research-article

GraphTrail: analyzing large multivariate, heterogeneous networks while supporting exploration history

Authors:

Nathalie Henry Riche,

Ronald Metoyer,

George RobertsonAuthors Info & Claims

CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Pages 1663 - 1672

https://doi.org/10.1145/2207676.2208293

Published: 05 May 2012 Publication History

Abstract

Exploring large network datasets, such as scientific collaboration networks, is challenging because they often contain a large number of nodes and edges in several types and with multiple attributes. Analyses of such networks are often long and complex, and may require several sessions by multiple users. Therefore, it is often difficult for users to recall their own exploration history or share it with others. We introduce GraphTrail, an interactive visualization for analyzing networks through exploration of node and edge aggregates that captures users' interactions and integrates this history directly in the exploration workspace. To facilitate large network analysis, GraphTrail integrates aggregation with familiar charts, drag-and-drop interaction on a canvas, and a novel pivoting mechanism for transitioning between aggregates. Through a three-month field study with a team of archeologists and a qualitative lab study with ten users, we demonstrate the effectiveness of our design and the benefits of integrated exploration history, including analysis comprehension, insight discovery, and exploration recall.

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References

[1]

Abello, J. and van Ham, F. Matrix Zoom: a visual interface to semi-external graphs. Proc. InfoVis '04, (2004), 183--190.

Digital Library

[2]

Abello, J., van Ham, F., and Krishnan, N. ASKGraphView: a large scale graph visualization system. IEEE TVCG (InfoVis '06) 12, 5 (2006), 669--676.

Digital Library

[3]

Adar, E. GUESS: a language and interface for graph exploration. Proc. CHI '06, (2006), 791--800.

Digital Library

[4]

Batagelj, V. and Mrvar, A. Pajek - Program for large network analysis. Connections 21, (1998), 47--57.

[5]

Bavoil, L., Callahan, S. P., Crossno, P. J., Freire, J., Scheidegger, C. E., Silva, C. T., and Vo, H. T. VisTrails: enabling interactive multiple-view visualizations. Proc. VIS '05, (2005), 135--142.

[6]

Bezerianos, A., Chevalier, F, Dragicevic, P., Elmqvist, N., and Fekete, J.-D. GraphDice: a system for exploring multivariate social networks. Computer Graphics Forum 29, 3 (2010), 863--872.

Digital Library

[7]

Blaas, J., Botha, C., Grundy, E., Jones, M., Laramee, R., and Post, F. Smooth graphs for visual exploration of higher-order state transitions. IEEE TVCG (InfoVis '09) 15, 6 (2009), 969--976.

Digital Library

[8]

Dill, J., Bartram, L., Ho, A., and Henigman, F.A continuously variable zoom for navigating large hierarchical networks. Proc. SMC '94, (1994), 386--390.

[9]

Fekete, J.-D., Wang, D., Dang, N., Aris, A., and Plaisant, C. Overlaying graph links on treemaps. Posters compendium of InfoVis '03, (2003), 82--83.

[10]

Freire, M., Plaisant, C., Shneiderman, B., and Golbeck, J. ManyNets: an interface for multiple network analysis and visualization. Proc. CHI '10, (2010), 213--222.

Digital Library

[11]

Heer, J., Mackinlay, J. D., Stolte, C., and Agrawala, M. Graphical histories for visualization: supporting analysis, communication, and evaluation. IEEE TVCG (InfoVis '08) 14, 6 (2008), 1189--1196.

Digital Library

[12]

Henry, N. and Fekete, J.-D. MatrixExplorer: a dualrepresentation system to explore social networks. IEEE TVCG (InfoVis '06) 12, 5 (2006), 677--684.

Digital Library

[13]

Henry, N., Fekete, J.-D., and McGuffin, M. J. NodeTrix: a hybrid visualization of social networks. IEEE TVCG (InfoVis '07) 13, 6 (2007), 1302--1309.

Digital Library

[14]

Jankun-Kelly, T. J., Ma, K.-L., and Gertz, M. A model and framework for visualization exploration. IEEE TVCG 13, 2 (2007), 357--369.

Digital Library

[15]

Kadivar, N., Chen, V., Dunsmuir, D., Lee, E., Qian, C., Dill, J., Shaw, C., and Woodbury, R. Capturing and supporting the analysis process. Proc. VAST '09, (2009), 131--138.

[16]

Kang, H., Plaisant, C., Lee, B., and Bederson, B. NetLens: Iterative exploration of content-actor network data. Information Visualization 6, (2007), 18--31.

Digital Library

[17]

Kang, Y-a. and Stasko, J. Characterizing the intelligence analysis process: Informing visual analytics design through a longitudinal field study. Proc. VAST '11, (2011), 21--30.

[18]

Lee, B., Czerwinski, M., Robertson, G., and Bederson, B. Understanding research trends in conferences using PaperLens. Ext. Abstracts. CHI '05, (2005), 1969--1972.

Digital Library

[19]

Lee, B., Smith, G., Robertson, G. G., Czerwinski, M., and Tan, D. S. FacetLens: exposing trends and relationships to support sensemaking within faceted datasets. Proc. CHI '09, (2009), 1293--1302.

Digital Library

[20]

Lee, J. P. and Grinstein, G. An architecture for retaining and analyzing visual explorations of databases. Proc. Vis '95, (1995), 101--108.

Digital Library

[21]

Lipford, H. R., Stuke, F., Dou, W., Hawkins, M. E., and Chang, R. Helping users recall their reasoning process. Proc. VAST '10, (2010), 187--194.

[22]

North, C., Chang, R., Endert, A., Dou, W., May, R., Pike, B., and Fink, G. Analytic provenance: process + interaction + insight. Ext. Abst. CHI '11, (2011), 33--36.

Digital Library

[23]

Perer, A. and Shneiderman, B. Balancing systematic and flexible exploration of social networks. IEEE TVCG (InfoVis '06) 12, 5 (2006), 693--700.

Digital Library

[24]

Pretorius, A. J. and van Wijk, J. J. Visual analysis of multivariate state transition graphs. IEEE TVCG (InfoVis '06) 12, 5 (2006), 685--692.

Digital Library

[25]

Robertson, G., Czerwinski, M., Larson, K., Robbins, D. C., Thiel, D., and van Dantzich, M. Data Mountain: using spatial memory for document management. Proc. UIST '98, (1998), 153--162.

Digital Library

[26]

Roth, S. F., Lucas, P., Senn, J. A., Gomberg, C. C., Burks, M. B., Stroffolino, P. J., Kolojejchick, J. A., and Dunmire, C. Visage: a user interface environment for exploring information. Proc. InfoVis '96, (1996), 3--12.

Digital Library

[27]

Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., Amin, N., Schwikowski, B., and Ideker, T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 13, 11 (2003), 2498--2504.

[28]

Shneiderman, B. and Aris, A. Network visualization by semantic substrates. IEEE TVCG (InfoVis '06) 12, 5 (2006), 733--740.

Digital Library

[29]

Shrinivasan, Y. B. and van Wijk, J. J. Supporting the analytical reasoning process in information visualization. Proc. CHI '08, (2008), 1237--1246.

Digital Library

[30]

Stasko, J., Gorg, C., Liu, Z., and Singhal, K. Jigsaw: supporting investigative analysis through interactive visualization. Proc. VAST '07, (2007), 131--138.

Digital Library

[31]

Ware, C., Gilman, A. T., and Bobrow, R. J. Visual thinking with an interactive diagram. Proc. Diagrams '08, (2008), 118--126.

Digital Library

[32]

Wattenberg, M. Visual exploration of multivariate graphs. Proc. CHI '06, (2006), 811--819.

Digital Library

[33]

Zhao, S., Chignell, M. H., and McGuffin, M. J. Elastic hierarchies: combining treemaps and node-link diagrams. Proc. InfoVis '05, (2005), 57--64.

Digital Library

Cited By

Taghipour PRezaie MLevy MShermer TCarpendale S(2024)Supporting Exploration of Women’s Print History Project Data via Interactively Constructing Networks of InterestProceedings of the 2024 International Conference on Advanced Visual Interfaces10.1145/3656650.3656697(1-9)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3656650.3656697
Li ZChockchowwat SFang HSahu RThakurdesai SPridaphatrakun KPark YBarcelo PSanchez-Pi NMeliou ASudarshan S(2024)Demonstration of ElasticNotebook: Migrating Live Computational Notebook StatesCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654752(540-543)Online publication date: 9-Jun-2024
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Gao JWu JDing J(2024)Heterogeneous Graph CondensationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.336286336:7(3126-3138)Online publication date: Jul-2024
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Index Terms

GraphTrail: analyzing large multivariate, heterogeneous networks while supporting exploration history
1. Human-centered computing
  1. Human computer interaction (HCI)

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Published In

cover image ACM Conferences

CHI '12: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

May 2012

3276 pages

ISBN:9781450310154

DOI:10.1145/2207676

General Chair:
Joseph A. Konstan
University of Minnesota
,
Program Chairs:
Ed H. Chi
Google
,
Kristina Höök
Mobile Life at KTH

Copyright © 2012 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]

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Published: 05 May 2012

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CHI '12: CHI Conference on Human Factors in Computing Systems

May 5 - 10, 2012

Texas, Austin, USA

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Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

Taghipour PRezaie MLevy MShermer TCarpendale S(2024)Supporting Exploration of Women’s Print History Project Data via Interactively Constructing Networks of InterestProceedings of the 2024 International Conference on Advanced Visual Interfaces10.1145/3656650.3656697(1-9)Online publication date: 3-Jun-2024
https://dl.acm.org/doi/10.1145/3656650.3656697
Li ZChockchowwat SFang HSahu RThakurdesai SPridaphatrakun KPark YBarcelo PSanchez-Pi NMeliou ASudarshan S(2024)Demonstration of ElasticNotebook: Migrating Live Computational Notebook StatesCompanion of the 2024 International Conference on Management of Data10.1145/3626246.3654752(540-543)Online publication date: 9-Jun-2024
https://dl.acm.org/doi/10.1145/3626246.3654752
Gao JWu JDing J(2024)Heterogeneous Graph CondensationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.336286336:7(3126-3138)Online publication date: Jul-2024
https://doi.org/10.1109/TKDE.2024.3362863
Li ZGor PPrabhu RYu HMao YPark Y(2023)ElasticNotebook: Enabling Live Migration for Computational NotebooksProceedings of the VLDB Endowment10.14778/3626292.362629617:2(119-133)Online publication date: 1-Oct-2023
https://dl.acm.org/doi/10.14778/3626292.3626296
Zhang YEns BSatriadi KYang YGoodwin S(2023)Embodied Provenance for Immersive SensemakingProceedings of the ACM on Human-Computer Interaction10.1145/36264717:ISS(198-216)Online publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1145/3626471
Zhang YEns BSatriadi KYang YGoodwin S(2023)Defining Embodied Provenance for Immersive SensemakingExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585691(1-7)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585691
Hsuan Yuan CYu TPan JLin W(2023)Interactive Visual Exploration of Knowledge Graphs with Embedding-based GuidanceExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585596(1-8)Online publication date: 19-Apr-2023
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Pister APrieur CFekete J(2023)ComBiNet: Visual Query and Comparison of Bipartite Multivariate Dynamic Social NetworksComputer Graphics Forum10.1111/cgf.1473142:1(290-304)Online publication date: 26-Jan-2023
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Chakhchoukh MBoukhelifa NBezerianos A(2023)Understanding How In-Visualization Provenance Can Support Trade-Off AnalysisIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.317107429:9(3758-3774)Online publication date: 1-Sep-2023
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Walchshofer CHinterreiter AXu KStitz HStreit M(2023)Provectories: Embedding-Based Analysis of Interaction Provenance DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.313569729:12(4816-4831)Online publication date: Dec-2023
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