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Digital Twins (DTs) evolve beyond their current usage as tools for experts into tools for the everyday lives of everyday people. How designers and researchers approach DT design in intelligible ways for non-expert users will be critical. This paper explores the temporal dimension of DTs in the context of domestic energy consumption. We develop a “Time Machine” analogy, as a conceptual tool, to describe the role of DTs, highlighting their capacity to navigate past, present, and future (predictive) data. With this tool, we developed three temporal interfaces for the domestic environment that allow users to navigate and view their energy usage. We evaluated those interfaces with 18 participants through semi-structured interviews and questionnaires. Our findings show that temporal forms of representation effect how users understand time and patterns in their energy usage, with linear presentations excelling in trend visualization, calendars aligning with familiar schedules, and spiral forms highlighting cyclical patterns and routines. Similarly, various data types influence the depth of user insights, with consumption data providing precise but abstract metrics, activity-based representations connecting energy use to specific actions, and context offering a comprehensive understanding of energy usage.

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Design of Temporal Interfaces of Digital Twins in Domestic Energy Consumption

  • 会议论文

  • 发表日期：

    2026年

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  • Yaxin Zheng,
  • Harm van Essen,
  • Scott Mitchell,
  • Liam Fennessy,
  • Laurene Vaughan,
  • Regina Bernhaupt

摘要

Digital Twins (DTs) evolve beyond their current usage as tools for experts into tools for the everyday lives of everyday people. How designers and researchers approach DT design in intelligible ways for non-expert users will be critical. This paper explores the temporal dimension of DTs in the context of domestic energy consumption. We develop a “Time Machine” analogy, as a conceptual tool, to describe the role of DTs, highlighting their capacity to navigate past, present, and future (predictive) data. With this tool, we developed three temporal interfaces for the domestic environment that allow users to navigate and view their energy usage. We evaluated those interfaces with 18 participants through semi-structured interviews and questionnaires. Our findings show that temporal forms of representation effect how users understand time and patterns in their energy usage, with linear presentations excelling in trend visualization, calendars aligning with familiar schedules, and spiral forms highlighting cyclical patterns and routines. Similarly, various data types influence the depth of user insights, with consumption data providing precise but abstract metrics, activity-based representations connecting energy use to specific actions, and context offering a comprehensive understanding of energy usage.