
... seeks to make the interaction with energy data a social experience by enabling users to view and overlay the results of their visualizations with other users' selections in a shared setting. Critically, this platform combines climate, urban, and building data into a collaborative, user-driven visualization experience, where community participants can explore datasets to understand their local conditions while co-creating strategies for building and neighborhood climate adaptation (Figure 4.1). ...
Context 2
... spotlight can illustrate a particular type of climate or energy resource through graphics and color, such as a false color heat map of solar radiation hitting that area of the city. In this example, the average monthly solar radiation data is calculated as kWh/m 2 , which gets converted into information that is more widely understood, such as the number of homes that could be powered by harnessing solar energy in that zone (Figure 4.2). Through this interactive experience, the personal spotlight provides a lens through which to explore energy data that is contextually specific, comparable to other datasets at the same scale, and spatial. ...
Context 3
... interactive experience designed through this platform is based on a novel workflow that links custom coding in interactive design software with 3D depth sensors that capture user locations and gestures as 3D data 'pointclouds.' The custom-coded environment, called 'vvvv,' is a live programming environment (vvvv 2020), which enables a full viewing of the pointcloud depth data that drives the selection of datasets projected on the model (Figure 4.3). It also provides a useful record of how users are engaging the platform including which selections were made and when (Figure 4.4). ...
Context 4
... custom-coded environment, called 'vvvv,' is a live programming environment (vvvv 2020), which enables a full viewing of the pointcloud depth data that drives the selection of datasets projected on the model (Figure 4.3). It also provides a useful record of how users are engaging the platform including which selections were made and when (Figure 4.4). Through this programming environment, updates to the system can be made on the fly and immediately visible to platform participants ( Krietemeyer et al. 2019). ...
Context 5
... types of spatialized building and urban data can be overlaid and related in ways that might not have occurred to any one individual before, leading to deeper insights and to the potential for emergent interactions between different layers of information. The convergence of multiple user's values, perspectives, and creations might lead to strategies that would otherwise not be considered in isolation (Figure 4.5). ...
Context 6
... multiple users have the opportunity to choose datasets and view them on the 3D projected model using gestural interactions that stay with them, platforms such as this could produce a dynamic collage of diverse interests, datasets, explorations, and attitudes, allowing viewers to collectively explore and imagine design futures (Figure 4.6). Recordings of visitor actions and user-driven visualizations create a unique method of documentation of how people are making selections, what data gets compared, which strategies get the most attention, and the emergence of strategies that might result from unexpected layering of spatiotemporal information. ...

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