Data Transparency Design in Internet of Things: A Systematic Review

Yonghao Long, Xiapu Luo, Yujie Zhu, Kun Pyo Lee, Stephen Jia Wang (Corresponding Author)

Research output: Journal article publicationJournal articleAcademic researchpeer-review

2 Citations (Scopus)

Abstract

Data transparency plays a critical role in understanding IoT privacy practices and making informed decisions. To gain a comprehensive understanding of transparency in the IoT environment, a systematic literature review of 58 academic articles is conducted to investigate the progress and status of existing data transparency studies from a design perspective. Data transparency was identified as a signifier to bridge the connection between user behavior and privacy risks. The level of transparency achieved was shaped by users’ privacy perceptions, which in turn influenced their privacy behavior. GUI-based transparency design has been widely used in IoT, but it is not sufficient to provide users with accessible, understandable, and unified transparency information. A conceptual transparency design is proposed based on the extracted design opportunities and practices. This paper provides an important resource on transparency issues in the IoT environment, and will benefit the design and computer science communities.
Original languageEnglish
Pages (from-to)1-23
JournalInternational Journal of Human-Computer Interaction
DOIs
Publication statusPublished - 18 Jul 2023

Keywords

  • Internet of things
  • data transparency
  • privacy
  • transparency design

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications

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