research-article

Towards Glyph-based visualizations for big data clustering

Authors:

Dietrich Kammer,

Thomas Gründer,

Martin Kleinsteuber,

Alexander Maasch,

Rainer GrohAuthors Info & Claims

VINCI '17: Proceedings of the 10th International Symposium on Visual Information Communication and Interaction

Pages 129 - 136

https://doi.org/10.1145/3105971.3105979

Published: 14 August 2017 Publication History

Abstract

Data Analysts have to deal with an ever-growing amount of data resources. One way to make sense of this data is to extract features and use clustering algorithms to group items according to a similarity measure. Algorithm developers are challenged when evaluating the performance of the algorithm since it is hard to identify features that influence the clustering. Moreover, many algorithms can be trained using a semi-supervised approach, where human users provide ground truth samples by manually grouping single items. Hence, visualization techniques are needed that help data analysts achieve their goal in evaluating Big data clustering algorithms. In this context, Multidimensional Scaling (MDS) has become a prominent visualization tool. In this paper, we propose a combination with glyphs that can provide a detailed view of specific features involved in MDS. In consequence, human users can understand, adjust, and ultimately improve clustering algorithms. We present a thorough glyph design, which is founded in a comprehensive survey of related work and report the results of a controlled experiments, where participants solved data analysis tasks with both glyphs and a traditional textual display of data values.

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Cited By

Abdelaal MGaluschka MZorn MKannenberg FMenges AWortmann TWeiskopf DKurzhals K(2024)Visual analysis of fitness landscapes in architectural design optimizationThe Visual Computer10.1007/s00371-024-03491-340:7(4927-4940)Online publication date: 17-Jun-2024
https://doi.org/10.1007/s00371-024-03491-3
van Onzenoodt CVázquez PRopinski T(2023)Out of the Plane: Flower versus Star Glyphs to Support High-Dimensional Exploration in Two-Dimensional EmbeddingsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.321691929:12(5468-5482)Online publication date: Dec-2023
https://doi.org/10.1109/TVCG.2022.3216919
Keck MEngeln LBottoni PPanizzi E(2022)Sparkle Glyphs: A Glyph Design for the Analysis of Temporal Multivariate Audio FeaturesProceedings of the 2022 International Conference on Advanced Visual Interfaces10.1145/3531073.3534491(1-3)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1145/3531073.3534491
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Index Terms

Towards Glyph-based visualizations for big data clustering
1. Human-centered computing
  1. Visualization
2. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Clustering and classification
    2. Users and interactive retrieval
      1. Search interfaces

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cover image ACM Other conferences

VINCI '17: Proceedings of the 10th International Symposium on Visual Information Communication and Interaction

August 2017

158 pages

ISBN:9781450352925

DOI:10.1145/3105971

General Chair:
Robert P. Biuk-Aghai
University of Macau, Macau
,
Program Chairs:
Jie Li
Tianjin University, China
,
Shigeo Takahashi
University of Aizu, Japan

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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KMUTT: King Mongkut's University of Technology Thonburi

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 August 2017

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Funding Sources

Free State of Saxony
European Regional Development Fund

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VINCI '17

Sponsor:

KMUTT

VINCI '17: 10th International Symposium on Visual Information Communication and Interaction

August 14 - 16, 2017

Bangkok, Thailand

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VINCI '17 Paper Acceptance Rate 12 of 27 submissions, 44%;

Overall Acceptance Rate 71 of 193 submissions, 37%

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Cited By

Abdelaal MGaluschka MZorn MKannenberg FMenges AWortmann TWeiskopf DKurzhals K(2024)Visual analysis of fitness landscapes in architectural design optimizationThe Visual Computer10.1007/s00371-024-03491-340:7(4927-4940)Online publication date: 17-Jun-2024
https://doi.org/10.1007/s00371-024-03491-3
van Onzenoodt CVázquez PRopinski T(2023)Out of the Plane: Flower versus Star Glyphs to Support High-Dimensional Exploration in Two-Dimensional EmbeddingsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.321691929:12(5468-5482)Online publication date: Dec-2023
https://doi.org/10.1109/TVCG.2022.3216919
Keck MEngeln LBottoni PPanizzi E(2022)Sparkle Glyphs: A Glyph Design for the Analysis of Temporal Multivariate Audio FeaturesProceedings of the 2022 International Conference on Advanced Visual Interfaces10.1145/3531073.3534491(1-3)Online publication date: 6-Jun-2022
https://dl.acm.org/doi/10.1145/3531073.3534491
Lamy J(2021)A data science approach to drug safety: Semantic and visual mining of adverse drug events from clinical trials of pain treatmentsArtificial Intelligence in Medicine10.1016/j.artmed.2021.102074115(102074)Online publication date: May-2021
https://doi.org/10.1016/j.artmed.2021.102074
Kammer DKeck MGrunder TMaasch AThom TKleinsteuber MGroh R(2020)Glyphboard: Visual Exploration of High-Dimensional Data Combining Glyphs with Dimensionality ReductionIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2020.296906026:4(1661-1671)Online publication date: 1-Apr-2020
https://doi.org/10.1109/TVCG.2020.2969060
Lamy J(2020)Comparison of four visual analytics techniques for the visualization of adverse drug event rates in clinical trials2020 24th International Conference Information Visualisation (IV)10.1109/IV51561.2020.00063(344-349)Online publication date: Sep-2020
https://doi.org/10.1109/IV51561.2020.00063
Zhao JKarimzadeh MSnyder LSurakitbanharn CQian ZEbert D(2019)MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety AgenciesIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2019.2934603(1-1)Online publication date: 2019
https://doi.org/10.1109/TVCG.2019.2934603
Anzai YMisue K(2019)Evaluation of Effectiveness of Glyphs to Enhance ChronoView2019 23rd International Conference Information Visualisation (IV)10.1109/IV.2019.00035(157-162)Online publication date: Jul-2019
https://doi.org/10.1109/IV.2019.00035
Kammer DKeck MGründer TGroh RCatarci TNorman KMecella M(2018)Big data landscapesProceedings of the 2018 International Conference on Advanced Visual Interfaces10.1145/3206505.3206556(1-3)Online publication date: 29-May-2018
https://dl.acm.org/doi/10.1145/3206505.3206556

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