Data Physicalization

Dragicevic, Pierre; Jansen, Yvonne; Moere, Andrew Vande

doi:10.1007/978-3-319-27648-9_94-1

Cited by 35 publications

(31 citation statements)

References 114 publications

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“…The final six dimensions are inspired by existing concepts and theoretical frameworks from within and outside physicalization research. More specifically, the dimension of Data type follows Munzner et al 's visualization classification [72] and Information communication expands on the actuation technologies as proposed by Dragicevic et al [22].…”

Section: Discussionmentioning

confidence: 99%

“…For example, they discuss the research challenge of identifying physical variables (additional to visual variables [5]) as physicality can go beyond solely visual concepts, and we need to identify these to understand the design space of physicalization. In 2020, Dragicevic et al [22] provided a further overview of the research area of data physicalization, categorized by different motivations to create and use them.…”

Section: Surveys and Conceptual Modelsmentioning

confidence: 99%

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Physecology: A Conceptual Framework to Describe Data Physicalizations in their Real-World Context

Sauvé

Sturdee

Houben

2022

ACM Trans. Comput.-Hum. Interact.

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The standard definition for “physicalizations” is “a physical artifact whose geometry or material properties encode data” [ 47 ]. While this working definition provides the fundamental groundwork for conceptualizing physicalization, in practice many physicalization systems go beyond the scope of this definition as they consist of distributed physical and digital elements that involve complex interaction mechanisms. In this article, we examine how “physicalization” is part of a broader ecology—the “physecology”—with properties that go beyond the scope of the working definition. Through analyzing 60 representative physicalization papers, we derived six design dimensions of a physecology: (i) represented data type, (ii) way of information communication, (iii) interaction mechanisms, (iv) spatial input–output coupling, (v) physical setup, and (vi) audiences involved. Our contribution is the extension of the definition of physicalization to the broader concept of “physecology,” to provide conceptual clarity on the design of physicalizations for future work.

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Section: Discussionmentioning

confidence: 99%

Section: Surveys and Conceptual Modelsmentioning

confidence: 99%

Physecology: A Conceptual Framework to Describe Data Physicalizations in their Real-World Context

Sauvé

Sturdee

Houben

2022

ACM Trans. Comput.-Hum. Interact.

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“…Combining Environments for Data Analysis Using different interactive environments has great potential for data analysis which was demonstrated by previous work on large display environments [3,51], physical visualizations [23], and immersive environments [24]. We believe that combining different environments can leverage their advantages and mitigate their disadvantages at the same time.…”

Section: Perception Of Ar Content and Displaymentioning

confidence: 93%

Personal Augmented Reality for Information Visualization on Large Interactive Displays

Reipschläger,

Flemisch,

Dachselt

2020

Preprint

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“…Most commonly, this spatial context has been used for geographic representations to show the built environment either in the past through remote sensing or as planned in the future [122]. The subfield of Situated Analytics [19] combines data with its spatial context to achieve a form of virtual data physicalisation [123] and embodied interaction [70,74,75,85,86] that enables humans to maximise the use of all senses to perceive the data (see Figure 7). Indeed, information on cities can be embedded in the situated context with meaningful 3D representations that users can explore.…”

Section: Situated Analyticsmentioning

confidence: 99%

“…Smart Objects are concrete implementations of a DT (and even the FTs paradigm), but they limit the Thing to be a small-scale object with a fixed use. Smart Objects are also a form of data physicalisation [123] that provides the opportunity to interact with data beyond a visual medium.…”

Section: The Analytical Environment Of the Digital Twin-models And Se...mentioning

confidence: 99%

The Hitchhiker’s Guide to Fused Twins: A Review of Access to Digital Twins In Situ in Smart Cities

et al. 2022

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Smart Cities already surround us, and yet they are still incomprehensibly far from directly impacting everyday life. While current Smart Cities are often inaccessible, the experience of everyday citizens may be enhanced with a combination of the emerging technologies Digital Twins (DTs) and Situated Analytics. DTs represent their Physical Twin (PT) in the real world via models, simulations, (remotely) sensed data, context awareness, and interactions. However, interaction requires appropriate interfaces to address the complexity of the city. Ultimately, leveraging the potential of Smart Cities requires going beyond assembling the DT to be comprehensive and accessible. Situated Analytics allows for the anchoring of city information in its spatial context. We advance the concept of embedding the DT into the PT through Situated Analytics to form Fused Twins (FTs). This fusion allows access to data in the location that it is generated in in an embodied context that can make the data more understandable. Prototypes of FTs are rapidly emerging from different domains, but Smart Cities represent the context with the most potential for FTs in the future. This paper reviews DTs, Situated Analytics, and Smart Cities as the foundations of FTs. Regarding DTs, we define five components (physical, data, analytical, virtual, and Connection Environments) that we relate to several cognates (i.e., similar but different terms) from existing literature. Regarding Situated Analytics, we review the effects of user embodiment on cognition and cognitive load. Finally, we classify existing partial examples of FTs from the literature and address their construction from Augmented Reality, Geographic Information Systems, Building/City Information Models, and DTs and provide an overview of future directions.

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Data Physicalization

Cited by 35 publications

References 114 publications

Physecology: A Conceptual Framework to Describe Data Physicalizations in their Real-World Context

Physecology: A Conceptual Framework to Describe Data Physicalizations in their Real-World Context

Personal Augmented Reality for Information Visualization on Large Interactive Displays

The Hitchhiker’s Guide to Fused Twins: A Review of Access to Digital Twins In Situ in Smart Cities

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