Biblio
Effective features of algorithm visualizations. In: SIGCSE '04: Proceedings of the 35th SIGCSE technical symposium on Computer science education. SIGCSE '04: Proceedings of the 35th SIGCSE technical symposium on Computer science education. New York, NY, USA; 2004. p. 382–386. PDF (210.96 KB)
. The Effect of Semantic Interaction on Foraging in Text Analysis. In: 2018 IEEE Conference on Visual Analytics Science and Technology (VAST). 2018 IEEE Conference on Visual Analytics Science and Technology (VAST). ; 2018. p. . effect-semantic-interaction.pdf (1.43 MB)
. The Effect of Presenting Long Documents with Large High-Resolution Displays on Comprehension of Content and User Experience. In: the 13th International Symposium on Electronic Theses and Dissertations (ETD' 10). the 13th International Symposium on Electronic Theses and Dissertations (ETD' 10). Austin, TX; 2010. p. .
. The Effect of Edge Bundling and Seriation on Sensemaking of Biclusters in Bipartite Graphs. IEEE Transactions on Visualization and Computer Graphics. 2019;25(10):2983-2998. 08423100.pdf (5.86 MB)
. Dynamic query sliders vs. brushing histograms. In: CHI '03: CHI '03 extended abstracts on Human factors in computing systems. CHI '03: CHI '03 extended abstracts on Human factors in computing systems. New York, NY, USA; 2003. p. 834–835.
. Dynamic Analysis of Large Datasets with Animated and Correlated Views. In: IEEE VAST 2012 (Extended Abstract) (Honorable Mention for Good Use of Coordinated Displays). IEEE VAST 2012 (Extended Abstract) (Honorable Mention for Good Use of Coordinated Displays). ; 2012. p. . VAST2012Challenge 2page Abstract.pdf (2.01 MB)
. Dropping the Baton?: Understanding Errors and Bottlenecks in a Crowdsourced Sensemaking Pipeline. Proc. ACM Hum.-Comput. Interact. [Internet]. 2019;3:136:1–136:26. Available from: http://doi.acm.org/10.1145/3359238 cscw136-li.pdf (2.09 MB)
. Do we still need physical monitors? An evaluation of the usability of AR virtual monitors for productivity work. In: IEEE Virtual Reality and 3D User Interfaces (VR). IEEE Virtual Reality and 3D User Interfaces (VR). ; 2021. p. 759-767. IEEE VR 2021 Do_we_still_need_physical_monitors__An_evaluation_of_the_usability_of_AR_virtual_monitors_for_productivity_work.pdf (398.21 KB)
. Different realities: a comparison of augmented and virtual reality for the sensemaking process. Frontiers in Virtual Reality. 2023;4:16. frvir-04-1177855 copy.pdf (470.99 KB)
. Developing Large High-Resolution Display Visualizations of High-Fidelity Terrain Data. Journal of Computing and Information Science in Engineering [Internet]. 2013;13(3). Available from: http://dx.doi.org/10.1115/1.4024656 jcis_13_3_034502.pdf (2.1 MB) Ferris.pdf (5.48 MB)
. Designing Usable Interactive Visual Analytics Tools for Dimension Reduction. In: CHI 2016 Workshop on Human-Centered Machine Learning (HCML). CHI 2016 Workshop on Human-Centered Machine Learning (HCML). ; 2016. p. 7. Self_design_paper_final.pdf (626.44 KB)
. Designing large high-resolution display workspaces. In: Proceedings of the International Working Conference on Advanced Visual Interfaces. Proceedings of the International Working Conference on Advanced Visual Interfaces. New York, NY, USA; 2012. p. 58–65. Available from: http://doi.acm.org/10.1145/2254556.2254570 PDF.pdf (4.71 MB)
. Designing for Interactive Dimension Reduction Visual Analytics Tools to Explore High-Dimensional Data. Blacksburg; 2015 p. . jzself_vast2015_tech_report.pdf (3.65 MB)
. Designing Display Ecologies for Visual Analysis. Computer Science. 2015;Ph.D.
. Design guidelines for narrative maps in sensemaking tasks. Information Visualization. 2022:1-26. 14738716221079593 copy.pdf (903.83 KB)
. DeepVA: Bridging Cognition and Computation through Semantic Interaction and Deep Learning. In: Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. . Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS’19. . ; 2019. p. . MLUI_2019-2.pdf (8.51 MB)
. DeepSI: Interactive Deep Learning for Semantic Interaction. In: 26th International Conference on Intelligent User Interfaces (IUI ’21). 26th International Conference on Intelligent User Interfaces (IUI ’21). ; 2021. p. 197-207. IUI2021_DeepSI-2.pdf (1.9 MB)
. CrowdTrace: Visualizing Provenance in Distributed Sensemaking. In: IEEE VIS Short Papers. IEEE VIS Short Papers. ; 2020. p. 5 pages. CrowdTrace_VIS_Short_Paper_Submission-3.pdf (738.58 KB)
. Crowdsourcing Intelligence Analysis with Context Slices. In: CHI 2018 Workshop on Sensemaking in a Senseless World. CHI 2018 Workshop on Sensemaking in a Senseless World. ; 2018. p. . Connect_the_Dots_CHI 2018_sensemaking_final.pdf (927.85 KB)
. CrowdIA: Solving Mysteries with Crowdsourced Sensemaking. Proc. ACM Hum.-Comput. Interact. [Internet]. 2018;2. Available from: https://doi.org/10.1145/3274374 cscw105-liA.pdf (7.93 MB)
. Construction and Usage of the Semantic Interaction Pipeline. 2018:1-29. construction-usage-semantic.pdf (4.5 MB)
. Component-based, user-constructed, multiple-view visualization. In: CHI '01: CHI '01 extended abstracts on Human factors in computing systems. CHI '01: CHI '01 extended abstracts on Human factors in computing systems. New York, NY, USA; 2001. p. 201–202.
. A Comparison of User-Generated and Automatic Graph Layouts. IEEE Transactions on Visualization and Computer Graphics. 2009;15:961–968. PDF (2.16 MB)
. A Comparison of Two Display Models for Collaborative Sensemaking. In: Proceedings of the 2Nd ACM International Symposium on Pervasive Displays. Proceedings of the 2Nd ACM International Symposium on Pervasive Displays. New York, NY, USA; 2013. p. 37–42. Available from: http://doi.acm.org/10.1145/2491568.2491577 Merged-PerDis_0423-realFinal.pdf (1.61 MB)
. A comparison of benchmark task and insight evaluation methods for information visualization. Information Visualization. 2011;10(3):162 - 181. Information Visualization-2011-North-162-81.pdf (916.23 KB)
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