Home > Research > Publications & Outputs > Exploring interactions with physically dynamic ...

Electronic data

Links

Text available via DOI:

View graph of relations

Exploring interactions with physically dynamic bar charts

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published

Standard

Exploring interactions with physically dynamic bar charts. / Taher, Faisal; Hardy, John; Karnik, Abhijit et al.
CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. New York: ACM, 2015. p. 3237-3246.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Taher, F, Hardy, J, Karnik, A, Weichel, C, Jansen, Y, Hornbaek, K & Alexander, J 2015, Exploring interactions with physically dynamic bar charts. in CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, New York, pp. 3237-3246. https://doi.org/10.1145/2702123.2702604

APA

Taher, F., Hardy, J., Karnik, A., Weichel, C., Jansen, Y., Hornbaek, K., & Alexander, J. (2015). Exploring interactions with physically dynamic bar charts. In CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (pp. 3237-3246). ACM. https://doi.org/10.1145/2702123.2702604

Vancouver

Taher F, Hardy J, Karnik A, Weichel C, Jansen Y, Hornbaek K et al. Exploring interactions with physically dynamic bar charts. In CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. New York: ACM. 2015. p. 3237-3246 doi: 10.1145/2702123.2702604

Author

Taher, Faisal ; Hardy, John ; Karnik, Abhijit et al. / Exploring interactions with physically dynamic bar charts. CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. New York : ACM, 2015. pp. 3237-3246

Bibtex

@inproceedings{25bcd930972b4326b003b32ed78a019d,
title = "Exploring interactions with physically dynamic bar charts",
abstract = "Visualizations such as bar charts help users reason about data, but are mostly screen-based, rarely physical, and almost never physical and dynamic. This paper investigates the role of physically dynamic bar charts and evaluates new interactions for exploring and working with datasets rendered in dynamic physical form. To facilitate our exploration we constructed a 10x10 interactive bar chart and designed interactions that supported fundamental visualisation tasks, specifically; annotation, filtering, organization, and navigation. The interactions were evaluated in a user study with 17 participants. Our findings identify the preferred methods of working with the data for each task i.e. directly tapping rows to hide bars, highlight the strengths and limitations of working with physical data, and discuss the challenges of integrating the proposed interactions together into a larger data exploration system. In general, physical interactions were intuitive, informative, and enjoyable, paving the way for new explorations in physical data visualizations.",
author = "Faisal Taher and John Hardy and Abhijit Karnik and Christian Weichel and Yvonne Jansen and Kasper Hornbaek and Jason Alexander",
year = "2015",
month = apr,
day = "18",
doi = "10.1145/2702123.2702604",
language = "English",
isbn = "9781450331456",
pages = "3237--3246",
booktitle = "CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Exploring interactions with physically dynamic bar charts

AU - Taher, Faisal

AU - Hardy, John

AU - Karnik, Abhijit

AU - Weichel, Christian

AU - Jansen, Yvonne

AU - Hornbaek, Kasper

AU - Alexander, Jason

PY - 2015/4/18

Y1 - 2015/4/18

N2 - Visualizations such as bar charts help users reason about data, but are mostly screen-based, rarely physical, and almost never physical and dynamic. This paper investigates the role of physically dynamic bar charts and evaluates new interactions for exploring and working with datasets rendered in dynamic physical form. To facilitate our exploration we constructed a 10x10 interactive bar chart and designed interactions that supported fundamental visualisation tasks, specifically; annotation, filtering, organization, and navigation. The interactions were evaluated in a user study with 17 participants. Our findings identify the preferred methods of working with the data for each task i.e. directly tapping rows to hide bars, highlight the strengths and limitations of working with physical data, and discuss the challenges of integrating the proposed interactions together into a larger data exploration system. In general, physical interactions were intuitive, informative, and enjoyable, paving the way for new explorations in physical data visualizations.

AB - Visualizations such as bar charts help users reason about data, but are mostly screen-based, rarely physical, and almost never physical and dynamic. This paper investigates the role of physically dynamic bar charts and evaluates new interactions for exploring and working with datasets rendered in dynamic physical form. To facilitate our exploration we constructed a 10x10 interactive bar chart and designed interactions that supported fundamental visualisation tasks, specifically; annotation, filtering, organization, and navigation. The interactions were evaluated in a user study with 17 participants. Our findings identify the preferred methods of working with the data for each task i.e. directly tapping rows to hide bars, highlight the strengths and limitations of working with physical data, and discuss the challenges of integrating the proposed interactions together into a larger data exploration system. In general, physical interactions were intuitive, informative, and enjoyable, paving the way for new explorations in physical data visualizations.

U2 - 10.1145/2702123.2702604

DO - 10.1145/2702123.2702604

M3 - Conference contribution/Paper

SN - 9781450331456

SP - 3237

EP - 3246

BT - CHI '15 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems

PB - ACM

CY - New York

ER -