I've seen "enough": Incrementally improving visualizations to support rapid decision making

Sajjadur Rahman, Maryam Aliakbarpour, Ha Kyung Kong, Eric Blais, Kyratso George Karahalios, Aditya G Parameswaran, Ronitt Rubinfield

Research output: Contribution to journalConference article

Abstract

Data visualization is an effective mechanism for identifying trends, insights, and anomalies in data. On large datasets, however, generating visualizations can take a long time, delaying the extraction of insights, hampering decision making, and reducing exploration time. One solution is to use online sampling-based schemes to generate visualizations faster while improving the displayed estimates incrementally, eventually converging to the exact visualization computed on the entire data. However, the intermediate visualizations are approximate, and often fluctuate drastically, leading to potentially incorrect decisions. We propose sampling-based incremental visualization algorithms that reveal the "salient" features of the visualization quickly-with a 46× speedup relative to baselines-while minimizing error, thus enabling rapid and errorfree decision making. We demonstrate that these algorithms are optimal in terms of sample complexity, in that given the level of interactivity, they generate approximations that take as few samples as possible. We have developed the algorithms in the context of an incremental visualization tool, titled INCVISAGE, for trendline and heatmap visualizations. We evaluate the usability of INCVISAGE via user studies and demonstrate that users are able to make effective decisions with incrementally improving visualizations, especially compared to vanilla online-sampling based schemes.

Original languageEnglish (US)
Pages (from-to)1262-1273
Number of pages12
JournalProceedings of the VLDB Endowment
Volume10
Issue number11
DOIs
StatePublished - Aug 1 2017
Event43rd International Conference on Very Large Data Bases, VLDB 2017 - Munich, Germany
Duration: Aug 28 2017Sep 1 2017

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Visualization
Decision making
Sampling
Data visualization

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

Cite this

Rahman, S., Aliakbarpour, M., Kong, H. K., Blais, E., Karahalios, K. G., Parameswaran, A. G., & Rubinfield, R. (2017). I've seen "enough": Incrementally improving visualizations to support rapid decision making. Proceedings of the VLDB Endowment, 10(11), 1262-1273. https://doi.org/10.14778/3137628.3137637

I've seen "enough" : Incrementally improving visualizations to support rapid decision making. / Rahman, Sajjadur; Aliakbarpour, Maryam; Kong, Ha Kyung; Blais, Eric; Karahalios, Kyratso George; Parameswaran, Aditya G; Rubinfield, Ronitt.

In: Proceedings of the VLDB Endowment, Vol. 10, No. 11, 01.08.2017, p. 1262-1273.

Research output: Contribution to journalConference article

Rahman, S, Aliakbarpour, M, Kong, HK, Blais, E, Karahalios, KG, Parameswaran, AG & Rubinfield, R 2017, 'I've seen "enough": Incrementally improving visualizations to support rapid decision making', Proceedings of the VLDB Endowment, vol. 10, no. 11, pp. 1262-1273. https://doi.org/10.14778/3137628.3137637
Rahman, Sajjadur ; Aliakbarpour, Maryam ; Kong, Ha Kyung ; Blais, Eric ; Karahalios, Kyratso George ; Parameswaran, Aditya G ; Rubinfield, Ronitt. / I've seen "enough" : Incrementally improving visualizations to support rapid decision making. In: Proceedings of the VLDB Endowment. 2017 ; Vol. 10, No. 11. pp. 1262-1273.
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