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A Study on Visual Representations for Active Plant Wall Data Analysis

Author

Listed:
  • Kahin Akram Hassan

    (Department of Science and Technology, Linköping University, Campus Norrköping, 602 21 Norrköping, Sweden)

  • Yu Liu

    (Department of Science and Technology, Linköping University, Campus Norrköping, 602 21 Norrköping, Sweden)

  • Lonni Besançon

    (Department of Science and Technology, Linköping University, Campus Norrköping, 602 21 Norrköping, Sweden)

  • Jimmy Johansson

    (Department of Science and Technology, Linköping University, Campus Norrköping, 602 21 Norrköping, Sweden)

  • Niklas Rönnberg

    (Department of Science and Technology, Linköping University, Campus Norrköping, 602 21 Norrköping, Sweden)

Abstract

The indoor climate is closely related to human health, well-being, and comfort. Thus, an understanding of the indoor climate is vital. One way to improve the indoor climates is to place an aesthetically pleasing active plant wall in the environment. By collecting data using sensors placed in and around the plant wall both the indoor climate and the status of the plant wall can be monitored and analyzed. This manuscript presents a user study with domain experts in this field with a focus on the representation of such data. The experts explored this data with a Line graph, a Horizon graph, and a Stacked area graph to better understand the status of the active plant wall and the indoor climate. Qualitative measures were collected with Think-aloud protocol and semi-structured interviews. The study resulted in four categories of analysis tasks: Overview, Detail, Perception, and Complexity. The Line graph was found to be preferred for use in providing an overview, and the Horizon graph for detailed analysis, revealing patterns and showing discernible trends, while the Stacked area graph was generally not preferred. Based on these findings, directions for future research are discussed and formulated. The results and future directions of this research can facilitate the analysis of multivariate temporal data, both for domain users and visualization researchers.

Suggested Citation

  • Kahin Akram Hassan & Yu Liu & Lonni Besançon & Jimmy Johansson & Niklas Rönnberg, 2019. "A Study on Visual Representations for Active Plant Wall Data Analysis," Data, MDPI, vol. 4(2), pages 1-18, May.
  • Handle: RePEc:gam:jdataj:v:4:y:2019:i:2:p:74-:d:233096
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