@conference {DOI357, title = {Evaluating Navigation and Comparison Performance of Computational Notebooks on Desktop and in Virtual Reality}, booktitle = {ACM CHI 2024}, year = {2024}, month = {05/2024}, pages = {15}, author = {Sungwon In and Eric Krokos and Whitley, Kirsten and North, Chris and Yang, Yalong} } @article {DOI351, title = {Multiple Monitors or Single Canvas? Evaluating Window Management and Layout Strategies on Virtual Displays}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {to appear}, year = {2024}, month = {12/2024}, author = {Leonardo Pavanatto Soares and Feiyu Lu and North, Chris and Bowman, Doug A.} } @conference {DOI10.1109/VDS60365.2023.00009, title = {Aardvark: Comparative Visualization of Data Analysis Scripts}, booktitle = {Symposium on Visualization in Data Science (VDS) at IEEE VIS}, year = {2023}, month = {10/2023}, pages = {30-38}, doi = {10.1109/VDS60365.2023.00009}, author = {Faust, Rebecca and C. Scheidegger and North, Chris} } @article {DOI10.3389/frvir.2023.1177855, title = {Different realities: a comparison of augmented and virtual reality for the sensemaking process}, journal = {Frontiers in Virtual Reality}, volume = {4}, year = {2023}, month = {08/2023}, pages = {16}, doi = {10.3389/frvir.2023.1177855}, author = {Lee Lisle and Kylie Davidson and Edward J.K. Gitre and North, Chris and Bowman, Doug A.} } @conference {DOI336, title = {Evaluating Differences in Insights from Interactive Dimensionality Reduction Visualizations through Complexity and Vocabulary}, booktitle = {International Conference on Information Visualization Theory and Applications (IVAPP)}, year = {2023}, month = {02/2023}, pages = {8 pages}, author = {Mia Taylor and Lata Kodali and House, Leanna and North, Chris} } @conference {DOI10.1109/ISMAR59233.2023.00086, title = {Evaluating the Feasibility of Predicting Information Relevance During Sensemaking with Eye Gaze Data}, booktitle = {2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}, year = {2023}, month = {10/2023}, pages = {713{\textendash}722}, doi = {10.1109/ISMAR59233.2023.00086}, author = {Tahmid, Ibrahim A. and Lee Lisle and Kylie Davidson and Whitley, Kirsten and North, Chris and Bowman, Doug A.} } @article {DOIhttps://doi.org/10.1007/s00138-023-01452-9, title = {Explainable interactive projections of images}, journal = {Machine Vision and Applications}, volume = {34}, number = {100}, year = {2023}, month = {09/2023}, doi = {https://doi.org/10.1007/s00138-023-01452-9}, author = {Huimin Han and Faust, Rebecca and Norambuena, Brian Felipe Keith and Jiayue Lin and Song Li and North, Chris} } @article {9894094, title = {Exploring the Evolution of Sensemaking Strategies in Immersive Space to Think}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {29}, year = {2023}, month = {12/2023}, pages = {5294-5307}, doi = {10.1109/TVCG.2022.3207357}, author = {Kylie Davidson and Lee Lisle and Whitley, Kirsten and Bowman, Doug A. and North, Chris} } @conference {DOI344, title = {Mixed Multi-Model Semantic Interaction for Graph-based Narrative Visualizations}, booktitle = {ACM Intelligent User Interfaces (IUI)}, year = {2023}, month = {03/2023}, author = {Brian Keith Norambuena and Tanu Mitra and North, Chris} } @article {DOI10.1109/MCSE.2023.3297753, title = {Reflecting on the Scalable Adaptive Graphics Environment Team{\textquoteright}s 20-Year Translational Research Endeavor in Digital Collaboration Tools}, journal = {Computing in Science \& Engineering}, volume = {25}, year = {2023}, month = {03/2023}, pages = {50-56}, doi = {10.1109/MCSE.2023.3297753}, author = {Mahdi Belcaid and Jason Leigh and North, Chris and Jesse Harden and et al} } @conference {DOI358, title = {SAGE3: Smart Amplified Group Environment}, booktitle = {Gateways 2023}, year = {2023}, month = {11/2023}, pages = {5}, author = {Roderick Tabalba and Nurit Kirshenbaum and Jesse Harden and Christman, Elizabeth and Mahdi Belcaid and North, Chris and Jason Leigh and et al.} } @conference {DOI10.1109/ISMAR59233.2023.00125, title = {Spaces to Think: A Comparison of Small, Large, and Immersive Displays for the Sensemaking Process}, booktitle = {IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}, year = {2023}, month = {10/2023}, pages = {1084-1093}, doi = {10.1109/ISMAR59233.2023.00125}, author = {Lee Lisle and Kylie Davidson and Leonardo Pavanatto Soares and Tahmid, Ibrahim A. and North, Chris and Bowman, Doug A.} } @article {DOIhttps://doi.org/10.1145/3584741, title = {A Survey on Event-Based News Narrative Extraction}, journal = {ACM Computing Surveys}, volume = {55}, number = {300}, year = {2023}, month = {07/2023}, pages = {39}, doi = {https://doi.org/10.1145/3584741}, author = {Norambuena, Brian Felipe Keith and Tanu Mitra and North, Chris} } @conference {DOI355, title = {There is no reason anybody should be using 1D anymore: Design and Evaluation of 2D Jupyter Notebooks}, booktitle = {Graphics Interface 2023}, year = {2023}, month = {05/2023}, pages = {12}, author = {Jesse Harden and Christman, Elizabeth and Nurit Kirshenbaum and Mahdi Belcaid and Jason Leigh and North, Chris} } @article {DOI10.1109/TVCG.2023.3299602, title = {This is the Table I Want! Interactive Data Transformation on Desktop and in Virtual Reality}, journal = {IEEE Transactions on Visualization and Computer Graphics}, year = {2023}, month = {07/2023}, pages = {17}, doi = {10.1109/TVCG.2023.3299602}, author = {Sungwon In and Tica Lin and North, Chris and Pfister, Hanspeter and Yang, Yalong} } @conference {DOI10.1109/ISMAR59233.2023.00126, title = {Uncovering Best Practices in Immersive Space to Think}, booktitle = {2023 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}, year = {2023}, month = {10/2023}, pages = {1094-1103}, doi = {10.1109/ISMAR59233.2023.00126}, author = {Kylie Davidson and Lee Lisle and Tahmid, Ibrahim A. and Whitley, Kirsten and North, Chris and Bowman, Doug A.} } @conference {asee_peer_41168, title = {Andromeda in the Classroom: Collaborative Data Analysis for 8th Grade Engineering Design}, booktitle = {2022 ASEE Annual Conference \& Exposition}, year = {2022}, note = {https://peer.asee.org/41168}, month = {08/2022}, publisher = {ASEE Conferences}, organization = {ASEE Conferences}, address = {Minneapolis, MN}, author = {Mia Taylor and Danny Mathieson and House, Leanna and North, Chris} } @conference {DOI342, title = {Case Study Comparison of Computational Notebook Platforms for Interactive Visual Analytics}, booktitle = {Proceedings of Symposium on Visualization in Data Science (VDS)}, year = {2022}, month = {10/2022}, author = {Han Liu and North, Chris} } @article {DOI10.1177/14738716221079593, title = {Design guidelines for narrative maps in sensemaking tasks}, journal = {Information Visualization}, year = {2022}, month = {03/2022}, pages = {1-26}, doi = {10.1177/14738716221079593}, author = {Brian Keith Norambuena and Tanu Mitra and North, Chris} } @conference {9995165, title = {Evaluating the Benefits of Explicit and Semi-Automated Clusters for Immersive Sensemaking}, booktitle = {2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)}, year = {2022}, pages = {479-488}, doi = {10.1109/ISMAR55827.2022.00064}, author = {Tahmid, Ibrahim A. and Lee Lisle and Kylie Davidson and North, Chris and Bowman, Doug A.} } @conference {10.1007/978-3-031-20713-6_6, title = {Explainable Interactive Projections For Image Data}, booktitle = {Advances in Visual Computing: 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3{\textendash}5, 2022, Proceedings, Part I}, year = {2022}, pages = {77{\textendash}90}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Berlin, Heidelberg}, abstract = {Making sense of large collections of images is difficult. Dimension reductions (DR) assist by organizing images in a 2D space based on similarities, but provide little support for explaining why images were placed together or apart in the 2D space. Additionally, they do not provide support for modifying and updating the 2D space to explore new relationships and organizations of images. To address these problems, we present an interactive DR method for images that uses visual features extracted by a deep neural network to project the images into 2D space and provides visual explanations of image features that contributed to the 2D location. In addition, it allows people to directly manipulate the 2D projection space to define alternative relationships and explore subsequent projections of the images. With an iterative cycle of semantic interaction and explainable-AI feedback, people can explore complex visual relationships in image data. Our approach to human-AI interaction integrates visual knowledge from both human mental models and pre-trained deep neural models to explore image data. We demonstrate our method through examples with collaborators in agricultural science.}, keywords = {Explainable AI, Image data, Interactive dimension reduction, Semantic interaction}, isbn = {978-3-031-20712-9}, doi = {10.1007/978-3-031-20713-6_6}, url = {https://doi.org/10.1007/978-3-031-20713-6_6}, author = {Huimin Han and Faust, Rebecca and Norambuena, Brian Felipe Keith and Prabhu, Ritvik and Smith, Timothy and Song Li and North, Chris} } @conference {9833128, title = {Exploring Organization of Computational Notebook Cells in 2D Space}, booktitle = {2022 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)}, year = {2022}, month = {09/2022}, pages = {1-6}, doi = {10.1109/VL/HCC53370.2022.9833128}, author = {Jesse Harden and Christman, Elizabeth and Nurit Kirshenbaum and Wenskovitch, John and Jason Leigh and North, Chris} } @conference {DOI326, title = {Interactive Deep Learning for Sorting Plant Images by Visual Phenotypes}, booktitle = {NAPPN Annual Conference}, year = {2022}, month = {02/2022}, pages = {5 pages}, author = {Huimin Han and Song Li and North, Chris} } @conference {9982307, title = {Interactive Visualization for Data Science Scripts}, booktitle = {2022 IEEE Visualization in Data Science (VDS)}, year = {2022}, month = {10/2022}, pages = {37-45}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, abstract = {As the field of data science continues to grow, so does the need for adequate tools to understand and debug data science scripts. Current debugging practices fall short when applied to a data science setting, due to the exploratory and iterative nature of analysis scripts. Additionally, computational notebooks, the preferred scripting environment of many data scientists, present additional challenges to understanding and debugging workflows, including the non-linear execution of code snippets. This paper presents Anteater, a trace-based visual debugging method for data science scripts. Anteater automatically traces and visualizes execution data with minimal analyst input. The visualizations illustrate execution and value behaviors that aid in understanding the results of analysis scripts. To maximize the number of workflows supported, we present prototype implementations in both Python and Jupyter. Last, to demonstrate Anteater\&$\#$x2019;s support for analysis understanding tasks, we provide two usage scenarios on real world analysis scripts.}, keywords = {behavioral sciences, codes, data science, Data visualization, debugging, prototypes, visualization}, doi = {10.1109/VDS57266.2022.00009}, url = {https://doi.ieeecomputersociety.org/10.1109/VDS57266.2022.00009}, author = {Faust, Rebecca and C. Scheidegger and K. Isaacs and W. Z. Bernstein and M. Sharp and North, Chris} } @article {DOI329, title = {Bridging cognitive gaps between user and model in interactive dimension reduction}, journal = {Visual Informatics}, volume = {53}, year = {2021}, pages = {13-25}, author = {Ming Wang and Wenskovitch, John and House, Leanna and Nicholas Polys and North, Chris} } @conference {DOIhttps://doi.org/10.1145/3397481.3450670, title = {DeepSI: Interactive Deep Learning for Semantic Interaction}, booktitle = {26th International Conference on Intelligent User Interfaces (IUI {\textquoteright}21)}, year = {2021}, month = {04/2021}, pages = {197-207}, doi = {https://doi.org/10.1145/3397481.3450670}, author = {Yali Bian and North, Chris} } @conference {DOI327, title = {Do we still need physical monitors? An evaluation of the usability of AR virtual monitors for productivity work}, booktitle = {IEEE Virtual Reality and 3D User Interfaces (VR)}, year = {2021}, pages = {759-767}, author = {Leonardo Pavanatto Soares and Doug Bowman and North, Chris and Carmen Badea and Rich Stoakley} } @article {DOI10.1109/TVCG.2020.3028890, title = {An Examination of Grouping and Spatial Organization Tasks for High-Dimensional Data Exploration}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {27}, year = {2021}, month = {1/2021}, pages = {1742-1752}, issn = {1077-2626}, doi = {10.1109/TVCG.2020.3028890}, author = {Wenskovitch, John and North, Chris} } @conference {DOI10.1109/VIS49827.2021.9623296, title = {Narrative Sensemaking: Strategies for Narrative Maps Construction}, booktitle = {IEEE Visualization Conference (VIS)}, year = {2021}, month = {10/2021}, pages = {181-185}, doi = {10.1109/VIS49827.2021.9623296}, author = {Brian Keith Norambuena and Tanu Mitra and North, Chris} } @conference {DOI10.1109/VIS49827.2021.9623322, title = {Semantic Explanation of Interactive Dimensionality Reduction}, booktitle = {IEEE Visualization Conference (VIS)}, year = {2021}, month = {10/2021}, pages = {5 pages}, doi = {10.1109/VIS49827.2021.9623322}, author = {Yali Bian and North, Chris and Eric Krokos and Sarah Joseph} } @conference {DOI10.1109/VR50410.2021.00077, title = {Sensemaking Strategies with Immersive Space to Think}, booktitle = {IEEE Virtual Reality and 3D User Interfaces (VR)}, year = {2021}, month = {03/2021}, pages = {529-537}, doi = {10.1109/VR50410.2021.00077}, author = {Lee Lisle and Kylie Davidson and Ed Gitre and North, Chris and Doug Bowman} } @conference {DOIhttps://doi.org/10.1145/3488552, title = {Traces of Time through Space: Advantages of Creating Complex Canvases in Collaborative Meetings}, booktitle = {Interactive Surfaces \& Spaces}, number = {502}, year = {2021}, month = {11/2021}, pages = {18 pages}, doi = {https://doi.org/10.1145/3488552}, author = {Nurit Kirshenbaum and Kylie Davidson and Jesse Harden and North, Chris and Jason Leigh} } @conference {DOI302, title = {Auto-Grading Jupyter Notebooks}, booktitle = {SIGCSE 2020}, year = {2020}, month = {03/2020}, author = {Hamza Manzoor and Amit Naik and Shaffer, Clifford A. and North, Chris and Stephen H. Edwards} } @conference {DOI319, title = {CrowdTrace: Visualizing Provenance in Distributed Sensemaking}, booktitle = {IEEE VIS Short Papers}, year = {2020}, month = {10/2020}, pages = {5 pages}, author = {Li, Tianyi and Belghith, Yasmine and North, Chris and Luther, Kurt} } @conference {lisle2020large, title = {Evaluating the Benefits of the Immersive Space to Think}, booktitle = {IEEE 6th Workshop on Everyday Virtual Reality (WEVR)}, series = {WEVR}, year = {2020}, month = {03/2020}, publisher = {IEEE}, organization = {IEEE}, author = {Lee Lisle and Xiaoyu Chen and Edward J.K. Gitre and North, Chris and Bowman, Doug A.} } @conference {DOI311, title = {Immersive Space to Think: The Role of 3D Space for Sensemaking}, booktitle = {4th Workshop on Immersive Analytics at ACM CHI 2020}, year = {2020}, month = {05/2020}, pages = {8 }, author = {Payel Bandyopadhyay and Lee Lisle and North, Chris and Bowman, Doug A. and Polys, Nicholas F.} } @article {9153297, title = {Interactive Artificial Intelligence: Designing for the "Two Black Boxes" Problem}, journal = {IEEE Computer}, volume = {53}, year = {2020}, month = {07/2020}, pages = {29-39}, doi = {10.1109/MC.2020.2996416}, author = {Wenskovitch, John and North, Chris} } @article {DOI10.1108/JEDT-05-2020-0161, title = {Modelling the Effect of Computation Sampling on Insight Error in Computational Fluid Dynamics Scientific Simulation}, journal = {Journal of Engineering, Design and Technology}, year = {2020}, month = {07/2020}, pages = {32}, doi = {10.1108/JEDT-05-2020-0161}, author = {Moeti M. Masiane and Eric Jacques and Wuchun Feng and North, Chris} } @conference {DOI324, title = {NetReAct: Interactive Learning for Network Summarization}, booktitle = {NeurIPS 2020 Workshop on Human and Model in the Loop Evaluation and Training Strategies (HAMLETS)}, year = {2020}, month = {12/2020}, author = {Amiri, Sorour and Adhikari, Bijaya and Wenskovitch, John and Rodriguez, Alexander and Michelle Dowling and North, Chris and Prakash, Aditya} } @conference {DOI315, title = {The Smart Amplified Group Environment}, booktitle = {4th Workshop on Immersive Analytics at ACM CHI 2020}, year = {2020}, month = {05/2020}, pages = {6}, author = {Nurit Kirshenbaum and Dylan Kobayashi and Mahdi Belcaid and Jason Leigh and Luc Renambot and Andrew Burks and Krishna Bharadwaj and Lance Long and Maxine Brown and Jason Haga and North, Chris} } @conference {10.1145/3377325.3377516, title = {With Respect to What? Simultaneous Interaction with Dimension Reduction and Clustering Projections}, booktitle = {Proceedings of the 25th International Conference on Intelligent User Interfaces}, series = {IUI {\textquoteright}20}, year = {2020}, month = {03/2020}, pages = {177{\textendash}188}, publisher = {Association for Computing Machinery}, organization = {Association for Computing Machinery}, address = {New York, NY, USA}, keywords = {clustering, dimension reduction, interaction, Visual Analytics}, isbn = {9781450371186}, doi = {10.1145/3377325.3377516}, url = {https://doi.org/10.1145/3377325.3377516}, author = {Wenskovitch, John and Michelle Dowling and North, Chris} } @conference {DOI294, title = {Albireo: An Interactive Tool for Visually Summarizing Computational Notebook Structure}, booktitle = {2019 Symposium on Visualization in Data Science (VDS{\textquoteright}19)}, year = {2019}, month = {10/2019}, author = {Wenskovitch, John and Zhao, Jian and Carter, Scott and Cooper, Matthew and North, Chris} } @conference {DOI287, title = {DeepVA: Bridging Cognition and Computation through Semantic Interaction and Deep Learning}, booktitle = {Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS{\textquoteright}19. }, year = {2019}, month = {10/2019}, author = {Yali Bian and Wenskovitch, John and North, Chris} } @article {Li:2019:DBU:3371885.3359238, title = {Dropping the Baton?: Understanding Errors and Bottlenecks in a Crowdsourced Sensemaking Pipeline}, journal = {Proc. ACM Hum.-Comput. Interact.}, volume = {3}, number = {CSCW}, year = {2019}, month = {11/2019}, pages = {136:1{\textendash}136:26}, publisher = {ACM}, address = {New York, NY, USA}, abstract = {Crowdsourced sensemaking has shown great potential for enabling scalable analysis of complex data sets, from planning trips, to designing products, to solving crimes. Yet, most crowd sensemaking approaches still require expert intervention because of worker errors and bottlenecks that would otherwise harm the output quality. Mitigating these errors and bottlenecks would significantly reduce the burden on experts, yet little is known about the types of mistakes crowds make with sensemaking micro-tasks and how they propagate in the sensemaking loop. In this paper, we conduct a series of studies with 325 crowd workers using a crowd sensemaking pipeline to solve a fictional terrorist plot, focusing on understanding why errors and bottlenecks happen and how they propagate. We classify types of crowd errors and show how the amount and quality of input data influence worker performance. We conclude by suggesting design recommendations for integrated crowdsourcing systems and speculating how a complementary top-down path of the pipeline could refine crowd analyses.}, keywords = {crowdsourcing, Intelligence Analysis, investigations, mysteries, sensemaking, text analytics}, issn = {2573-0142}, doi = {10.1145/3359238}, url = {http://doi.acm.org/10.1145/3359238}, author = {Li, Tianyi and Manns, Chandler J. and North, Chris and Luther, Kurt} } @article {DOI10.1109/TVCG.2018.2861397, title = {The Effect of Edge Bundling and Seriation on Sensemaking of Biclusters in Bipartite Graphs}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {25}, year = {2019}, month = {07/2019}, pages = {2983-2998}, abstract = {Exploring coordinated relationships (e.g., shared relationships between two sets of entities) is an important analytics task in a variety of real-world applications, such as discovering similarly behaved genes in bioinformatics, detecting malware collusions in cyber security, and identifying products bundles in marketing analysis. Coordinated relationships can be formalized as biclusters. In order to support visual exploration of biclusters, bipartite graphs based visualizations have been proposed, and edge bundling is used to show biclusters. However, it suffers from edge crossings due to possible overlaps of biclusters, and lacks in-depth understanding of its impact on user exploring biclusters in bipartite graphs. To address these, we propose a novel bicluster-based seriation technique that can reduce edge crossings in bipartite graphs drawing and conducted a user experiment to study the effect of edge bundling and this proposed technique on visualizing biclusters in bipartite graphs. We found that they both had impact on reducing entity visits for users exploring biclusters, and edge bundles helped them find more justified answers. Moreover, we identified four key trade-offs that inform the design of future bicluster visualizations. The study results suggest that edge bundling is critical for exploring biclusters in bipartite graphs, which helps to reduce low-level perceptual problems and support high-level inferences. }, keywords = {Bicluster, bicluster visualizations, bicluster-based seriation, Bioinformatics, Bipartite graph, bipartite graph based visualizations, data analysis, data visualisation, edge bundles, edge bundling, edge crossings, exploratory data analysis, graph theory, Image edge detection, Layout, pattern clustering, product bundles, seriation, Visual Analytics}, doi = {10.1109/TVCG.2018.2861397}, author = {Sun, Maoyuan and Zhao, Jian and Hao Wu and Luther, Kurt and North, Chris and Ramakrishnan, Naren} } @conference {DOI297, title = {Evaluating Semantic Interaction on Word Embeddings via Simulation}, booktitle = {EValuation of Interactive VisuAl Machine Learning systems, an IEEE VIS 2019 Workshop}, year = {2019}, month = {10/2019}, author = {Yali Bian and Michelle Dowling and North, Chris} } @article {10.3389/frobt.2019.00082, title = {Immersive Analytics: Theory and Research Agenda}, journal = {Frontiers in Robotics and AI}, volume = {6}, year = {2019}, month = {09/2019}, pages = {82}, abstract = {Advances in a variety of computing fields, including {\textquotedblleft}big data,{\textquotedblright} machine learning, visualization, and augmented/mixed/virtual reality, have combined to give rise to the emerging field of immersive analytics, which investigates how these new technologies support analysis and decision making. Thus far, we feel that immersive analytics research has been somewhat ad hoc, possibly owing to the fact that there is not yet an organizing framework for immersive analytics research. In this paper, we address this lack by proposing a definition for immersive analytics and identifying some general research areas and specific research questions that will be important for the development of this field. We also present three case studies that, while all being examples of what we would consider immersive analytics, present different challenges, and opportunities. These serve to demonstrate the breadth of immersive analytics and illustrate how the framework proposed in this paper applies to practical research.}, issn = {2296-9144}, doi = {10.3389/frobt.2019.00082}, url = {https://www.frontiersin.org/article/10.3389/frobt.2019.00082}, author = {Skarbez, Richard and Polys, Nicholas F. and Ogle, J. Todd and North, Chris and Bowman, Doug A.} } @conference {DOI300, title = {Interactive Bicluster Aggregation in Bipartite Graphs}, booktitle = {VIS 2019 Short Papers}, year = {2019}, month = {10/2019}, author = {Sun, Maoyuan and Koop, David and Zhao, Jian and North, Chris and Ramakrishnan, Naren} } @article {DOWLING201949, title = {Interactive Visual Analytics for Sensemaking with Big Text}, journal = {Big Data Research}, volume = {16}, year = {2019}, month = {July/2019}, pages = {49 - 58}, abstract = {Analysts face many steep challenges when performing sensemaking tasks on collections of textual information larger than can be reasonably analyzed without computational assistance. To scale up such sensemaking tasks, new methods are needed to interactively integrate human cognitive sensemaking activity with machine learning. Towards that goal, we offer a human-in-the-loop computational model that mirrors the human sensemaking process, and consists of foraging and synthesis sub-processes. We model the synthesis loop as an interactive spatial projection and the foraging loop as an interactive relevance ranking combined with topic modeling. We combine these two components of the sensemaking process using semantic interaction such that the human{\textquoteright}s spatial synthesis actions are transformed into automated foraging and synthesis of new relevant information. Ultimately, the model{\textquoteright}s ability to forage as a result of the analyst{\textquoteright}s synthesis activities makes interacting with big text data easier and more efficient, thereby facilitating analysts{\textquoteright} sensemaking ability. We discuss the interaction design and theory behind our interactive sensemaking model. The model is embodied in a novel visual analytics prototype called Cosmos in which analysts synthesize structure within the larger corpus by directly interacting with a reduced-dimensionality space to express relationships on a subset of data. We then demonstrate how Cosmos supports sensemaking tasks with a realistic scenario that investigates the affect of natural disasters in Adelaide, Australia in September 2016 using a database of over 30,000 news articles.}, keywords = {Big data, interactive visual analytics, Semantic interaction, text analytics, Topic modeling, visualization}, issn = {2214-5796}, doi = {https://doi.org/10.1016/j.bdr.2019.04.003}, url = {http://www.sciencedirect.com/science/article/pii/S2214579618302995}, author = {Michelle Dowling and Nathan Wycoff and Brian Mayer and Wenskovitch, John and Leman, Scotland and House, Leanna and Nicholas Polys and North, Chris and Peter Hauck} } @conference {DOI298, title = {Machine Learning from Interaction in Multi-Model Visual Analytics}, booktitle = {Proceedings of the ACM CHI Conference Workshop on Human-Centered Machine Learning Perspectives at CHI{\textquoteright}19.}, year = {2019}, month = {04/2019}, author = {Wenskovitch, John and North, Chris} } @conference {DOI296, title = {Machine Learning from User Interaction for Visualization and Analytics: A Workshop-Generated Research Agenda}, booktitle = {Proceedings of the IEEE VIS Workshop MLUI 2019: Machine Learning from User Interactions for Visualization and Analytics. VIS{\textquoteright}19.}, year = {2019}, month = {10/2019}, author = {Wenskovitch, John and Michelle Dowling and Grose, Laura and North, Chris and Chang, Remco and Endert, Alex and Rogers, David} } @conference {DOI293, title = {Pollux: Interactive Cluster-First Projections of High-Dimensional Data}, booktitle = {2019 Symposium on Visualization in Data Science (VDS{\textquoteright}19)}, year = {2019}, month = {10/2019}, author = {Wenskovitch, John and North, Chris} } @conference {Wenskovitch:2019:SID:3308557.3308718, title = {Simultaneous Interaction with Dimension Reduction and Clustering Projections}, booktitle = {Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion}, series = {IUI {\textquoteright}19}, year = {2019}, month = {03/2019}, pages = {89{\textendash}90}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {clustering, dimension reduction, interaction, Visual Analytics}, isbn = {978-1-4503-6673-1}, doi = {10.1145/3308557.3308718}, url = {http://doi.acm.org/10.1145/3308557.3308718}, author = {Wenskovitch, John and Michelle Dowling and North, Chris} } @article {doi:10.1080/0144929X.2019.1616223, title = {Towards insight-driven sampling for big data visualisation}, journal = {Behaviour \& Information Technology}, year = {2019}, month = {05/2019}, pages = {1-20}, publisher = {Taylor \& Francis}, doi = {10.1080/0144929X.2019.1616223}, url = {https://doi.org/10.1080/0144929X.2019.1616223}, author = {Moeti M. Masiane and Anne Driscoll and Wuchun Feng and Wenskovitch, John and North, Chris} } @proceedings {kodali2019uncertainty, title = {Uncertainty in Interactive WMDS Visualizations}, journal = {2019 Symposium on Visualization in Data Science Posters}, year = {2019}, address = {Vancouver, BC, Canada}, abstract = {Visualizations are useful when learning from high-dimensional data. However, visualizations can be misleading when they do not incorporate measures of uncertainty; e.g., uncertainty from the data or the dimension reduction algorithm used to create the visual display. In our work, we extend a framework called Bayesian Visual Analytics (BaVA) on a dimension reduction algorithm, Weighted Multidimensional Scaling (WMDS), to incorporate uncertainty as analysts explore data visually. BaVA-WMDS visualizations are interactive, and possible interactions include manipulating variable weights and/or the coordinates of the two-dimensional projection. Uncertainty exists in these visualizations on the variable weights, the user interactions, and the fit of WMDS. We quantify these uncertainties using Bayesian models exploring randomness in both coordinates and weights in a method we call Interactive Probabilistic WMDS (IP-WMDS). Specifically, we use posterior estimates to assess fit of WMDS, the range of motion of coordinates, as well as variability in weights. Visually, we display such uncertainty in the form of color and ellipses, and practically, these uncertainties reflect trust in fitting a dimension reduction algorithm. Our results show that these displays of uncertainty highlight different aspects of the visualization, which can help inform analysts.}, keywords = {poster}, author = {Lata Kodali and Wenskovitch, John and Nathan Wycoff and House, Leanna and North, Chris} } @article {DOI269, title = {Be the Data: Embodied Visual Analytics}, journal = {IEEE Transactions on Learning Technologies}, volume = {11}, year = {2018}, pages = {81-95}, doi = {10.1109/TLT.2017.2757481}, author = {Xin Chen and Self, Jessica Zeitz and House, Leanna and Wenskovitch, John and Sun, Maoyuan and Nathan Wycoff and Jane Robertson Evia and Leman, Scotland and North, Chris} } @conference {DOI282, title = {A Bidirectional Pipeline for Semantic Interaction}, booktitle = {VIS Workshop on Machine Learning from User Interaction for Visualization and Analytics}, year = {2018}, month = {10/2018}, author = {Michelle Dowling and Wenskovitch, John and Peter Hauck and Adam Binford and Nicholas Polys and North, Chris} } @conference {wenskovitch2018computational, title = {The Cognitive and Computational Benefits and Limitations of Clustering for Sensemaking}, booktitle = {CHI {\textquoteright}18 Workshop on Sensemaking in a Senseless World}, year = {2018}, month = {04/2018}, address = {Montreal, QC, Canada}, abstract = {The cognitive process of sensemaking refers to acquiring, representing, and organizing information in order to understand that information. The organization component naturally supports the introduction of clusters, an important enabler for grouping objects such that similar objects are placed in the same cluster. This paper explores the benefits and limitations of introducing clusters into systems for exploratory data analysis. We consider these issues for tasks that the system may support, methods for visualizing and interacting with data in the system, and algorithms that are encoded into the system. We discuss the use of clusters in these systems with respect to cognition and computation, and we call out future areas of research in this area.}, keywords = {clustering, exploratory data analysis, interaction, sensemaking, tasks, visualization}, author = {Wenskovitch, John and Michelle Dowling and North, Chris} } @unpublished {dowling2018construction, title = {Construction and Usage of the Semantic Interaction Pipeline}, year = {2018}, pages = {1-29}, publisher = {InfoVis Lab, Virginia Tech}, type = {Technical Report}, address = {Blacksburg, VA}, abstract = {Semantic interaction techniques in visual data analytics allow users to indirectly adjust model parameters by directly manipulating the visual output of the models. Many existing tools that support semantic interaction do so with a number of similar features, including using an underlying bidirectional pipeline, using a series of statistical models, and performing inverse computations to transform user interactions into model updates. We propose a visual analytics pipeline that captures these necessary features of semantic interactions. Our flexible, multi-model, bidirectional pipeline has modular functionality to enable rapid prototyping. This enables quick alterations to the type of data being visualized, models for transforming the data, semantic interaction methods, and visual encodings. To demonstrate how this pipeline can be used, we developed a series of applications that employ semantic interactions. We also discuss how the pipeline can be used or extended for future research on semantic interactions in visual analytics.}, author = {Michelle Dowling and Wenskovitch, John and Peter Hauck and Adam Binford and Theo Long and Nicholas Polys and North, Chris} } @article {10.1145/3274374, title = {CrowdIA: Solving Mysteries with Crowdsourced Sensemaking}, journal = {Proc. ACM Hum.-Comput. Interact.}, volume = {2}, number = {CSCW}, year = {2018}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, keywords = {crowdsourcing, Intelligence Analysis, investigation, mysteries, sensemaking, text analytics}, doi = {10.1145/3274374}, url = {https://doi.org/10.1145/3274374}, author = {Li, Tianyi and Luther, Kurt and North, Chris} } @conference {DOI304, title = {Crowdsourcing Intelligence Analysis with Context Slices}, booktitle = {CHI 2018 Workshop on Sensemaking in a Senseless World}, year = {2018}, month = {04/2018}, author = {Li, Tianyi and Asmita Shah and Luther, Kurt and North, Chris} } @conference {wenskovitch2018effect, title = {The Effect of Semantic Interaction on Foraging in Text Analysis}, booktitle = {2018 IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2018}, abstract = {Completing text analysis tasks is a continuous sensemaking loop of foraging for information and incrementally synthesizing it into hypotheses. Past research has shown the advantages of using spatial workspaces as a means for synthesizing information through externalizing hypotheses and creating spatial schemas. However, spatializing the entirety of datasets becomes prohibitive as the number of documents available to the analysts grows, particularly when only a small subset are relevant to the task at hand. StarSPIRE is a visual analytics tool designed to explore collections of documents, leveraging users{\textquoteright} semantic interactions to steer (1) a synthesis model that aids in document layout, and (2) a foraging model to automatically retrieve new relevant information. In contrast to traditional keyword search foraging (KSF), "semantic interaction foraging" (SIF) occurs as a result of the user{\textquoteright}s synthesis actions. To quantify the value of semantic interaction foraging, we use StarSPIRE to evaluate its utility for an intelligence analysis sensemaking task. Semantic interaction foraging accounted for 26\% of useful documents found, and it also resulted in increased synthesis interactions and improved sensemaking task performance by users in comparison to only using keyword search.}, author = {Wenskovitch, John and Lauren Bradel and Michelle Dowling and House, Leanna and North, Chris} } @article {DOI261, title = {Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models}, journal = {ACM Transactions on Knowledge Discovery from Data}, volume = {12}, number = {7}, year = {2018}, month = {02/2018}, doi = {10.1145/3047017}, author = {Hao Wu and Sun, Maoyuan and Peng Mi and Nikolaj Ta and North, Chris and Ramakrishnan, Naren} } @article {self2018observation, title = {Observation-Level and Parametric Interaction for High-Dimensional Data Analysis}, journal = {ACM Transactions on Interactive Intelligent Systems}, volume = {8}, year = {2018}, month = {07/2018}, doi = {10.1145/3158230}, author = {Self, Jessica Zeitz and Michelle Dowling and Wenskovitch, John and Ian Crandell and Ming Wang and House, Leanna and Leman, Scotland and North, Chris} } @conference {dowling2018sirius, title = {SIRIUS: Dual, Symmetric, Interactive Dimension Reductions}, booktitle = {2018 IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2018}, month = {Oct}, abstract = {Much research has been done regarding how to visualize and interact with observations and attributes of high-dimensional data for exploratory data analysis. From the analyst{\textquoteright}s perceptual and cognitive perspective, current visualization approaches typically treat the observations of the high-dimensional dataset very differently from the attributes. Often, the attributes are treated as inputs (e.g., sliders), and observations as outputs (e.g., projection plots), thus emphasizing investigation of the observations. However, there are many cases in which analysts wish to investigate both the observations and the attributes of the dataset, suggesting a symmetry between how analysts think about attributes and observations. To address this, we define SIRIUS (Symmetric Interactive Representations In a Unified System), a symmetric, dual projection technique to support exploratory data analysis of high-dimensional data. We provide an example implementation of SIRIUS and demonstrate how this symmetry affords additional insights.}, keywords = {attribute projection, dimension reduction, exploratory data analysis, observation projection, Semantic interaction}, author = {Michelle Dowling and Wenskovitch, John and J.T. Fry and Leman, Scotland and House, Leanna and North, Chris} } @article {DOI281, title = {Smooth, Efficient, and Interruptible Zooming and Panning}, journal = {IEEE Transactions on Visualization \& Computer Graphics }, year = {2018}, month = {To appear}, author = {Reach, Caleb and North, Chris} } @article {wenskovitch2018towards, title = {Towards a Systematic Combination of Dimension Reduction and Clustering in Visual Analytics}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {24}, number = {01}, year = {2018}, month = {01/2018}, pages = {131-141}, keywords = {Algorithm design and analysis, clustering, Clustering algorithms, Data visualization, Dimension reduction;algorithms, Manifolds, Partitioning algorithms, Visual Analytics, visualization}, issn = {1077-2626}, doi = {10.1109/TVCG.2017.2745258}, author = {Wenskovitch, John and Ian Crandell and Ramakrishnan, Naren and House, Leanna and Leman, Scotland and North, Chris} } @conference {DOI265, title = {Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills}, booktitle = {Proceedings of the 33rd Annual Consortium of Computing Sciences in Colleges (CCSC) Eastern Regional Conference}, year = {2017}, month = {10/2017}, pages = {10}, author = {Self, Jessica Zeitz and Self, Nathan and House, Leanna and Jane Robertson Evia and Leman, Scotland and North, Chris} } @conference {wenskovitch2017oli, title = {Observation-Level Interaction with Clustering and Dimension Reduction Algorithms}, booktitle = {Proceedings of the 2nd Workshop on Human-In-the-Loop Data Analytics}, series = {HILDA{\textquoteright}17}, year = {2017}, pages = {14:1{\textendash}14:6}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {data clustering, Observation-Level Interaction (OLI), Semantic interaction, sensemaking, Visual Analytics}, isbn = {978-1-4503-5029-7}, doi = {10.1145/3077257.3077259}, url = {http://doi.acm.org/10.1145/3077257.3077259}, author = {Wenskovitch, John and North, Chris} } @conference {DOI10.1109/HPCC-SmartCity-DSS.2017.2, title = {Portable Parallel Design of Weighted Multi-Dimensional Scaling for Real-Time Data Analysis}, booktitle = {2017 IEEE 19th International Conference on High Performance Computing and Communications}, year = {2017}, month = {12/2017}, doi = {10.1109/HPCC-SmartCity-DSS.2017.2}, author = {Dash, Sajal and Anshuman Verma and North, Chris and Feng, Wu-chun} } @article {DOI252, title = {AVIST: A GPU-Centric Design for Visual Exploration of Large Multidimensional Datasets}, journal = {Informatics}, volume = {3}, year = {2016}, month = {10/2016}, pages = {18}, publisher = {MDPI}, edition = {Special Issue on Information Visualization for Massive Data}, doi = {10.3390/informatics3040018}, url = {http://www.mdpi.com/2227-9709/3/4/18}, author = {Peng Mi and Sun, Maoyuan and Moeti Masiane and Yong Cao and North, Chris} } @conference {DOI251, title = {Be the Data: A New Approach for Immersive Analytics}, booktitle = {IEEE Virtual Reality 2016 Workshop on Immersive Analytics}, year = {2016}, month = {03/2016}, pages = {6}, author = {Xin Chen and Self, Jessica Zeitz and House, Leanna and North, Chris} } @conference {DOI245, title = {Be the Data: An Embodied Experience for Data Analytics}, booktitle = { 2016 Annual Meeting of the American Educational Research Association (AERA)}, year = {2016}, month = {04/2016}, pages = {20}, author = {Xin Chen and House, Leanna and Self, Jessica Zeitz and Leman, Scotland and Jane Robertson Evia and James Thomas Fry and North, Chris} } @conference {DOI248, title = {Be the Data: Social Meetings with Visual Analytics}, booktitle = {International Workshop on Visualization and Collaboration (VisualCol 2016)}, year = {2016}, month = {11/2016}, pages = {8}, author = {Xin Chen and Self, Jessica Zeitz and Sun, Maoyuan and House, Leanna and North, Chris} } @article {DOI10.1109/TVCG.2015.2467813, title = {BiSet: Semantic Edge Bundling with Biclusters for Sensemaking}, journal = {Visualization and Computer Graphics, IEEE Transactions on}, volume = {22}, year = {2016}, month = {01/2016}, pages = {310-319}, publisher = {IEEE}, abstract = {Identifying coordinated relationships is an important task in data analytics. For example, an intelligence analyst might want to discover three suspicious people who all visited the same four cities. Existing techniques that display individual relationships, such as between lists of entities, require repetitious manual selection and significant mental aggregation in cluttered visualizations to find coordinated relationships. In this paper, we present BiSet, a visual analytics technique to support interactive exploration of coordinated relationships. In BiSet, we model coordinated relationships as biclusters and algorithmically mine them from a dataset. Then, we visualize the biclusters in context as bundled edges between sets of related entities. Thus, bundles enable analysts to infer task-oriented semantic insights about potentially coordinated activities. We make bundles as first class objects and add a new layer, {\textquotedblleft}in-between{\textquotedblright}, to contain these bundle objects. Based on this, bundles serve to organize entities represented in lists and visually reveal their membership. Users can interact with edge bundles to organize related entities, and vice versa, for sensemaking purposes. With a usage scenario, we demonstrate how BiSet supports the exploration of coordinated relationships in text analytics.}, issn = {1077-2626}, doi = {10.1109/TVCG.2015.2467813}, author = {Sun, Maoyuan and Peng, Mi and North, Chris and Ramakrishnan, Naren} } @conference {DOI249, title = {Bridging the Gap between User Intention and Model Parameters for Data Analytics}, booktitle = {SIGMOD 2016 Workshop on Human-In-the-Loop Data Analytics (HILDA 2016)}, year = {2016}, month = {06/2016}, pages = {6}, author = {Self, Jessica Zeitz and Vinayagam, R.K. and James Thomas Fry and North, Chris} } @conference {DOI250, title = {Designing Usable Interactive Visual Analytics Tools for Dimension Reduction}, booktitle = {CHI 2016 Workshop on Human-Centered Machine Learning (HCML)}, year = {2016}, month = {05/2016}, pages = {7}, author = {Self, Jessica Zeitz and Hu, Xinran and House, Leanna and Leman, Scotland and North, Chris} } @article {DOI10.3390/informatics3040023 , title = {Interactive Graph Layout of a Million Nodes}, journal = {Informatics}, volume = {3}, year = {2016}, month = {12/2016}, pages = {23}, edition = {Special Issue on Information Visualization for Massive Data}, doi = {10.3390/informatics3040023 }, url = {http://www.mdpi.com/2227-9709/3/4/23}, author = {Peng Mi and Sun, Maoyuan and Moeti Masiane and Yong Cao and North, Chris} } @conference {DOI246, title = {Usability Challenges underlying Bicluster Interaction for Sensemaking}, booktitle = {CHI 2016 Workshop on Human Centred Machine Learning}, year = {2016}, month = {05/2016}, pages = {6 pages}, author = {Sun, Maoyuan and Peng Mi and Hao Wu and North, Chris and Ramakrishnan, Naren} } @article {DOI235, title = {Andromeda: Observation-Level and Parametric Interaction for Exploratory Data Analysis}, year = {2015}, institution = {Virginia Tech}, type = {Technical Report}, address = {Blacksburg}, abstract = {Exploring high-dimensional number of dimensions in datasets increases, it becomes harder to discover patterns and develop insights. Dimension reduction algorithms, such as multidimensional scaling, support data explorations by reducing datasets to two dimensions for visualization. Because these algorithms rely on underlying parameterizations, they may be tweaked to assess the data from multiple perspectives. Alas, tweaking can be difficult for users without a strong knowledge base of the underlying algorithms. We present Andromeda, an interactive visual analytics tool we developed to enable non-experts of statistical models to explore domain- specific, high-dimensional data. This application implements interactive weighted multidimensional scaling (WMDS) and allows for both parametric and observation- level interaction to provide in-depth data exploration. In this paper, we present the results of a controlled usability study assessing Andromeda. We focus on the comparison of parametric interaction, observation-level interaction and a combination of the two.}, author = {Self, Jessica Zeitz and House, Leanna and Leman, Scotland and North, Chris} } @conference {DOI10.1109/LDAV.2015.7348078, title = {Bandlimited OLAP cubes for interactive big data visualization}, booktitle = {Large Data Analysis and Visualization (LDAV), 2015 IEEE 5th Symposium on}, year = {2015}, month = {10/2015}, pages = {107-114}, publisher = {IEEE}, organization = {IEEE}, address = {Chicago, IL, USA}, abstract = {Visualizations backed by data cubes can scale to massive datasets while remaining interactive. However, the use of data cubes introduces artifacts, causing these visualizations to appear noisy at best and deceptive at worst. Moreover, data cubes highly constrain the space of possible visualizations. For example, a histogram backed by a data cube is constrained to have a bin width that is a multiple of the data cube bin size. Similarly, for dynamic queries backed by data cubes, query extents must be aligned with bin boundaries. We present bandlimited OLAP (online analytical processing) cubes (BLOCs), a technique that uses established tools from digital signal processing to generate interactive visualizations of very large datasets. Based on kernel density plots and Gaussian filtering, BLOCs suppress the artifacts that occur in data cubes and allow for a continuous range of zoom/pan positions and continuous dynamic queries.}, doi = {10.1109/LDAV.2015.7348078}, author = {Reach, Caleb and North, Chris} } @conference {DOI242, title = {Big Text Visual Analytics in Sensemaking}, booktitle = {IEEE International Symposium on Big Data Visual Analytics}, year = {2015}, month = {09/2015}, pages = {8 pages}, author = {Lauren Bradel and Nathan Wycoff and House, Leanna and North, Chris} } @article {DOI244, title = {Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills}, year = {2015}, institution = {Virginia Tech}, type = {Technical Report}, address = {Blacksburg}, abstract = {This paper addresses the use of visual analytics in education for teaching what we call cognitive dimensionality (CD) and other EDA skills. We present the concept of CD to characterize students{\textquoteright} capacity for making dimensionally complex insights from data. Using this concept, we build a vocabulary and methodology to support a student{\textquoteright}s progression in terms of growth from low cognitive dimensionality (LCD) to high cognitive dimensionality (HCD). Crucially, students do not need high-level math skills to develop HCD. Rather, we use our own tool called Andromeda that enables human-computer interaction with a common, easy to interpret visualization method called Weighted Multidimensional Scaling (WMDS) to promote the idea of making high-dimensional insights. In this paper, we present Andromeda and report findings from a series of classroom assignments to 18 graduate students. These assignments progress from spreadsheet manipulations to statistical software such as R and finally to the use of Andromeda. In parallel with the assignments, we saw students{\textquoteright} CD begin low and improve.}, keywords = {dimension reduction, education, multidimensional scaling, multivariate analysis, Visual Analytics}, author = {Self, Jessica Zeitz and Self, Nathan and House, Leanna and Jane Robertson Evia and Leman, Scotland and North, Chris} } @article {DOI241, title = {Designing for Interactive Dimension Reduction Visual Analytics Tools to Explore High-Dimensional Data}, year = {2015}, institution = {Virginia Tech}, type = {Technical Report}, address = {Blacksburg}, abstract = {Exploring high-dimensional data is challenging. As the number of dimensions in datasets increases, the harder it becomes to discover patterns and develop insights. Dimension reduction algorithms, such as multidimensional scaling, support data explorations by reducing datasets to two dimensions for visualization. Because these algorithms rely on underlying parameterizations, they may be tweaked to assess the data from multiple perspectives. Alas, tweaking can be difficult for users without a strong knowledge base of the underlying algorithms. In this paper, we present principles for developing interactive visual analytic systems that enable users to tweak model parameters directly or indirectly so that they may explore high-dimensional data. To exemplify our principles, we introduce an application that implements interactive weighted multidimensional scaling (WMDS). Our application, Andromeda, allows for both parametric and object-level interaction to provide in-depth data exploration. In this paper, we describe the types of tasks and insights that users may gain with Andromeda. Also, the final version of Andromeda is the result of sequential improvements made to multiple designs that were critiqued by users. With each critique we uncovered design principles of effective, interactive, visual analytic tools. These design principles focus on three main areas: (1) layout, (2) semantically visualizing parameters, and (3) designing the communication between the interface and the algorithm.}, author = {Self, Jessica Zeitz and Hu, Xinran and House, Leanna and Leman, Scotland and North, Chris} } @conference {DOI10.1109/VAST.2015.7347628, title = {Four considerations for supporting visual analysis in display ecologies}, booktitle = {Visual Analytics Science and Technology (VAST), 2015 IEEE Conference on}, year = {2015}, month = {10/2015}, pages = {33-40}, publisher = {IEEE}, organization = {IEEE}, address = {Chicago, IL, USA}, abstract = {The current proliferation of large displays and mobile devices presents a number of exciting opportunities for visual analytics and information visualization. The display ecology enables multiple displays to function in concert within a broader technological environment to accomplish visual analysis tasks. Based on a comprehensive survey of multi-display systems from a variety of fields, we propose four key considerations for visual analysis in display ecologies: 1) Display Composition, 2) Information Coordination/Transfer, 3) Information Connection, and 4) Display Membership. Different aspects of display ecologies stemming from these design considerations will enable users to transform and empower multiple displays as a display ecology for visual analysis.}, doi = {10.1109/VAST.2015.7347628}, author = {Chung, Haeyong and North, Chris and Joshi, Sarang and Chen, Jian} } @article {DOI268, title = {Semantic Interaction: Coupling Cognition and Computation through Usable Interactive Analytics}, journal = {IEEE Computer Graphics and Applications}, year = {2015}, month = {07/2015}, pages = {6-11}, author = {Endert, Alex and Chang, Remco and North, Chris and Zhou, Michelle} } @conference {Zhang:2015:VTC:2713579.2713583, title = {Visualizing Traffic Causality for Analyzing Network Anomalies}, booktitle = {Proceedings of the 2015 ACM International Workshop on Security and Privacy Analytics}, series = {IWSPA {\textquoteright}15}, year = {2015}, pages = {37{\textendash}42}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {anomaly detection, information visualization, network traffic analysis, usable security, visual locality}, isbn = {978-1-4503-3341-2}, doi = {10.1145/2713579.2713583}, url = {http://doi.acm.org/10.1145/2713579.2713583}, author = {Zhang, Hao and Sun, Maoyuan and Yao, Danfeng and North, Chris} } @article {Rohrdantz11042013, title = {Augmenting the educational curriculum with the Visual Analytics Science and Technology Challenge: Opportunities and pitfalls}, journal = {Information Visualization}, volume = {13}, year = {2014}, pages = {313-325}, abstract = {With its mission to move science into practice, the Visual Analytics Science and Technology Challenge has become an integrated part of the annual Visual Analytics Science and Technology Conference since its inception in 2006. In this article, we discuss how we can transfer this objective into a classroom setting by using the Visual Analytics Science and Technology Challenge datasets and by encouraging student submissions to the challenge. By means of Bloom{\textquoteright}s Taxonomy of Educational Objectives for Knowledge-Based Goals, we show how the Visual Analytics Science and Technology Challenge enables the integration of additional learning objectives into two types of courses: a dedicated course that focuses on the contest participation and an integrated course that uses the contest data to emphasize practical course elements. The core contribution of this article is that we assess the opportunities and pitfalls that we experienced at the University of Konstanz in Germany and Virginia Tech in the United States when augmenting the educational curriculum with the Visual Analytics Science and Technology Challenge.}, doi = {10.1177/1473871613481693}, author = {Rohrdantz, Christian and Mansmann, Florian and North, Chris and Keim, Daniel A} } @conference {Wang2014a, title = {Event-Based Text Visual Analytics}, booktitle = {VAST Challenge 2014}, year = {2014}, address = {Paris, France}, abstract = {We present an event-based approach for solving a directed sensemaking task in which we combine powerful information foraging tools with intuitive synthesis spaces to solve the VAST 2014 Mini-Challenge 1 (MC1). A combination of student-created and commericially available software are used to solve various aspects of the scenario. In addition to applying entitiy extraction and topic modelling, we enable the user to explore a large dataset using multi-model semantic interaction, which infers analytical reasoning from user actions to augment the data spatialization and determine what information should be presented and suggested to the user. Additionally, we visualize extracted topics using Tableau to construct a timeline of events surrounding the questions posed by the challen}, keywords = {event extraction, Semantic interaction, sensemaking, topic modelling}, author = {Wang, Ji and Lauren Bradel and North, Chris} } @article {DOI10.1007/s10844-014-0304-9, title = {The human is the loop: new directions for visual analytics}, journal = {Journal of Intelligent Information Systems}, volume = {43}, year = {2014}, pages = {411-435}, publisher = {Springer US}, abstract = {Visual analytics is the science of marrying interactive visualizations and analytic algorithms to support exploratory knowledge discovery in large datasets. We argue for a shift from a {\textquoteleft}human in the loop{\textquoteright} philosophy for visual analytics to a {\textquoteleft}human is the loop{\textquoteright} viewpoint, where the focus is on recognizing analysts{\textquoteright} work processes, and seamlessly fitting analytics into that existing interactive process. We survey a range of projects that provide visual analytic support contextually in the sensemaking loop, and outline a research agenda along with future challenges.}, keywords = {clustering, Semantic interaction, Spatialization, Storytelling, Visual Analytics}, issn = {0925-9902}, doi = {10.1007/s10844-014-0304-9}, author = {Endert, Alex and Hossain, M. Shahriar and Ramakrishnan, Naren and North, Chris and Fiaux, Patrick and Andrews, Christopher} } @article {DOI228, title = {Improving Students{\textquoteright} Cognitive Dimensionality through Education with Object-Level Interaction}, year = {2014}, institution = {Virginia Tech}, type = {Technical Report}, address = {Blacksburg}, abstract = {This paper addresses the use of visual analytics techniques in education to advance students{\textquoteright} cognitive dimensionality. Students naturally tend to characterize data in simplistic one dimensional terms using metrics such as mean, median, mode. Real- world data, however, is more complex and students need to learn to recognize and create high-dimensional arguments. Data exploration methods can encourage thinking beyond traditional one dimensional insights. In particular, visual analytics tools that afford object-level interaction (OLI) allow for generation of more complex insights, despite inexperience with multivariate data. With these tools, students{\textquoteright} insights are of higher complexity in terms of dimensionality and cardinality and built on more diverse interactions. We present the concept of cognitive dimensionality to characterize students{\textquoteright} capacity for dimensionally complex insights. Using this concept, we build a vocabulary and methodology to support a student{\textquoteright}s progression in terms of growth from low to high cognitive dimensionality. We report findings from a series of classroom assignments with increasingly complex analysis tools. These assignments progressed from spreadsheet manipulations to statistical software such as R and finally to an OLI application, Andromeda. Our findings suggest that students{\textquoteright} cognitive dimensionality can be improved and further research on the impact of visual analytics tools on education for cognitive dimensionality is warranted.}, keywords = {multivariate data analysis, object level interaction, Visual Analytics}, author = {Self, Jessica Zeitz and Self, Nathan and House, Leanna and Leman, Scotland and North, Chris} } @conference {Wang2014b, title = {Making Sense of Daily Life Data: From Commonalities To Anomalies}, booktitle = {VAST Challenge 2014}, year = {2014}, abstract = {We report the approach and results to solve the VAST 2014 Mini-Challenge 2 (MC2). Based on the commercial interactive visualization software Tableau, we follow the notional model of sensemaking loop for analysis of the massive multi-dimensional, multi-source and time-varying data sets in MC2. Our findings show that we can effectively identify the commonalities and anomalies to understand the GAStech employees{\textquoteright} daily life.}, keywords = {Geo-visualization, human information interaction, Intelligence Analysis, sense-makingloop, visualanalysis}, author = {Wang, Ji and Peng Mi and North, Chris} } @conference {Wang:2014:RSW:2619648.2619674, title = {ReCloud: Semantics-based Word Cloud Visualization of User Reviews}, booktitle = {Proceedings of the 2014 Graphics Interface Conference}, series = {GI {\textquoteright}14}, year = {2014}, pages = {151{\textendash}158}, publisher = {Canadian Information Processing Society}, organization = {Canadian Information Processing Society}, address = {Toronto, Ont., Canada, Canada}, isbn = {978-1-4822-6003-8}, url = {http://dl.acm.org/citation.cfm?id=2619648.2619674}, author = {Wang, Ji and Zhao, Jian and Guo, Sheng and North, Chris and Ramakrishnan, Naren} } @conference {DOI219, title = {StarSpire: Multi-Model Semantic Interaction for Text Analytics}, booktitle = {IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2014}, pages = {1-10}, publisher = {IEEE}, organization = {IEEE}, address = {Paris, France}, abstract = {Semantic interaction offers an intuitive communication mechanism between human users and complex statistical models. By shielding the users from manipulating model parameters, they focus instead on directly manipulating the spatialization, thus remaining in their cognitive zone. However, this technique is not inherently scalable past hundreds of text documents. To remedy this, we present the concept of multi-model semantic interaction, where semantic interactions can be used to steer multiple models at multiple levels of data scale, enabling users to tackle larger data problems. We also present an updated visualization pipeline model for generalized multi-model semantic interaction. To demonstrate multi-model semantic interaction, we introduce StarSPIRE, a visual text analytics prototype that transforms user interactions on documents into both small-scale display layout updates as well as large-scale relevancy-based document selection.}, author = {Lauren Bradel and North, Chris and House, Leanna and Leman, Scotland} } @article {Chung_2014, title = {A Survey of Software Frameworks for Cluster-Based Large High-Resolution Displays}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {20}, number = {8}, year = {2014}, month = {8/2014}, pages = {1158{\textendash}1177}, publisher = {Institute of Electrical {\&} Electronics Engineers (${\l}brace$IEEE$\rbrace$)}, doi = {10.1109/TVCG.2013.272}, author = {Chung, Haeyong and Andrews, Christopher and North, Chris} } @conference {DOI215, title = {Toward Usable Interactive Analytics: Coupling Cognition and Computation}, booktitle = {KDD 2014 Workshop on Interactive Data Exploration and Analytics (IDEA)}, year = {2014}, url = {http://poloclub.gatech.edu/idea2014/papers/p52-endert.pdf}, author = {Endert, Alex and North, Chris and Chang, Remco and Zhou, Michelle} } @article {DOI10.1007/s00779-013-0727-2, title = {VisPorter: facilitating information sharing for collaborative sensemaking on multiple displays}, journal = {Personal and Ubiquitous Computing}, volume = {18}, year = {2014}, month = {6/2014}, pages = {1169{\textendash}1186}, publisher = {Springer London}, keywords = {collaborative sensemaking, Display ecology, multiple displays, text analytics, Visual Analytics}, issn = {1617-4909}, doi = {10.1007/s00779-013-0727-2}, url = {http://dx.doi.org/10.1007/s00779-013-0727-2}, author = {Chung, Haeyong and North, Chris and Self, Jessica Zeitz and Chu, Sharon and Francis Quek} } @conference {DOI10.1109/ISI.2013.6578831, title = {Auto-Highlighter: Identifying Salient Sentences in Text}, booktitle = {2013 IEEE International Conference on Intelligence and Security Informatics (ISI)}, year = {2013}, month = {6/2013}, pages = {260 - 262}, publisher = {IEEE}, organization = {IEEE}, address = {Seattle, WA, USA}, isbn = {978-1-4673-6214-6}, doi = {10.1109/ISI.2013.6578831}, author = {Self, Jessica Zeitz and Zeitz, Rebecca and North, Chris and Breitler, Alan L.} } @article {DOI10.1109/MCG.2013.53, title = {Beyond Control Panels: Direct Manipulation for Visual Analytics}, journal = {IEEE Computer Graphics and Applications}, volume = {33}, year = {2013}, month = {07/2013}, pages = {6 - 13}, issn = {0272-1716}, doi = {10.1109/MCG.2013.53}, author = {Endert, Alex and Lauren Bradel and North, Chris} } @article {DOI10.1109/MC.2013.269, title = {Bixplorer: Visual Analytics with Biclusters}, journal = {Computer}, volume = {46}, year = {2013}, month = {08/2013}, pages = {90 - 94}, issn = {0018-9162}, doi = {10.1109/MC.2013.269}, author = {Fiaux, Patrick and Sun, Maoyuan and Lauren Bradel and North, Chris and Ramakrishnan, Naren and Endert, Alex} } @conference {Chung:2013:CTD:2491568.2491577, title = {A Comparison of Two Display Models for Collaborative Sensemaking}, booktitle = {Proceedings of the 2Nd ACM International Symposium on Pervasive Displays}, series = {PerDis {\textquoteright}13}, year = {2013}, pages = {37{\textendash}42}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {collaborative sensemaking, Display ecology, multiple displays, Visual Analytics}, isbn = {978-1-4503-2096-2}, doi = {10.1145/2491568.2491577}, url = {http://doi.acm.org/10.1145/2491568.2491577}, author = {Chung, Haeyong and Chu, Sharon Lynn and North, Chris} } @article {DOI208, title = {Developing Large High-Resolution Display Visualizations of High-Fidelity Terrain Data}, journal = {Journal of Computing and Information Science in Engineering}, volume = {13}, year = {2013}, note = {10.1115/1.4024656}, month = {2013/07/22}, chapter = {034502}, abstract = {The vehicle terrain measurement system (VTMS) allows highly detailed terrain modeling and vehicle simulations. Visualization of large-scale terrain datasets taken from VTMS provides better insights into the characteristics of the pavement or road surface. However, the resolution of these terrain datasets greatly exceeds the capability of traditional graphics displays and computer systems. Large high-resolution displays (LHRDs) enable visualization of large-scale VTMS datasets with high resolution, large physical size, scalable rendering performance, advanced interaction methods, and collaboration. This paper investigates beneficial factors, implementation issues, and case study applications of LHRDs for visualizing large, high-fidelity, terrain datasets from VTMS. Two prototype visualizations are designed and evaluated with automotive and pavement engineers to demonstrate effectiveness of LHRDs for multiscale tasks that involve understanding pavement surface details within the overall context of the terrain.}, isbn = {1530-9827}, url = {http://dx.doi.org/10.1115/1.4024656}, author = {Chung, Haeyong and North, Chris and Ferris, John} } @conference {Wang:2013:FWC:2468356.2468673, title = {Fisheye Word Cloud for Temporal Sentiment Exploration}, booktitle = {CHI {\textquoteright}13 Extended Abstracts on Human Factors in Computing Systems}, series = {CHI EA {\textquoteright}13}, year = {2013}, pages = {1767{\textendash}1772}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {sentiment analysis, temporal twitter data analysis, user study, word cloud}, isbn = {978-1-4503-1952-2}, doi = {10.1145/2468356.2468673}, url = {http://doi.acm.org/10.1145/2468356.2468673}, author = {Wang, Ji and Dent, Kyle and North, Chris} } @conference {DOI10.1109/ISI.2013.6578780, title = {How analysts cognitively {\textquotedblleft}connect the dots{\textquotedblright}}, booktitle = {2013 IEEE International Conference on Intelligence and Security Informatics (ISI)}, year = {2013}, month = {6/2013}, pages = {24 - 26}, publisher = {IEEE}, organization = {IEEE}, address = {Seattle, WA, USA}, isbn = {978-1-4673-6214-6}, doi = {10.1109/ISI.2013.6578780}, author = {Lauren Bradel and Self, Jessica Zeitz and Endert, Alex and Hossain, M. Shahriar and North, Chris and Ramakrishnan, Naren} } @article {DOI10.1109/TVCG.2013.205, title = {The Impact of Physical Navigation on Spatial Organization for Sensemaking}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {19}, year = {2013}, month = {12/2013}, pages = {2207 - 2216}, issn = {1077-2626}, doi = {10.1109/TVCG.2013.205}, author = {Andrews, Christopher and North, Chris} } @article {DOI10.1016/j.ijhcs.2013.07.004, title = {Large High Resolution Displays for Co-Located Collaborative Sensemaking: Display Usage and Territoriality}, journal = {International Journal of Human-Computer Studies}, volume = {71}, year = {2013}, month = {11/2013}, pages = {1078-1088}, issn = {10715819}, doi = {10.1016/j.ijhcs.2013.07.004}, author = {Lauren Bradel and Endert, Alex and Koch, Kristen and Andrews, Christopher and North, Chris} } @article {DOI10.1109/TVCG.2013.188, title = {Semantics of Directly Manipulating Spatializations}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {19}, year = {2013}, month = {12/2013}, pages = {2052 - 2059}, issn = {1077-2626}, doi = {10.1109/TVCG.2013.188}, author = {Hu, Xinran and Lauren Bradel and Maiti, Dipayan and House, Leanna and North, Chris and Leman, Scotland} } @article {DOI10.1371/journal.pone.0050474, title = {Visual to Parametric Interaction (V2PI)}, journal = {PLoS ONE}, volume = {8}, year = {2013}, month = {03/2013}, pages = {e50474}, abstract = {Typical data visualizations result from linear pipelines that start by characterizing data using a model or algorithm to reduce the dimension and summarize structure, and end by displaying the data in a reduced dimensional form. Sensemaking may take place at the end of the pipeline when users have an opportunity to observe, digest, and internalize any information displayed. However, some visualizations mask meaningful data structures when model or algorithm constraints (e.g., parameter specifications) contradict information in the data. Yet, due to the linearity of the pipeline, users do not have a natural means to adjust the displays. In this paper, we present a framework for creating dynamic data displays that rely on both mechanistic data summaries and expert judgement. The key is that we develop both the theory and methods of a new human-data interaction to which we refer as {\textquotedblleft} Visual to Parametric Interaction{\textquotedblright} (V2PI). With V2PI, the pipeline becomes bi-directional in that users are embedded in the pipeline; users learn from visualizations and the visualizations adjust to expert judgement. We demonstrate the utility of V2PI and a bi-directional pipeline with two examples.}, doi = {10.1371/journal.pone.0050474}, author = {Leman, Scotland and House, Leanna and Maiti, Dipayan and Endert, Alex and North, Chris} } @conference {DOI10.1109/VAST.2012.6400559, title = {Analyst{\textquoteright}s Workspace: An embodied sensemaking environment for large, high-resolution displays}, booktitle = {2012 IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2012}, pages = {123 - 131}, publisher = {IEEE}, organization = {IEEE}, address = {Seattle, WA, USA}, abstract = {Distributed cognition and embodiment provide compelling models for how humans think and interact with the environment. Our examination of the use of large, high-resolution displays from an embodied perspective has lead directly to the development of a new sensemaking environment called Analyst{\textquoteright}s Workspace (AW). AW leverages the embodied resources made more accessible through the physical nature of the display to create a spatial workspace. By combining spatial layout of documents and other artifacts with an entity-centric, explorative investigative approach, AW aims to allow the analyst to externalize elements of the sensemaking process as a part of the investigation, integrated into the visual representations of the data itself. In this paper, we describe the various capabilities of AW and discuss the key principles and concepts underlying its design, emphasizing unique design principles for designing visual analytic tools for large, high-resolution displays.}, isbn = {978-1-4673-4752-5}, doi = {10.1109/VAST.2012.6400559}, author = {Andrews, Christopher and North, Chris} } @conference {Endert:2012:DLH:2254556.2254570, title = {Designing large high-resolution display workspaces}, booktitle = {Proceedings of the International Working Conference on Advanced Visual Interfaces}, series = {AVI {\textquoteright}12}, year = {2012}, pages = {58{\textendash}65}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {Large, high-resolution displays have enormous potential to aid in scenarios beyond their current usage. Their current usages are primarily limited to presentations, visualization demonstrations, or conducting experiments. In this paper, we present a new usage for such systems: an everyday workspace. We discuss how seemingly small large-display design decisions can have significant impacts on users{\textquoteright} perceptions of these workspaces, and thus the usage of the space. We describe the effects that various physical configurations have on the overall usability and perception of the display. We present conclusions on how to broaden the usage scenarios of large, high-resolution displays to enable frequent and effective usage as everyday workspaces while still allowing transformation to collaborative or presentation spaces.}, keywords = {large high-resolution displays}, isbn = {978-1-4503-1287-5}, doi = {10.1145/2254556.2254570}, url = {http://doi.acm.org/10.1145/2254556.2254570}, author = {Endert, Alex and Lauren Bradel and Zeitz, Jessica and Andrews, Christopher and North, Chris} } @conference {DOI140, title = {Dynamic Analysis of Large Datasets with Animated and Correlated Views}, booktitle = {IEEE VAST 2012 (Extended Abstract) (Honorable Mention for Good Use of Coordinated Displays)}, year = {2012}, abstract = {In this paper, we introduce a GPU-accelerated visual analytics tool, AVIST. By adopting the in-situ visualization architecture on the GPUs, AVIST supports real-time data analysis and visualization of massive scale datasets, such as VAST 2012 Challenge dataset. The design objective of the tool is to identify temporal patterns from large and complex data. To achieve this goal, we introduce three unique features: automatic animation, disjunctive data filters, and time-synced visualization of multiple datasets.}, author = {Yong Cao and Reese Moore and Peng Mi and Endert, Alex and North, Chris and Randy Marchany} } @unpublished {Wang2012, title = {{GreenVis : Energy-Saving Color Schemes for Sequential Data Visualization on OLED Displays}}, year = {2012}, pages = {8}, publisher = {Department of Computer Science, Virginia Tech}, address = {Blacskburg, VA}, keywords = {color scheme, energy saving, oled display, optimization}, url = {http://eprints.cs.vt.edu/archive/00001192/}, author = {Wang, Ji and Lin, Xiao and North, Chris} } @conference {DOI10.1109/VAST.2012.6400512, title = {Pixel-oriented Treemap for multiple displays}, booktitle = {VAST Challenge 2012 IEEE Conference on Visual Analytics Science and Technology (VAST)}, year = {2012}, pages = {289 - 290}, publisher = {IEEE}, organization = {IEEE}, address = {Seattle, WA, USA}, abstract = {We have developed a Pixel-oriented Treemap visualization intended for use on multiple displays with collaborating users. It visualizes the health and status of about a million devices with a Treemap layout. In this paper we describe how we found useful pieces of the VAST 2012 Challenge MC1dataset and discuss how users interacted with this visualization during the analysis.}, keywords = {large display, multiple displays, physical navigation, pixel-oriented visualization, treemap}, isbn = {978-1-4673-4752-5}, doi = {10.1109/VAST.2012.6400512}, author = {Chung, Haeyong and Cho, Yong Ju and Self, Jessica Zeitz and North, Chris} } @article {DOI10.1109/TVCG.2012.260, title = {Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {18}, year = {2012}, month = {12/2012}, pages = {2879 - 2888}, abstract = {Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users{\textquoteright} analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user{\textquoteright}s reasoning and intuition.}, issn = {1077-2626}, doi = {10.1109/TVCG.2012.260}, author = {Endert, Alex and Fiaux, Patrick and North, Chris} } @conference {Endert:2012:SIV:2207676.2207741, title = {Semantic interaction for visual text analytics}, booktitle = {Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems}, series = {CHI {\textquoteright}12}, year = {2012}, pages = {473{\textendash}482}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {Visual analytics emphasizes sensemaking of large, complex datasets through interactively exploring visualizations generated by statistical models. For example, dimensionality reduction methods use various similarity metrics to visualize textual document collections in a spatial metaphor, where similarities between documents are approximately represented through their relative spatial distances to each other in a 2D layout. This metaphor is designed to mimic analysts{\textquoteright} mental models of the document collection and support their analytic processes, such as clustering similar documents together. However, in current methods, users must interact with such visualizations using controls external to the visual metaphor, such as sliders, menus, or text fields, to directly control underlying model parameters that they do not understand and that do not relate to their analytic process occurring within the visual metaphor. In this paper, we present the opportunity for a new design space for visual analytic interaction, called semantic interaction, which seeks to enable analysts to spatially interact with such models directly within the visual metaphor using interactions that derive from their analytic process, such as searching, highlighting, annotating, and repositioning documents. Further, we demonstrate how semantic interactions can be implemented using machine learning techniques in a visual analytic tool, called ForceSPIRE, for interactive analysis of textual data within a spatial visualization. Analysts can express their expert domain knowledge about the documents by simply moving them, which guides the underlying model to improve the overall layout, taking the user{\textquoteright}s feedback into account.}, keywords = {interaction, Visual Analytics, visualization}, isbn = {978-1-4503-1015-4}, doi = {10.1145/2207676.2207741}, url = {http://doi.acm.org/10.1145/2207676.2207741}, author = {Endert, Alex and Fiaux, Patrick and North, Chris} } @conference {Endert:2012:SCA:2254556.2254660, title = {The semantics of clustering: analysis of user-generated spatializations of text documents}, booktitle = {Proceedings of the International Working Conference on Advanced Visual Interfaces}, series = {AVI {\textquoteright}12}, year = {2012}, pages = {555{\textendash}562}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {Analyzing complex textual datasets consists of identifying connections and relationships within the data based on users{\textquoteright} intuition and domain expertise. In a spatial workspace, users can do so implicitly by spatially arranging documents into clusters to convey similarity or relationships. Algorithms exist that spatialize and cluster such information mathematically based on similarity metrics. However, analysts often find inconsistencies in these generated clusters based on their expertise. Therefore, to support sensemaking, layouts must be co-created by the user and the model. In this paper, we present the results of a study observing individual users performing a sensemaking task in a spatial workspace. We examine the users{\textquoteright} interactions during their analytic process, and also the clusters the users manually created. We found that specific interactions can act as valuable indicators of important structure within a dataset. Further, we analyze and characterize the structure of the user-generated clusters to identify useful metrics to guide future algorithms. Through a deeper understanding of how users spatially cluster information, we can inform the design of interactive algorithms to generate more meaningful spatializations for text analysis tasks, to better respond to user interactions during the analytics process, and ultimately to allow analysts to more rapidly gain insight.}, keywords = {clustering, text analytics, Visual Analytics, visualization}, isbn = {978-1-4503-1287-5}, doi = {10.1145/2254556.2254660}, url = {http://doi.acm.org/10.1145/2254556.2254660}, author = {Endert, Alex and Fox, Seth and Maiti, Dipayan and Leman, Scotland and North, Chris} } @conference {North:2011:APP:1979742.1979570, title = {Analytic provenance: process+interaction+insight}, booktitle = {Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems}, series = {CHI EA {\textquoteright}11}, year = {2011}, pages = {33{\textendash}36}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {analytic provenance, user interaction, Visual Analytics, visualization}, isbn = {978-1-4503-0268-5}, doi = {http://doi.acm.org/10.1145/1979742.1979570}, url = {http://doi.acm.org/10.1145/1979742.1979570}, author = {North, Chris and Chang, Remco and Endert, Alex and Dou, Wenwen and May, Richard and Pike, Bill and Fink, G.} } @conference {Endert:2011:CLN:1979742.1979628, title = {ChairMouse: leveraging natural chair rotation for cursor navigation on large, high-resolution displays}, booktitle = {Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems}, series = {CHI EA {\textquoteright}11}, year = {2011}, pages = {571{\textendash}580}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, abstract = {Large, high-resolution displays lead to more spatially based approaches. In such environments, the cursor (and hence the physical mouse) is the primary means of interaction. However, usability issues occur when standard mouse interaction is applied to workstations with large size and high pixel density. Previous studies show users navigate physically when interacting with information on large displays by rotating their chair. ChairMouse captures this natural chair movement and translates it into large-scale cursor movement while still maintaining standard mouse usage for local cursor movement. ChairMouse supports both active and passive use, reducing tedious mouse interactions by leveraging physical chair action.}, keywords = {Embodied Interaction, interaction design, large display}, isbn = {978-1-4503-0268-5}, doi = {http://doi.acm.org/10.1145/1979742.1979628}, url = {http://doi.acm.org/10.1145/1979742.1979628}, author = {Endert, Alex and Fiaux, Patrick and Chung, Haeyong and Stewart, Michael and Andrews, Christopher and North, Chris} } @conference {119, title = {Co-located Collaborative Sensemaking on a Large High-Resolution Display with Multiple Input Devices}, booktitle = {INTERACT 2011}, volume = {6947}, year = {2011}, pages = {589 - 604}, address = {Lisbon, Portugal}, keywords = {co-located, CSCW, Large High Resolution Display, large high-resolution display, sensemaking, Visual Analytics}, isbn = {978-3-642-23771-3}, issn = {1611-3349}, doi = {10.1007/978-3-642-23771-3_44}, author = {Katherine Vogt and Lauren Bradel and Andrews, Christopher and North, Chris and Endert, Alex and Duke Hutchings} } @article {DOI10.1177/1473871611415989, title = {A comparison of benchmark task and insight evaluation methods for information visualization}, journal = {Information Visualization}, volume = {10}, year = {2011}, month = {07/2011}, pages = {162 - 181}, issn = {1473-8716}, doi = {10.1177/1473871611415989}, author = {North, Chris and Saraiya, Purvi and Duca, Karen} } @conference {DOI201, title = {Helping Intelligence Analysts Make Connections}, booktitle = {AAAI{\textquoteright}11, Workshop on Scalable Integration of Analytics and Visualization (WS-11-17)}, year = {2011}, pages = {22-31}, author = {Hossain, M. Shahriar and Andrews, Christopher and Ramakrishnan, Naren and North, Chris} } @article {Andrews01102011, title = {Information visualization on large, high-resolution displays: Issues, challenges, and opportunities}, journal = {Information Visualization}, volume = {10}, number = {4}, year = {2011}, pages = {341-355}, abstract = {Larger, higher-resolution displays are becoming accessible to a greater number of users as display technologies decrease in cost and software for the displays improves. The additional pixels are especially useful for information visualization where scalability has typically been limited by the number of pixels available on a display. But how will visualizations for larger displays need to fundamentally differ from visualizations on desktop displays? Are the basic visualization design principles different? With this potentially new design paradigm comes questions such as whether the relative effectiveness of various graphical encodings are different on large displays, which visualizations and datasets benefit the most, and how interaction with visualizations on large, high-resolution displays will need to change. As we explore these possibilities, we shift away from the technical limitations of scalability imposed by traditional displays (e.g. number of pixels) to studying the human abilities that emerge when these limitations are removed. There is much potential for information visualizations to benefit from large, high-resolution displays, but this potential will only be realized through understanding the interaction between visualization design, perception, interaction techniques, and the display technology. In this paper we present critical design issues and outline some of the challenges and future opportunities for designing visualizations for large, high-resolution displays. We hope that these issues, challenges, and opportunities will provide guidance for future research in this area.}, doi = {10.1177/1473871611415997}, url = {http://ivi.sagepub.com/content/10/4/341.abstract}, author = {Andrews, Christopher and Endert, Alex and Yost, Beth and North, Chris} } @conference {6102449, title = {Observation-level interaction with statistical models for visual analytics}, booktitle = {Visual Analytics Science and Technology (VAST), 2011 IEEE Conference on}, year = {2011}, month = {oct.}, pages = {121 -130}, abstract = {In visual analytics, sensemaking is facilitated through interactive visual exploration of data. Throughout this dynamic process, users combine their domain knowledge with the dataset to create insight. Therefore, visual analytic tools exist that aid sensemaking by providing various interaction techniques that focus on allowing users to change the visual representation through adjusting parameters of the underlying statistical model. However, we postulate that the process of sensemaking is not focused on a series of parameter adjustments, but instead, a series of perceived connections and patterns within the data. Thus, how can models for visual analytic tools be designed, so that users can express their reasoning on observations (the data), instead of directly on the model or tunable parameters? Observation level (and thus $\#$x201C;observation $\#$x201D;) in this paper refers to the data points within a visualization. In this paper, we explore two possible observation-level interactions, namely exploratory and expressive, within the context of three statistical methods, Probabilistic Principal Component Analysis (PPCA), Multidimensional Scaling (MDS), and Generative Topographic Mapping (GTM). We discuss the importance of these two types of observation level interactions, in terms of how they occur within the sensemaking process. Further, we present use cases for GTM, MDS, and PPCA, illustrating how observation level interaction can be incorporated into visual analytic tools.}, keywords = {data analysis, data interactive visual exploration, data visualisation, exploratory interaction, expressive interaction, generative topographic mapping, multidimensional scaling, observation-level interaction, parameter adjustments, principal component analysis, probabilistic principal component analysis, probability, sensemaking process, statistical models, Visual Analytics}, doi = {10.1109/VAST.2011.6102449}, author = {Endert, Alex and Chao Han and Maiti, Dipayan and House, Leanna and Leman, Scotland and North, Chris} } @unpublished {120, title = {Space for Two to Think: Large, High-Resolution Displays for Co-located Collaborative Sensemaking}, journal = {Technical Report TR-11-11}, year = {2011}, publisher = {Computer Science, Virginia Tech}, keywords = {collaborative sensemaking, high-resolution displays, large, Large High Resolution Display, single display groupware, Visual Analytics}, author = {Lauren Bradel and Andrews, Christopher and Endert, Alex and Katherine Vogt and Duke Hutchings and North, Chris} } @conference {Singh:2011:SCA:2016904.2016907, title = {Supporting the cyber analytic process using visual history on large displays}, booktitle = {Proceedings of the 8th International Symposium on Visualization for Cyber Security}, series = {VizSec {\textquoteright}11}, year = {2011}, pages = {3:1{\textendash}3:8}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {interaction styles, large high-resolution displays, prototyping, screen design, user-centered design}, isbn = {978-1-4503-0679-9}, doi = {10.1145/2016904.2016907}, url = {http://doi.acm.org/10.1145/2016904.2016907}, author = {Singh, Ankit and Lauren Bradel and Endert, Alex and Kincaid, Robert and Andrews, Christopher and North, Chris} } @conference {123, title = {Unifying the Sensemaking Loop with Semantic Interaction}, booktitle = {IEEE Workshop on Interactive Visual Text Analytics for Decision Making at VisWeek 2011}, year = {2011}, month = {10/2011}, address = {Providence, RI}, keywords = {Visual Analytics}, author = {Endert, Alex and Fiaux, Patrick and North, Chris} } @conference {Endert:2011:VES:1992917.1992935, title = {Visual encodings that support physical navigation on large displays}, booktitle = {Proceedings of Graphics Interface 2011}, series = {GI {\textquoteright}11}, year = {2011}, pages = {103{\textendash}110}, publisher = {Canadian Human-Computer Communications Society}, organization = {Canadian Human-Computer Communications Society}, address = {School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada}, keywords = {aggregation, high-resolution display, information visualization, large, perceptual scalability}, isbn = {978-1-4503-0693-5}, url = {http://dl.acm.org/citation.cfm?id=1992917.1992935}, author = {Endert, Alex and Andrews, Christopher and Lee, Yueh Hua and North, Chris} } @conference {112, title = {The Effect of Presenting Long Documents with Large High-Resolution Displays on Comprehension of Content and User Experience}, booktitle = {the 13th International Symposium on Electronic Theses and Dissertations (ETD{\textquoteright} 10)}, year = {2010}, month = {06/2010}, address = {Austin, TX}, keywords = {Large High Resolution Display}, author = {Yang, S. and Chung, Haeyong and North, Chris and Fox, Edward A.} } @conference {1753336, title = {Space to think: large high-resolution displays for sensemaking}, booktitle = {CHI {\textquoteright}10: Proceedings of the 28th international conference on Human factors in computing systems}, year = {2010}, pages = {55{\textendash}64}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {LHRD}, isbn = {978-1-60558-929-9}, doi = {http://doi.acm.org/10.1145/1753326.1753336}, author = {Andrews, Christopher and Endert, Alex and North, Chris} } @conference {111, title = {VizCept: Supporting Synchronous Collaboration for Constructing Visualizations in Intelligence Analysis}, booktitle = {IEEE VAST Conference}, year = {2010}, month = {10/2010}, address = {Salt Lake City, Utah}, keywords = {Visual Analytics}, author = {Chung, Haeyong and Yang, S. and Massjouni, N. and Andrews, Christopher and Kanna, R. and North, Chris} } @conference {5283504, title = {Co-located Many-Player Gaming on Large High-Resolution Displays}, booktitle = {Computational Science and Engineering, 2009. CSE {\textquoteright}09. International Conference on}, volume = {4}, year = {2009}, pages = {697 -704}, keywords = {colocated many-player gaming, computer games, human computer interaction, interactive devices, large high-resolution displays, multiplayer gaming}, doi = {10.1109/CSE.2009.65}, author = {Machaj, D. and Andrews, Christopher and North, Chris} } @article {1639196, title = {A Comparison of User-Generated and Automatic Graph Layouts}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {15}, number = {6}, year = {2009}, pages = {961{\textendash}968}, publisher = {IEEE Educational Activities Department}, address = {Piscataway, NJ, USA}, issn = {1077-2626}, doi = {http://dx.doi.org/10.1109/TVCG.2009.109}, author = {Dwyer, Tim and Lee, Bongshin and Fisher, Danyel and Quinn, Kori Inkpen and Isenberg, Petra and Robertson, George and North, Chris} } @conference {1544262, title = {A multiscale interaction technique for large, high-resolution displays}, booktitle = {3DUI {\textquoteright}09: Proceedings of the 2009 IEEE Symposium on 3D User Interfaces}, year = {2009}, pages = {31{\textendash}38}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {978-1-4244-3965-2}, doi = {http://dx.doi.org/10.1109/3DUI.2009.4811202}, author = {Peck, Sarah M. and North, Chris and Bowman, Doug A.} } @conference {102, title = {Professional Analysts using a Large, High-Resolution Display}, booktitle = {IEEE VAST 2009 (Extended Abstract) (Awarded Special Contributions to the VAST Challenge Contest)}, year = {2009}, keywords = {Large High Resolution Display, Visual Analytics}, author = {Endert, Alex and Andrews, Christopher and North, Chris} } @article {104, title = {Shaping the Display of the Future: The Effects of Display Size and Curvature on User Performance and Insights}, journal = {Human{\textendash}Computer Interaction}, volume = {24}, year = {2009}, keywords = {Large High Resolution Display}, author = {Shupp, Lauren and Andrews, Christopher and Dickey-Kurdziolek, Margaret and Yost, Beth and North, Chris} } @conference {1616257, title = {Understanding Multi-touch Manipulation for Surface Computing}, booktitle = {INTERACT {\textquoteright}09: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction}, year = {2009}, pages = {236{\textendash}249}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Berlin, Heidelberg}, isbn = {978-3-642-03657-6}, doi = {http://dx.doi.org/10.1007/978-3-642-03658-3_31}, author = {North, Chris and Dwyer, Tim and Lee, Bongshin and Fisher, Danyel and Isenberg, Petra and Robertson, George and Inkpen, Kori} } @conference {5333245, title = {VAST contest dataset use in education}, booktitle = {Visual Analytics Science and Technology, 2009. IEEE VAST 2009.}, year = {2009}, pages = {115 -122}, keywords = {data visualisation, education, educational technology, evaluation metrics, IEEE visual analytics science and technology, information analysis, information analysts, VAST, Visual Analytics}, doi = {10.1109/VAST.2009.5333245}, author = {Whiting, M.A. and North, Chris and Endert, Alex and Scholtz, J. and Haack, J. and Varley, C. and Thomas, J.} } @conference {5375542, title = {Visualizing cyber security: Usable workspaces}, booktitle = {Visualization for Cyber Security, 2009. VizSec 2009. 6th International Workshop on}, year = {2009}, pages = {45 -56}, keywords = {cyber analytics work environment, cyber security visualization, data visualisation, digital infrastructures, information foraging, Large High Resolution Display, security of data, usability evaluation, usable workspaces, Visual Analytics}, doi = {10.1109/VIZSEC.2009.5375542}, author = {Fink, G. and North, Chris and Endert, Alex and Rose, S.} } @conference {1375717, title = {The effects of peripheral vision and physical navigation on large scale visualization}, booktitle = {GI {\textquoteright}08: Proceedings of graphics interface 2008}, year = {2008}, pages = {9{\textendash}16}, publisher = {Canadian Information Processing Society}, organization = {Canadian Information Processing Society}, address = {Toronto, Ont., Canada, Canada}, keywords = {geospatial, LHRD, multidimensional, physical navigation}, isbn = {978-1-56881-423-0}, author = {Ball, Robert and North, Chris} } @article {1324740, title = {Unification of problem solving environment implementation layers with XML-based specifications}, journal = {Adv. Eng. Softw.}, volume = {39}, number = {3}, year = {2008}, pages = {189{\textendash}201}, publisher = {Elsevier Science Ltd.}, address = {Oxford, UK, UK}, keywords = {databases, problem solving, XML}, issn = {0965-9978}, doi = {http://dx.doi.org/10.1016/j.advengsoft.2007.02.005}, author = {Shu, Jiang and Watson, Layne T. and Ramakrishnan, Naren and Kamke, Frederick A. and North, Chris} } @article {1422921, title = {The Value of Information Visualization}, year = {2008}, pages = {1{\textendash}18}, publisher = {Springer-Verlag}, address = {Berlin, Heidelberg}, keywords = {information visualization}, isbn = {978-3-540-70955-8}, doi = {http://dx.doi.org/10.1007/978-3-540-70956-5_1}, author = {Fekete, Jean-Daniel and Wijk, Jarke J. and Stasko, John T. and North, Chris} } @conference {1240639, title = {Beyond visual acuity: the perceptual scalability of information visualizations for large displays}, booktitle = {CHI {\textquoteright}07: Proceedings of the SIGCHI conference on Human factors in computing systems}, year = {2007}, pages = {101{\textendash}110}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {information visualization, LHRD, Visual Acuity}, isbn = {978-1-59593-593-9}, doi = {http://doi.acm.org/10.1145/1240624.1240639}, author = {Yost, Beth and Haciahmetoglu, Yonca and North, Chris} } @conference {1233421, title = {High-resolution displays enhancing geo-temporal data visualizations}, booktitle = {ACM-SE 45: Proceedings of the 45th annual southeast regional conference}, year = {2007}, pages = {443{\textendash}448}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {geospatial, information visualization, Intelligence Analysis, LHRD}, isbn = {978-1-59593-629-5}, doi = {http://doi.acm.org/10.1145/1233341.1233421}, author = {Booker, John and Buennemeyer, Timothy and Sabri, Andrew and North, Chris} } @article {1224823, title = {High-resolution gaming: Interfaces, notifications, and the user experience}, journal = {Interact. Comput.}, volume = {19}, number = {2}, year = {2007}, pages = {151{\textendash}166}, publisher = {Elsevier Science Inc.}, address = {New York, NY, USA}, keywords = {Games, LHRD, Notifications, User Interfaces}, issn = {0953-5438}, doi = {http://dx.doi.org/10.1016/j.intcom.2006.08.002}, author = {Sabri, Andrew and Ball, Robert and Fabian, Alain and Bhatia, Saurabh and North, Chris} } @conference {1240656, title = {Move to improve: promoting physical navigation to increase user performance with large displays}, booktitle = {CHI {\textquoteright}07: Proceedings of the SIGCHI conference on Human factors in computing systems}, year = {2007}, pages = {191{\textendash}200}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {Embodied Interaction, LHRD, physical navigation, Virtual Navigation}, isbn = {978-1-59593-593-9}, doi = {http://doi.acm.org/10.1145/1240624.1240656}, author = {Ball, Robert and North, Chris and Bowman, Doug A.} } @article {1244749, title = {Realizing embodied interaction for visual analytics through large displays}, journal = {Computers \& Graphics}, volume = {31}, number = {3}, year = {2007}, pages = {380{\textendash}400}, publisher = {Pergamon Press, Inc.}, address = {Elmsford, NY, USA}, keywords = {Embodied Interaction, LHRD, Space Scale, Visual Analytics}, issn = {0097-8493}, doi = {http://dx.doi.org/10.1016/j.cag.2007.01.029}, author = {Ball, Robert and North, Chris} } @article {94, title = {Reflections on Human-Computer Interaction: A special Issue in Honor of Ben Shneiderman{\textquoteright}s 60th Birthday}, journal = {International Journal of Human-Computer Interaction}, volume = {23}, year = {2007}, month = {12/2007}, pages = {195-204}, keywords = {human computer interaction}, issn = {1532-7590}, doi = {http://dx.doi.org/10.1080/10447310701702766}, url = {http://www.cs.umd.edu/hcil/ben60/}, author = {Plaisant, Catherine and North, Chris} } @article {1375941, title = {Workshop report: information visualization-human-centered issues in visual representation, interaction, and evalution}, journal = {Information Visualization}, volume = {6}, number = {3}, year = {2007}, pages = {189{\textendash}196}, publisher = {Palgrave Macmillan}, keywords = {Evaluation, Human-Centered, information visualization, Visual Analytics}, issn = {1473-8716}, doi = {http://doi.acm.org/10.1145/1375939.1375941}, author = {Kerren, Andreas and Stasko, John T. and Fekete, Jean-Daniel and North, Chris} } @conference {2558, title = {Applying Embodied Interaction and Usability Engineering to Visualization on Large Displays}, booktitle = {ACM British HCI - Workshop on Visualization \& Interaction}, year = {2006}, month = {10/2006}, keywords = {Embodied Interaction, information visualization, LHRD}, author = {Ball, Robert and Michael DellaNoce and Ni, Tao and Francis Quek and North, Chris} } @conference {1267813, title = {Bridging the host-network divide: survey, taxonomy, and solution}, booktitle = {LISA {\textquoteright}06: Proceedings of the 20th conference on Large Installation System Administration}, year = {2006}, pages = {20{\textendash}20}, publisher = {USENIX Association}, organization = {USENIX Association}, address = {Berkeley, CA, USA}, keywords = {information visualization, network security}, author = {Fink, G. and Duggirala, Vyas and Correa, Ricardo and North, Chris} } @conference {1143100, title = {Evaluation of viewport size and curvature of large, high-resolution displays}, booktitle = {GI {\textquoteright}06: Proceedings of Graphics Interface 2006}, year = {2006}, pages = {123{\textendash}130}, publisher = {Canadian Information Processing Society}, organization = {Canadian Information Processing Society}, address = {Toronto, Ont., Canada, Canada}, keywords = {Evaluation, LHRD}, isbn = {1-56881-308-2}, author = {Shupp, Lauren and Ball, Robert and Yost, Beth and Booker, John and North, Chris} } @article {1176163, title = {An Insight-Based Longitudinal Study of Visual Analytics}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {12}, number = {6}, year = {2006}, pages = {1511{\textendash}1522}, publisher = {IEEE Educational Activities Department}, address = {Piscataway, NJ, USA}, keywords = {Evaluation, GUI, information visualization}, issn = {1077-2626}, doi = {http://dx.doi.org/10.1109/TVCG.2006.85}, author = {Saraiya, Purvi and North, Chris and Lam, Vy and Duca, Karen} } @conference {Somervell04makinga, title = {Making a Case for HCI: Exploring Benefits of Visualization for Case Studies}, booktitle = {World Conference on Educational Multimedia/Hypermedia and Educational Telecommunications (ED-MEDIA {\textquoteright}06)}, year = {2006}, month = {06/2006}, address = {Orlando FL}, keywords = {information visualization}, url = {http://www.cs.vt.edu/node/1328}, author = {Brandon Berry and Laurian Hobby and McCrickard, D. Scott and North, Chris and Manuel A. P{\'e}rez-Qui{\~n}ones} } @article {1187795, title = {The Perceptual Scalability of Visualization}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {12}, number = {5}, year = {2006}, pages = {837{\textendash}844}, publisher = {IEEE Educational Activities Department}, address = {Piscataway, NJ, USA}, keywords = {Evaluation, information visualization, LHRD}, issn = {1077-2626}, doi = {http://dx.doi.org/10.1109/TVCG.2006.184}, author = {Yost, Beth and North, Chris} } @proceedings {96, title = {Is There Science in Visualization?}, journal = {IEEE Visualization 2006}, year = {2006}, month = {2006}, keywords = {Evaluation, information visualization}, author = {T. J. Jankun-Kelly and Robert Kosara and Gordon Kindlmann and North, Chris and Colin Ware and E. Wes Bethel} } @article {1137267, title = {Toward Measuring Visualization Insight}, journal = {IEEE Comput. Graph. Appl.}, volume = {26}, number = {3}, year = {2006}, pages = {6{\textendash}9}, publisher = {IEEE Computer Society Press}, address = {Los Alamitos, CA, USA}, keywords = {Evaluation, information visualization}, issn = {0272-1716}, doi = {http://dx.doi.org/10.1109/MCG.2006.70}, author = {North, Chris} } @conference {1185584, title = {Vizability: a tool for usability engineering process improvement through the visualization of usability problem data}, booktitle = {ACM-SE 44: Proceedings of the 44th annual Southeast regional conference}, year = {2006}, pages = {620{\textendash}625}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, keywords = {Evaluation, Usability}, isbn = {1-59593-315-8}, doi = {http://doi.acm.org/10.1145/1185448.1185584}, author = {Pyla, Pardha S. and Howarth, Jonathan R. and Catanzaro, Chris and North, Chris} } @conference {108, title = {An Analysis of User Behavior on High-Resolution Tiled Displays}, booktitle = {The Tenth IFIP International Conference on Human-Computer Interaction (INTERACT 2005)}, year = {2005}, month = {09/2005}, publisher = {Springer Berlin / Heidelberg}, organization = {Springer Berlin / Heidelberg}, abstract = {

The use of multiple monitors for personal desktop computing is becoming more prevalent as the price of display technology decreases. The use of two monitors for a single desktop has been shown to have performance improvement in several studies. However, few studies have been performed with more than three monitors. As a result, we report an observational analysis of the use of a large tiled display containing nine monitors (in a 3x3 matrix). The total resolution of the large display is 3840x3072, for a total of 11,796,480 pixels. Over the course of six months we observed the behavior and actions of five users who used the display extensively as a desktop. We relate our observations, provide feedback concerning common usage of how people do and do not use the display, provide common scenarios and results of interviews, and give a series of design recommendations and guidelines for future designers of applications for high-resolution, tiled displays.

}, keywords = {Large High Resolution Display, User Behavior}, doi = {10.1007/11555261_30}, url = {http://dx.doi.org/10.1007/11555261_30}, author = {Ball, Robert and North, Chris} } @article {1138786, title = {Bioinformatics visualization: introduction to the special issue}, journal = {Information Visualization}, volume = {4}, number = {3}, year = {2005}, pages = {147{\textendash}148}, publisher = {Palgrave Macmillan}, issn = {1473-8716}, doi = {http://dx.doi.org/10.1057/palgrave.ivs.9500103}, author = {North, Chris and Rhyne, Theresa Marie and Duca, Karen} } @conference {1056875, title = {Effects of tiled high-resolution display on basic visualization and navigation tasks}, booktitle = {CHI {\textquoteright}05: CHI {\textquoteright}05 extended abstracts on Human factors in computing systems}, year = {2005}, pages = {1196{\textendash}1199}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-59593-002-7}, doi = {http://doi.acm.org/10.1145/1056808.1056875}, author = {Ball, Robert and North, Chris} } @conference {107, title = {Evaluating the Benefits of Tiled Displays for Navigating Maps}, booktitle = {IASTED International Conference on Human-Computer Interaction}, year = {2005}, month = {11/2005}, keywords = {high resolution, Large High Resolution Display, maps, navigation, Usability}, author = {Ball, Robert and Michael Varghese and Bill Carstensen and E. Dana Cox and Chris Fierer and Matthew Peterson and North, Chris} } @inbook {109, title = {Information Visualization}, booktitle = {Handbook of Human Factors and Ergonomics}, year = {2005}, pages = {pg. 1222-1246}, publisher = {John Wiley \& Sons}, organization = {John Wiley \& Sons}, edition = {3rd Edition}, chapter = {Information Visualization}, address = {New York}, keywords = {information visualization}, author = {North, Chris} } @article {1070747, title = {An Insight-Based Methodology for Evaluating Bioinformatics Visualizations}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {11}, number = {4}, year = {2005}, pages = {443{\textendash}456}, publisher = {IEEE Educational Activities Department}, address = {Piscataway, NJ, USA}, issn = {1077-2626}, doi = {http://dx.doi.org/10.1109/TVCG.2005.53}, author = {Saraiya, Purvi and North, Chris and Duca, Karen} } @conference {1084409, title = {Learnability of Interactive Coordinated-View Visualizations}, booktitle = {IV {\textquoteright}05: Proceedings of the Ninth International Conference on Information Visualisation}, year = {2005}, pages = {306{\textendash}311}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7695-2397-8}, doi = {http://dx.doi.org/10.1109/IV.2005.70}, author = {Krishnamoorthy, Sujatha and North, Chris} } @conference {1106720, title = {Root Polar Layout of Internet Address Data for Security Administration}, booktitle = {VIZSEC {\textquoteright}05: Proceedings of the IEEE Workshops on Visualization for Computer Security}, year = {2005}, pages = {7}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7803-9477-1}, doi = {http://dx.doi.org/10.1109/VIZSEC.2005.23}, author = {Fink, G. and North, Chris} } @conference {1057048, title = {Single complex glyphs versus multiple simple glyphs}, booktitle = {CHI {\textquoteright}05: CHI {\textquoteright}05 extended abstracts on Human factors in computing systems}, year = {2005}, pages = {1889{\textendash}1892}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-59593-002-7}, doi = {http://doi.acm.org/10.1145/1056808.1057048}, author = {Yost, Beth and North, Chris} } @conference {110, title = {Tracking User Navigation and Performance on High-Resolution Displays using a Dynamic Real-Time Strategy Game}, booktitle = {Compendium of IEEE Symposium on Information Visualization (InfoVis 2005)}, year = {2005}, month = {10/2005}, keywords = {game, Large High Resolution Display, navigation, performance}, author = {Ball, Robert and Sabri, Andrew and Michael Varghese and North, Chris} } @conference {1106732, title = {Visual Correlation of Host Processes and Network Traffic}, booktitle = {VIZSEC {\textquoteright}05: Proceedings of the IEEE Workshops on Visualization for Computer Security}, year = {2005}, pages = {2}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7803-9477-1}, doi = {http://dx.doi.org/10.1109/VIZSEC.2005.18}, author = {Fink, G. and Muessig, Paul and North, Chris} } @conference {1106596, title = {Visualization of Graphs with Associated Timeseries Data}, booktitle = {INFOVIS {\textquoteright}05: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization}, year = {2005}, pages = {30}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7803-9464-x}, doi = {http://dx.doi.org/10.1109/INFOVIS.2005.37}, author = {Saraiya, Purvi and Lee, Peter and North, Chris} } @article {1138790, title = {Visualizing biological pathways: requirements analysis, systems evaluation and research agenda}, journal = {Information Visualization}, volume = {4}, number = {3}, year = {2005}, pages = {191{\textendash}205}, publisher = {Palgrave Macmillan}, issn = {1473-8716}, doi = {http://dx.doi.org/10.1057/palgrave.ivs.9500102}, author = {Saraiya, Purvi and North, Chris and Duca, Karen} } @conference {971432, title = {Effective features of algorithm visualizations}, booktitle = {SIGCSE {\textquoteright}04: Proceedings of the 35th SIGCSE technical symposium on Computer science education}, year = {2004}, pages = {382{\textendash}386}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-798-2}, doi = {http://doi.acm.org/10.1145/971300.971432}, author = {Saraiya, Purvi and Shaffer, Clifford A. and McCrickard, D. Scott and North, Chris} } @conference {1038775, title = {An Evaluation of Microarray Visualization Tools for Biological Insight}, booktitle = {INFOVIS {\textquoteright}04: Proceedings of the IEEE Symposium on Information Visualization}, year = {2004}, pages = {1{\textendash}8}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7803-8779-3}, doi = {http://dx.doi.org/10.1109/INFOVIS.2004.5}, author = {Saraiya, Purvi and North, Chris and Duca, Karen} } @conference {1029217, title = {Home-centric visualization of network traffic for security administration}, booktitle = {VizSEC/DMSEC {\textquoteright}04: Proceedings of the 2004 ACM workshop on Visualization and data mining for computer security}, year = {2004}, pages = {55{\textendash}64}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-974-8}, doi = {http://doi.acm.org/10.1145/1029208.1029217}, author = {Ball, Robert and Fink, G. and North, Chris} } @conference {985042, title = {PathSim visualizer: an Information-Rich Virtual Environment framework for systems biology}, booktitle = {Web3D {\textquoteright}04: Proceedings of the ninth international conference on 3D Web technology}, year = {2004}, pages = {7{\textendash}14}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-845-8}, doi = {http://doi.acm.org/10.1145/985040.985042}, author = {Polys, Nicholas F. and Bowman, Doug A. and North, Chris and Laubenbacher, Reinhard and Duca, Karen} } @conference {766020, title = {Dynamic query sliders vs. brushing histograms}, booktitle = {CHI {\textquoteright}03: CHI {\textquoteright}03 extended abstracts on Human factors in computing systems}, year = {2003}, pages = {834{\textendash}835}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-637-4}, doi = {http://doi.acm.org/10.1145/765891.766020}, author = {Li, Qing and Bao, Xiaofeng and Song, Chen and Zhang, Jinfei and North, Chris} } @conference {937950, title = {Exploring Context Switching and Cognition in Dual-View Coordinated Visualizations}, booktitle = {CMV {\textquoteright}03: Proceedings of the conference on Coordinated and Multiple Views In Exploratory Visualization}, year = {2003}, pages = {55}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7695-2001-4}, author = {Convertino, Gregorio and Chen, Jian and Yost, Beth and Ryu, Young-Sam and North, Chris} } @conference {765897, title = {Fusion: interactive coordination of diverse data, visualizations, and mining algorithms}, booktitle = {CHI {\textquoteright}03: CHI {\textquoteright}03 extended abstracts on Human factors in computing systems}, year = {2003}, pages = {626{\textendash}627}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-637-4}, doi = {http://doi.acm.org/10.1145/765891.765897}, author = {North, Chris and Conklin, Nathan and Indukuri, Kiran and Saini, Varun and Yu, Qiang} } @conference {1008669, title = {Information-rich virtual environments: theory, tools, and research agenda}, booktitle = {VRST {\textquoteright}03: Proceedings of the ACM symposium on Virtual reality software and technology}, year = {2003}, pages = {81{\textendash}90}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-569-6}, doi = {http://doi.acm.org/10.1145/1008653.1008669}, author = {Bowman, Doug A. and North, Chris and Chen, Jian and Polys, Nicholas F. and Pyla, Pardha S. and Yilmaz, Umur} } @conference {506604, title = {Breakdown visualization: multiple foci polyarchies of values and attributes}, booktitle = {CHI {\textquoteright}02: CHI {\textquoteright}02 extended abstracts on Human factors in computing systems}, year = {2002}, pages = {800{\textendash}801}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-454-1}, doi = {http://doi.acm.org/10.1145/506443.506604}, author = {Prabhakar, Sandeep and Conklin, Nathan and North, Chris and Thirunavukkarasu, Muthukumar and Dandapani, Anusha and Panchanathan, Ganesh} } @conference {544279, title = {Enhancing the ENVISION interface for digital libraries}, booktitle = {JCDL {\textquoteright}02: Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries}, year = {2002}, pages = {275{\textendash}276}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-513-0}, doi = {http://doi.acm.org/10.1145/544220.544279}, author = {Wang, Jun and Agrawal, Abhishek and Bazaza, Anil and Angle, Supriya and Fox, Edward A. and North, Chris} } @conference {509775, title = {An evaluation of information visualization in attention-limited environments}, booktitle = {VISSYM {\textquoteright}02: Proceedings of the symposium on Data Visualisation 2002}, year = {2002}, pages = {211{\textendash}216}, publisher = {Eurographics Association}, organization = {Eurographics Association}, address = {Aire-la-Ville, Switzerland, Switzerland}, isbn = {1-58113-536-X}, author = {Somervell, Jacob and McCrickard, D. Scott and North, Chris and Shukla, Maulik} } @conference {602206, title = {Evolving visual metaphors and dynamic tools for bioinformatics visualization}, booktitle = {VIS {\textquoteright}02: Proceedings of the conference on Visualization {\textquoteright}02}, year = {2002}, pages = {579{\textendash}582}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7803-7498-3}, author = {Rhyne, Theresa Marie and Dunning,Jr., Thomas H. and Calapristi, Gus and North, Chris and Gresh, Donna} } @conference {857741, title = {Multiple Foci Drill-Down through Tuple and Attribute Aggregation Polyarchies in Tabular Data}, booktitle = {INFOVIS {\textquoteright}02: Proceedings of the IEEE Symposium on Information Visualization (InfoVis{\textquoteright}02)}, year = {2002}, pages = {131}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7695-1751-X}, author = {Conklin, Nathan and Prabhakar, Sandeep and North, Chris} } @conference {506503, title = {An ordering of secondary task display attributes}, booktitle = {CHI {\textquoteright}02: CHI {\textquoteright}02 extended abstracts on Human factors in computing systems}, year = {2002}, pages = {600{\textendash}601}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-454-1}, doi = {http://doi.acm.org/10.1145/506443.506503}, author = {Tessendorf, David and Chewar, C. M. and Ndiwalana, Ali and Pryor, Jon and McCrickard, D. Scott and North, Chris} } @conference {602168, title = {A radial focus+context visualization for multi-dimensional functions}, booktitle = {VIS {\textquoteright}02: Proceedings of the conference on Visualization {\textquoteright}02}, year = {2002}, pages = {443{\textendash}450}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7803-7498-3}, author = {Jayaraman, Sanjini and North, Chris} } @conference {509766, title = {Secondary task display attributes: optimizing visualizations for cognitive task suitability and interference avoidance}, booktitle = {VISSYM {\textquoteright}02: Proceedings of the symposium on Data Visualisation 2002}, year = {2002}, pages = {165{\textendash}171}, publisher = {Eurographics Association}, organization = {Eurographics Association}, address = {Aire-la-Ville, Switzerland, Switzerland}, isbn = {1-58113-536-X}, author = {Chewar, C. M. and McCrickard, D. Scott and Ndiwalana, Ali and North, Chris and Pryor, Jon and Tessendorf, David} } @article {861134, title = {Visualization schemas and a web-based architecture for custom multiple-view visualization of multiple-table databases}, journal = {Information Visualization}, volume = {1}, number = {3/4}, year = {2002}, pages = {211{\textendash}228}, publisher = {Palgrave Macmillan}, issn = {1473-8716}, doi = {http://dx.doi.org/10.1057/palgrave.ivs.9500020}, author = {North, Chris and Conklin, Nathan and Indukuri, Kiran and Saini, Varun} } @conference {857737, title = {Visualization Schemas for Flexible Information Visualization}, booktitle = {INFOVIS {\textquoteright}02: Proceedings of the IEEE Symposium on Information Visualization (InfoVis{\textquoteright}02)}, year = {2002}, pages = {15}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, isbn = {0-7695-1751-X}, author = {North, Chris and Conklin, Nathan and Saini, Varun} } @conference {634188, title = {Component-based, user-constructed, multiple-view visualization}, booktitle = {CHI {\textquoteright}01: CHI {\textquoteright}01 extended abstracts on Human factors in computing systems}, year = {2001}, pages = {201{\textendash}202}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-340-5}, doi = {http://doi.acm.org/10.1145/634067.634188}, author = {North, Chris and Shneiderman, Ben} } @conference {345282, title = {Snap-together visualization: a user interface for coordinating visualizations via relational schemata}, booktitle = {AVI {\textquoteright}00: Proceedings of the working conference on Advanced visual interfaces}, year = {2000}, pages = {128{\textendash}135}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-252-2}, doi = {http://doi.acm.org/10.1145/345513.345282}, author = {North, Chris and Shneiderman, Ben} } @article {362772, title = {Snap-together visualization: can users construct and operate coordinated visualizations?}, journal = {Int. J. Hum.-Comput. Stud.}, volume = {53}, number = {5}, year = {2000}, pages = {715{\textendash}739}, publisher = {Academic Press, Inc.}, address = {Duluth, MN, USA}, issn = {1071-5819}, doi = {http://dx.doi.org/10.1006/ijhc.2000.0418}, author = {North, Chris and Shneiderman, Ben} } @mastersthesis {931491, title = {A user interface for coordinating visualizations based on relational schemata: snap-together visualization}, year = {2000}, note = {Chair-Shneiderman, Ben}, school = {University of Maryland at College Park}, type = {phd}, address = {College Park, MD, USA}, isbn = {0-599-72609-1}, author = {North, Chris} } @conference {331780, title = {Temporal, geographical and categorical aggregations viewed through coordinated displays: a case study with highway incident data}, booktitle = {NPIVM {\textquoteright}99: Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge management}, year = {1999}, pages = {26{\textendash}34}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-254-9}, doi = {http://doi.acm.org/10.1145/331770.331780}, author = {Fredrikson, Anna and North, Chris and Plaisant, Catherine and Shneiderman, Ben} } @article {300823, title = {User controlled overviews of an image library: a case study of the visible human}, year = {1999}, pages = {570{\textendash}578}, publisher = {Morgan Kaufmann Publishers Inc.}, address = {San Francisco, CA, USA}, isbn = {1-55860-533-9}, author = {North, Chris and Shneiderman, Ben and Plaisant, Catherine} } @conference {286529, title = {Robust, end-user programmable, multiple-window coordination}, booktitle = {CHI {\textquoteright}98: CHI 98 conference summary on Human factors in computing systems}, year = {1998}, pages = {60{\textendash}61}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {1-58113-028-7}, doi = {http://doi.acm.org/10.1145/286498.286529}, author = {North, Chris} } @conference {257406, title = {Browsing anatomical image databases: a case study of the visible human}, booktitle = {CHI {\textquoteright}96: Conference companion on Human factors in computing systems}, year = {1996}, pages = {414{\textendash}415}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {0-89791-832-0}, doi = {http://doi.acm.org/10.1145/257089.257406}, author = {North, Chris and Korn, Flip} } @conference {226946, title = {User controlled overviews of an image library: a case study of the visible human}, booktitle = {DL {\textquoteright}96: Proceedings of the first ACM international conference on Digital libraries}, year = {1996}, pages = {74{\textendash}82}, publisher = {ACM}, organization = {ACM}, address = {New York, NY, USA}, isbn = {0-89791-830-4}, doi = {http://doi.acm.org/10.1145/226931.226946}, author = {North, Chris and Shneiderman, Ben and Plaisant, Catherine} }