More Web Proxy on the site http://driver.im/

Article

Line graph explorer: scalable display of line graphs using Focus+Context

Authors:

Robert Kincaid,

Heidi LamAuthors Info & Claims

AVI '06: Proceedings of the working conference on Advanced visual interfaces

Pages 404 - 411

https://doi.org/10.1145/1133265.1133348

Published: 23 May 2006 Publication History

Abstract

Scientific measurements are often depicted as line graphs. State-of-the-art high throughput systems in life sciences, telemetry and electronics measurement rapidly generate hundreds to thousands of such graphs. Despite the increasing volume and ubiquity of such data, few software systems provide efficient interactive management, navigation and exploratory analysis of large line graph collections. To address these issues, we have developed Line Graph Explorer (LGE). LGE is a novel and visually scalable line graph management system that supports facile navigation and interactive visual analysis. LGE provides a compact overview of the entire collection by encoding the y-dimension of individual line graphs with color instead of space, thus enabling the analyst to see major common features and alignments of the data. Using Focus+Context techniques, LGE provides interactions for viewing selected compressed graphs in detail as standard line graphs without losing a sense of the general pattern and major features of the collection. To further enhance visualization and pattern discovery, LGE provides sorting and clustering of line graphs based on similarity of selected graph features. Sequential sorting by associated line graph metadata is also supported. We illustrate the features and use of LGE with examples from meteorology and biology.

References

[1]

Agilent Technologies, Agilent 5100 Automated Lab-on-a-Chip Platform http://www.chem.agilent.com, 2005.

[2]

Amar, R., Eagan, J. and Stasko, J., Low-Level Components of Analytic Activity in Information Visualization. in Proc. of the IEEE Symp. on Information Visualization (INFOVIS '05), 2005, 111--117.

Digital Library

[3]

Baudisch, P., Lee, B. and Hanna, L., Fishnet, a fisheye web browser with search term popouts: a comparative evaluation with overview and linear view. in Proc. of the Working Conf. on Advanced Visual Interfaces (AVI'04), 2004, 133--140.

Digital Library

[4]

Berry, L. and Munzner, T., BinX: Dynamic Exploration of Time Series Datasets Across Aggregation Levels. in Posters Compendium of the IEEE Symp. on Information Visualization (INFOVIS'04), 2004, 5--6.

Digital Library

[5]

Bertin, J. Graphics and Graphic Information-Processing. Walter de Gruyter, 1981.

[6]

Card, S. K., Mackinlay, J. D. and Shneiderman, B. Readings in information visualization: using vision to think. Morgan Kaufmann Publishers, San Francisco, Calif., 1999.

Digital Library

[7]

Clarke, S. and Engelbach, R. Ancient Egyptian construction and architecture. Dover Publications, New York, 1990.

[8]

Eisen, M. B., Spellman, P. T., Brown, P. O. and Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. U S A, 95, 25 (1998), 14863--14868.

[9]

Gutwin, C. and Fedak, C., A comparison of fisheye lenses for interactive layout tasks. in Proc. of Graphics Interface, 2004, 213--220.

Digital Library

[10]

Gutwin, C. and Skopik, A., Fisheye View are Good for Large Steering Tasks. in Proc. of the Conf. on Human Factors in Computing Systems (CHI'03), 2003, 201--208.

Digital Library

[11]

Hao, M. C., Dayal, U., Keim, D. A. and Schreck, T., Importance-driven visualization layouts for large time series data. in Proc. of the IEEE Symp. on Information Visualization (INFOVIS'05), 2005, 203--210.

Digital Library

[12]

Hochheiser, H. and Shneiderman, B., A dynamic query interface for finding patterns in time series data. in Proc. of the Conf. on Human Factors in Computing Systems (CHI'02), 2002, 522--523.

Digital Library

[13]

Kincaid, R., VistaClara: an interactive visualization for exploratory analysis of DNA microarrays. in Proc. of the ACM Symp. on Applied computing (SAC'04), 2004, 167--174.

Digital Library

[14]

Kincaid, R., Ben-Dor, A. and Yakhini, Z. Exploratory visualization of array-based comparative genomic hybridization. Information Visualization, 4, 3 (2005), 176--190.

Digital Library

[15]

Kobsa, A. User Experiments with Tree Visualization Systems. Proc. of the IEEE Symp. on Information Visualization (INFOVIS'04) (2004), 9--16.

Digital Library

[16]

Molina, M. A., et al. Trastuzumab (Herception), a humanized anti-HER2 receptor monoclonal antibody, inhibits basal and activated HER2 ectodomain cleavage in breast cancer cells. Cancer Research 61, 12 (2001), 4744--4749.

[17]

Müller, W. and Schumann, H., Visualization for modeling and simulation: visualization methods for time-dependent data - an overview. in Proc. of the Winter Conf. on Simulation, 2003, 737--745.

Digital Library

[18]

Pirolli, P. and Rao, R. Table lens as a tool for making sense of data. in Proc. of the Workshop on Advanced Visual Interfaces (AVI'96), ACM Press, Gubbio, Italy, 1996, 67--80.

Digital Library

[19]

Plot, R. Philosophical Transactions of the Royal Society of London, 169 (1685), 930--931.

[20]

Pollack, J. R., et al. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc. Natl. Acad. Sci. U S A, 99, 20 (2002), 12963--12968.

[21]

Rao, R. and Card, S. K., The table lens: merging graphical and symbolic representations in an interactive focus + context visualization for tabular information. in Proc. of the Conf. on Human Factors in Computing Systems (CHI'94), 1994, 318--322.

Digital Library

[22]

Ryall, K., et al. QueryLines: approximate query for visual browsing. in Extended Abstracts of the Conf. on Human Factors in Computing Systems (CHI '05), ACM Press, Portland, OR, USA, 2005, 1765--1768.

Digital Library

[23]

Saito, T., et al., Two-tone pseudo coloring: compact visualization for one-dimensional data. in Proc. of the IEEE Symp. on Information Visualization (INFOVIS'05), 2005, 173--180.

Digital Library

[24]

Schaffer, D., et al. Navigating Clustered Networks through Fisheye and Full-Zoom Methods. ACM Trans. Comput.-Hum. Interact., 3, 2 (1996), 162--188.

Digital Library

[25]

Siirtola, H., Interaction with the Reorderable Matrix. in Proc. of the International Conf. on Information Visualisation (IV'99), 1999, 272.

Digital Library

[26]

Spotfire, Inc., Spotfire http://www.spotfire.com, 2005.

[27]

University of Dayton. Temperature Data Archive http://www.engr.udayton.edu/weather, 2005.

Cited By

Bendeck ABromley DSetlur V(2024)SlopeSeeker: A Search Tool for Exploring a Dataset of Quantifiable TrendsProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645208(817-836)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645208
Hao JShi QYe YZeng W(2024): Diagnosing Time Representations for Time-Series Forecasting with Counterfactual ExplanationsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332738930:1(1183-1193)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TVCG.2023.3327389
Chen HBeachnau AThomas PManeriker PKimball JRossi R(2024)LIVE-ITS: LSH-based Interactive Visualization Explorer for Large-Scale Incomplete Time Series2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825096(840-849)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825096
Show More Cited By

Index Terms

Line graph explorer: scalable display of line graphs using Focus+Context

Recommendations

Collapsible graphs and Hamiltonian connectedness of line graphs

Thomassen conjectured that every 4-connected line graph is Hamiltonian. Chen and Lai [Z.-H. Chen, H.-J. Lai, Reduction techniques for super-Eulerian graphs and related topics-an update, in: Ku Tung-Hsin (Ed.), Combinatorics and Graph Theory, vol. 95, ...
On 3-connected hamiltonian line graphs

Thomassen conjectured that every 4-connected line graph is hamiltonian. It has been proved that every 4-connected line graph of a claw-free graph, or an almost claw-free graph, or a quasi-claw-free graph, is hamiltonian. In 1998, Ainouche et al. [2] ...
Every 3-connected, essentially 11-connected line graph is Hamiltonian

Thomassen conjectured that every 4-connected line graph is Hamiltonian. A vertex cut X of G is essential if G - X has at least two non-trivial components. We prove that every 3-connected, essentially 11-connected line graph is Hamiltonian. Using Ryjáček'...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

AVI '06: Proceedings of the working conference on Advanced visual interfaces

May 2006

512 pages

ISBN:1595933530

DOI:10.1145/1133265

General Chair:
Augusto Celentano
Università Ca' Foscari di Venezia, Mestre(VE), Italy

Copyright © 2006 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 ACM 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2006

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

AVI06

AVI06: The International Conference on Advanced Visual Interfaces

May 23 - 26, 2006

Venezia, Italy

Acceptance Rates

Overall Acceptance Rate 128 of 490 submissions, 26%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

61
Total Citations
View Citations
1,057
Total Downloads

Downloads (Last 12 months)74
Downloads (Last 6 weeks)5

Reflects downloads up to 26 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Bendeck ABromley DSetlur V(2024)SlopeSeeker: A Search Tool for Exploring a Dataset of Quantifiable TrendsProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645208(817-836)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3640543.3645208
Hao JShi QYe YZeng W(2024): Diagnosing Time Representations for Time-Series Forecasting with Counterfactual ExplanationsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.332738930:1(1183-1193)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TVCG.2023.3327389
Chen HBeachnau AThomas PManeriker PKimball JRossi R(2024)LIVE-ITS: LSH-based Interactive Visualization Explorer for Large-Scale Incomplete Time Series2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825096(840-849)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825096
Feng THu YYang JPolk TZhao YLiu SYang Z(2023)TimePool: Visually Answer “Which and When” Questions On Univariate Time Series2023 IEEE Visualization and Visual Analytics (VIS)10.1109/VIS54172.2023.00049(201-205)Online publication date: 21-Oct-2023
https://doi.org/10.1109/VIS54172.2023.00049
Zhou JSaha KLopez Carron IYoo DDeeter CDe Choudhury MArriaga R(2022)Veteran Critical Theory as a Lens to Understand Veterans' Needs and Support on Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/35129806:CSCW1(1-28)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1145/3512980
Liu DAlnegheimish SZytek AVeeramachaneni K(2022)MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time SeriesProceedings of the ACM on Human-Computer Interaction10.1145/35129506:CSCW1(1-30)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1145/3512950
Habib HPearman SYoung ESaxena IZhang RCranor L(2022)Identifying User Needs for Advertising Controls on FacebookProceedings of the ACM on Human-Computer Interaction10.1145/35129066:CSCW1(1-42)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1145/3512906
Lohfink ADuque Anton SLeitte HGarth C(2022)Knowledge Rocks: Adding Knowledge Assistance to Visualization SystemsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311468728:1(1117-1127)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1109/TVCG.2021.3114687
Alqahtani AAli MXie XJones M(2021)Deep Time-Series Clustering: A ReviewElectronics10.3390/electronics1023300110:23(3001)Online publication date: 2-Dec-2021
https://doi.org/10.3390/electronics10233001
Yaali JGrégoire VHurtut T(2021)HFTViz: Visualization for the exploration of high frequency trading dataInformation Visualization10.1177/1473871621106492121:2(182-193)Online publication date: 29-Dec-2021
https://doi.org/10.1177/14738716211064921
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten