%0 Journal Article %J IEEE Transactions on Visualization and Computer Graphics %D 2024 %T Multiple Monitors or Single Canvas? Evaluating Window Management and Layout Strategies on Virtual Displays %A Leonardo Pavanatto Soares %A Feiyu Lu %A North, Chris %A Bowman, Doug A. %B IEEE Transactions on Visualization and Computer Graphics %V to appear %8 12/2024 %0 Conference Paper %B Symposium on Visualization in Data Science (VDS) at IEEE VIS %D 2023 %T Aardvark: Comparative Visualization of Data Analysis Scripts %A Faust, Rebecca %A C. Scheidegger %A North, Chris %B Symposium on Visualization in Data Science (VDS) at IEEE VIS %P 30-38 %8 10/2023 %R 10.1109/VDS60365.2023.00009 %0 Conference Paper %B IEEE International Symposium on Mixed and Augmented Reality (ISMAR) %D 2023 %T Spaces to Think: A Comparison of Small, Large, and Immersive Displays for the Sensemaking Process %A Lee Lisle %A Kylie Davidson %A Leonardo Pavanatto Soares %A Tahmid, Ibrahim A. %A North, Chris %A Bowman, Doug A. %B IEEE International Symposium on Mixed and Augmented Reality (ISMAR) %P 1084-1093 %8 10/2023 %R 10.1109/ISMAR59233.2023.00125 %0 Conference Paper %B Advances in Visual Computing: 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part I %D 2022 %T Explainable Interactive Projections For Image Data %A Huimin Han %A Faust, Rebecca %A Norambuena, Brian Felipe Keith %A Prabhu, Ritvik %A Smith, Timothy %A Song Li %A North, Chris %K Explainable AI %K Image data %K Interactive dimension reduction %K Semantic interaction %X 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. %B Advances in Visual Computing: 17th International Symposium, ISVC 2022, San Diego, CA, USA, October 3–5, 2022, Proceedings, Part I %I Springer-Verlag %C Berlin, Heidelberg %P 77–90 %@ 978-3-031-20712-9 %U https://doi.org/10.1007/978-3-031-20713-6_6 %R 10.1007/978-3-031-20713-6_6 %0 Conference Paper %B 2022 IEEE Visualization in Data Science (VDS) %D 2022 %T Interactive Visualization for Data Science Scripts %A Faust, Rebecca %A C. Scheidegger %A K. Isaacs %A W. Z. Bernstein %A M. Sharp %A North, Chris %K behavioral sciences %K codes %K data science %K Data visualization %K debugging %K prototypes %K visualization %X 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’s support for analysis understanding tasks, we provide two usage scenarios on real world analysis scripts. %B 2022 IEEE Visualization in Data Science (VDS) %I IEEE Computer Society %C Los Alamitos, CA, USA %P 37-45 %8 10/2022 %U https://doi.ieeecomputersociety.org/10.1109/VDS57266.2022.00009 %R 10.1109/VDS57266.2022.00009 %0 Conference Paper %B IEEE Virtual Reality and 3D User Interfaces (VR) %D 2021 %T Do we still need physical monitors? An evaluation of the usability of AR virtual monitors for productivity work %A Leonardo Pavanatto Soares %A Doug Bowman %A North, Chris %A Carmen Badea %A Rich Stoakley %B IEEE Virtual Reality and 3D User Interfaces (VR) %P 759-767 %0 Conference Paper %B SIGCSE 2020 %D 2020 %T Auto-Grading Jupyter Notebooks %A Hamza Manzoor %A Amit Naik %A Shaffer, Clifford A. %A North, Chris %A Stephen H. Edwards %B SIGCSE 2020 %8 03/2020 %0 Journal Article %J IEEE Transactions on Visualization and Computer Graphics %D 2019 %T The Effect of Edge Bundling and Seriation on Sensemaking of Biclusters in Bipartite Graphs %A Sun, Maoyuan %A Zhao, Jian %A Hao Wu %A Luther, Kurt %A North, Chris %A Ramakrishnan, Naren %K Bicluster %K bicluster visualizations %K bicluster-based seriation %K Bioinformatics %K Bipartite graph %K bipartite graph based visualizations %K data analysis %K data visualisation %K edge bundles %K edge bundling %K edge crossings %K exploratory data analysis %K graph theory %K Image edge detection %K Layout %K pattern clustering %K product bundles %K seriation %K Visual Analytics %X 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. %B IEEE Transactions on Visualization and Computer Graphics %V 25 %P 2983-2998 %8 07/2019 %N 10 %R 10.1109/TVCG.2018.2861397 %0 Journal Article %J Frontiers in Robotics and AI %D 2019 %T Immersive Analytics: Theory and Research Agenda %A Skarbez, Richard %A Polys, Nicholas F. %A Ogle, J. Todd %A North, Chris %A Bowman, Doug A. %X Advances in a variety of computing fields, including “big data,” 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. %B Frontiers in Robotics and AI %V 6 %P 82 %8 09/2019 %U https://www.frontiersin.org/article/10.3389/frobt.2019.00082 %R 10.3389/frobt.2019.00082 %0 Conference Paper %B VIS 2019 Short Papers %D 2019 %T Interactive Bicluster Aggregation in Bipartite Graphs %A Sun, Maoyuan %A Koop, David %A Zhao, Jian %A North, Chris %A Ramakrishnan, Naren %B VIS 2019 Short Papers %8 10/2019 %0 Journal Article %J IEEE Transactions on Learning Technologies %D 2018 %T Be the Data: Embodied Visual Analytics %A Xin Chen %A Self, Jessica Zeitz %A House, Leanna %A Wenskovitch, John %A Sun, Maoyuan %A Nathan Wycoff %A Jane Robertson Evia %A Leman, Scotland %A North, Chris %B IEEE Transactions on Learning Technologies %V 11 %P 81-95 %N 1 %R 10.1109/TLT.2017.2757481 %0 Conference Paper %B CHI 2018 Workshop on Sensemaking in a Senseless World %D 2018 %T Crowdsourcing Intelligence Analysis with Context Slices %A Li, Tianyi %A Asmita Shah %A Luther, Kurt %A North, Chris %B CHI 2018 Workshop on Sensemaking in a Senseless World %8 04/2018 %0 Journal Article %J ACM Transactions on Knowledge Discovery from Data %D 2018 %T Interactive Discovery of Coordinated Relationship Chains with Maximum Entropy Models %A Hao Wu %A Sun, Maoyuan %A Peng Mi %A Nikolaj Ta %A North, Chris %A Ramakrishnan, Naren %B ACM Transactions on Knowledge Discovery from Data %V 12 %8 02/2018 %N 1 %R 10.1145/3047017 %0 Journal Article %J ACM Transactions on Interactive Intelligent Systems %D 2018 %T Observation-Level and Parametric Interaction for High-Dimensional Data Analysis %A Self, Jessica Zeitz %A Michelle Dowling %A Wenskovitch, John %A Ian Crandell %A Ming Wang %A House, Leanna %A Leman, Scotland %A North, Chris %B ACM Transactions on Interactive Intelligent Systems %V 8 %8 07/2018 %N 2 %R 10.1145/3158230 %0 Conference Paper %B Proceedings of the 33rd Annual Consortium of Computing Sciences in Colleges (CCSC) Eastern Regional Conference %D 2017 %T Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills %A Self, Jessica Zeitz %A Self, Nathan %A House, Leanna %A Jane Robertson Evia %A Leman, Scotland %A North, Chris %B Proceedings of the 33rd Annual Consortium of Computing Sciences in Colleges (CCSC) Eastern Regional Conference %P 10 %8 10/2017 %0 Journal Article %J Informatics %D 2016 %T AVIST: A GPU-Centric Design for Visual Exploration of Large Multidimensional Datasets %A Peng Mi %A Sun, Maoyuan %A Moeti Masiane %A Yong Cao %A North, Chris %B Informatics %7 Special Issue on Information Visualization for Massive Data %I MDPI %V 3 %P 18 %8 10/2016 %U http://www.mdpi.com/2227-9709/3/4/18 %N 4 %R 10.3390/informatics3040018 %0 Conference Paper %B IEEE Virtual Reality 2016 Workshop on Immersive Analytics %D 2016 %T Be the Data: A New Approach for Immersive Analytics %A Xin Chen %A Self, Jessica Zeitz %A House, Leanna %A North, Chris %B IEEE Virtual Reality 2016 Workshop on Immersive Analytics %P 6 %8 03/2016 %0 Conference Paper %B 2016 Annual Meeting of the American Educational Research Association (AERA) %D 2016 %T Be the Data: An Embodied Experience for Data Analytics %A Xin Chen %A House, Leanna %A Self, Jessica Zeitz %A Leman, Scotland %A Jane Robertson Evia %A James Thomas Fry %A North, Chris %B 2016 Annual Meeting of the American Educational Research Association (AERA) %P 20 %8 04/2016 %0 Conference Paper %B International Workshop on Visualization and Collaboration (VisualCol 2016) %D 2016 %T Be the Data: Social Meetings with Visual Analytics %A Xin Chen %A Self, Jessica Zeitz %A Sun, Maoyuan %A House, Leanna %A North, Chris %B International Workshop on Visualization and Collaboration (VisualCol 2016) %P 8 %8 11/2016 %0 Journal Article %J Visualization and Computer Graphics, IEEE Transactions on %D 2016 %T BiSet: Semantic Edge Bundling with Biclusters for Sensemaking %A Sun, Maoyuan %A Peng, Mi %A North, Chris %A Ramakrishnan, Naren %X 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, “in-between”, 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. %B Visualization and Computer Graphics, IEEE Transactions on %I IEEE %V 22 %P 310-319 %8 01/2016 %N 1 %R 10.1109/TVCG.2015.2467813 %0 Conference Paper %B SIGMOD 2016 Workshop on Human-In-the-Loop Data Analytics (HILDA 2016) %D 2016 %T Bridging the Gap between User Intention and Model Parameters for Data Analytics %A Self, Jessica Zeitz %A Vinayagam, R.K. %A James Thomas Fry %A North, Chris %B SIGMOD 2016 Workshop on Human-In-the-Loop Data Analytics (HILDA 2016) %P 6 %8 06/2016 %0 Conference Paper %B CHI 2016 Workshop on Human-Centered Machine Learning (HCML) %D 2016 %T Designing Usable Interactive Visual Analytics Tools for Dimension Reduction %A Self, Jessica Zeitz %A Hu, Xinran %A House, Leanna %A Leman, Scotland %A North, Chris %B CHI 2016 Workshop on Human-Centered Machine Learning (HCML) %P 7 %8 05/2016 %0 Journal Article %J Informatics %D 2016 %T Interactive Graph Layout of a Million Nodes %A Peng Mi %A Sun, Maoyuan %A Moeti Masiane %A Yong Cao %A North, Chris %B Informatics %7 Special Issue on Information Visualization for Massive Data %V 3 %P 23 %8 12/2016 %U http://www.mdpi.com/2227-9709/3/4/23 %N 4 %R 10.3390/informatics3040023 %0 Conference Paper %B CHI 2016 Workshop on Human Centred Machine Learning %D 2016 %T Usability Challenges underlying Bicluster Interaction for Sensemaking %A Sun, Maoyuan %A Peng Mi %A Hao Wu %A North, Chris %A Ramakrishnan, Naren %B CHI 2016 Workshop on Human Centred Machine Learning %P 6 pages %8 05/2016 %0 Report %D 2015 %T Andromeda: Observation-Level and Parametric Interaction for Exploratory Data Analysis %A Self, Jessica Zeitz %A House, Leanna %A Leman, Scotland %A North, Chris %X 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. %I Virginia Tech %C Blacksburg %9 Technical Report %0 Report %D 2015 %T Bringing Interactive Visual Analytics to the Classroom for Developing EDA Skills %A Self, Jessica Zeitz %A Self, Nathan %A House, Leanna %A Jane Robertson Evia %A Leman, Scotland %A North, Chris %K dimension reduction %K education %K multidimensional scaling %K multivariate analysis %K Visual Analytics %X 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' capacity for making dimensionally complex insights from data. Using this concept, we build a vocabulary and methodology to support a student’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' CD begin low and improve. %I Virginia Tech %C Blacksburg %9 Technical Report %0 Report %D 2015 %T Designing for Interactive Dimension Reduction Visual Analytics Tools to Explore High-Dimensional Data %A Self, Jessica Zeitz %A Hu, Xinran %A House, Leanna %A Leman, Scotland %A North, Chris %X 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. %I Virginia Tech %C Blacksburg %9 Technical Report %0 Conference Paper %B Proceedings of the 2015 ACM International Workshop on Security and Privacy Analytics %D 2015 %T Visualizing Traffic Causality for Analyzing Network Anomalies %A Zhang, Hao %A Sun, Maoyuan %A Yao, Danfeng %A North, Chris %K anomaly detection %K information visualization %K network traffic analysis %K usable security %K visual locality %B Proceedings of the 2015 ACM International Workshop on Security and Privacy Analytics %S IWSPA '15 %I ACM %C New York, NY, USA %P 37–42 %@ 978-1-4503-3341-2 %U http://doi.acm.org/10.1145/2713579.2713583 %R 10.1145/2713579.2713583 %0 Journal Article %J Visualization and Computer Graphics, IEEE Transactions on %D 2014 %T A Five-Level Design Framework for Bicluster Visualizations %A Sun, Maoyuan %A North, C. %A Ramakrishnan, N. %K bicluster visualizations %K Biclusters %K Bioinformatics %K Cluster approximation %K coordinated relationships %K data analysis %K Data mining %K data visualisation %K design framework %K five-level design framework %K interactive visual analytics %K navigation %K pattern clustering %K Visual Analytics %K visual analytics tools %X Analysts often need to explore and identify coordinated relationships (e.g., four people who visited the same five cities on the same set of days) within some large datasets for sensemaking. Biclusters provide a potential solution to ease this process, because each computed bicluster bundles individual relationships into coordinated sets. By understanding such computed, structural, relations within biclusters, analysts can leverage their domain knowledge and intuition to determine the importance and relevance of the extracted relationships for making hypotheses. However, due to the lack of systematic design guidelines, it is still a challenge to design effective and usable visualizations of biclusters to enhance their perceptibility and interactivity for exploring coordinated relationships. In this paper, we present a five-level design framework for bicluster visualizations, with a survey of the state-of-the-art design considerations and applications that are related or that can be applied to bicluster visualizations. We summarize pros and cons of these design options to support user tasks at each of the five-level relationships. Finally, we discuss future research challenges for bicluster visualizations and their incorporation into visual analytics tools. %B Visualization and Computer Graphics, IEEE Transactions on %V 20 %P 1713-1722 %8 Dec %N 12 %R 10.1109/TVCG.2014.2346665 %0 Report %D 2014 %T Improving Students' Cognitive Dimensionality through Education with Object-Level Interaction %A Self, Jessica Zeitz %A Self, Nathan %A House, Leanna %A Leman, Scotland %A North, Chris %K multivariate data analysis %K object level interaction %K Visual Analytics %X This paper addresses the use of visual analytics techniques in education to advance students' 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’ 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' capacity for dimensionally complex insights. Using this concept, we build a vocabulary and methodology to support a student’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' cognitive dimensionality can be improved and further research on the impact of visual analytics tools on education for cognitive dimensionality is warranted. %I Virginia Tech %C Blacksburg %9 Technical Report %0 Conference Paper %B Proceedings of the 32Nd Annual ACM Conference on Human Factors in Computing Systems %D 2014 %T The Role of Interactive Biclusters in Sensemaking %A Sun, Maoyuan %A Lauren Bradel %A North, Chris L. %A Ramakrishnan, Naren %K biclustering %K Intelligence Analysis %K visual interaction %B Proceedings of the 32Nd Annual ACM Conference on Human Factors in Computing Systems %S CHI '14 %I ACM %C New York, NY, USA %P 1559–1562 %@ 978-1-4503-2473-1 %U http://doi.acm.org/10.1145/2556288.2557337 %R 10.1145/2556288.2557337 %0 Journal Article %J Personal and Ubiquitous Computing %D 2014 %T VisPorter: facilitating information sharing for collaborative sensemaking on multiple displays %A Chung, Haeyong %A North, Chris %A Self, Jessica Zeitz %A Chu, Sharon %A Francis Quek %K collaborative sensemaking %K Display ecology %K multiple displays %K text analytics %K Visual Analytics %B Personal and Ubiquitous Computing %I Springer London %V 18 %P 1169–1186 %8 6/2014 %U http://dx.doi.org/10.1007/s00779-013-0727-2 %N 5 %R 10.1007/s00779-013-0727-2 %0 Conference Paper %B 2013 IEEE International Conference on Intelligence and Security Informatics (ISI) %D 2013 %T Auto-Highlighter: Identifying Salient Sentences in Text %A Self, Jessica Zeitz %A Zeitz, Rebecca %A North, Chris %A Breitler, Alan L. %B 2013 IEEE International Conference on Intelligence and Security Informatics (ISI) %I IEEE %C Seattle, WA, USA %P 260 - 262 %8 6/2013 %@ 978-1-4673-6214-6 %R 10.1109/ISI.2013.6578831 %0 Journal Article %J Computer %D 2013 %T Bixplorer: Visual Analytics with Biclusters %A Fiaux, Patrick %A Sun, Maoyuan %A Lauren Bradel %A North, Chris %A Ramakrishnan, Naren %A Endert, Alex %B Computer %V 46 %P 90 - 94 %8 08/2013 %N 8 %! Computer %R 10.1109/MC.2013.269 %0 Conference Paper %B 2013 IEEE International Conference on Intelligence and Security Informatics (ISI) %D 2013 %T How analysts cognitively “connect the dots” %A Lauren Bradel %A Self, Jessica Zeitz %A Endert, Alex %A Hossain, M. Shahriar %A North, Chris %A Ramakrishnan, Naren %B 2013 IEEE International Conference on Intelligence and Security Informatics (ISI) %I IEEE %C Seattle, WA, USA %P 24 - 26 %8 6/2013 %@ 978-1-4673-6214-6 %R 10.1109/ISI.2013.6578780 %0 Conference Paper %B VAST Challenge 2012 IEEE Conference on Visual Analytics Science and Technology (VAST) %D 2012 %T Pixel-oriented Treemap for multiple displays %A Chung, Haeyong %A Cho, Yong Ju %A Self, Jessica Zeitz %A North, Chris %K large display %K multiple displays %K physical navigation %K pixel-oriented visualization %K treemap %X 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. %B VAST Challenge 2012 IEEE Conference on Visual Analytics Science and Technology (VAST) %I IEEE %C Seattle, WA, USA %P 289 - 290 %@ 978-1-4673-4752-5 %R 10.1109/VAST.2012.6400512 %0 Conference Paper %B Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems %D 2011 %T ChairMouse: leveraging natural chair rotation for cursor navigation on large, high-resolution displays %A Endert, Alex %A Fiaux, Patrick %A Chung, Haeyong %A Stewart, Michael %A Andrews, Christopher %A North, Chris %K Embodied Interaction %K interaction design %K large display %X 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. %B Proceedings of the 2011 annual conference extended abstracts on Human factors in computing systems %S CHI EA '11 %I ACM %C New York, NY, USA %P 571–580 %@ 978-1-4503-0268-5 %U http://doi.acm.org/10.1145/1979742.1979628 %R http://doi.acm.org/10.1145/1979742.1979628 %0 Journal Article %J Information Visualization %D 2011 %T A comparison of benchmark task and insight evaluation methods for information visualization %A North, Chris %A Saraiya, Purvi %A Duca, Karen %B Information Visualization %V 10 %P 162 - 181 %8 07/2011 %N 3 %! Information Visualization %R 10.1177/1473871611415989 %0 Conference Paper %B Proceedings of the 8th International Symposium on Visualization for Cyber Security %D 2011 %T Supporting the cyber analytic process using visual history on large displays %A Singh, Ankit %A Lauren Bradel %A Endert, Alex %A Kincaid, Robert %A Andrews, Christopher %A North, Chris %K interaction styles %K large high-resolution displays %K prototyping %K screen design %K user-centered design %B Proceedings of the 8th International Symposium on Visualization for Cyber Security %S VizSec '11 %I ACM %C New York, NY, USA %P 3:1–3:8 %@ 978-1-4503-0679-9 %U http://doi.acm.org/10.1145/2016904.2016907 %R 10.1145/2016904.2016907 %0 Journal Article %J Human–Computer Interaction %D 2009 %T Shaping the Display of the Future: The Effects of Display Size and Curvature on User Performance and Insights %A Shupp, Lauren %A Andrews, Christopher %A Dickey-Kurdziolek, Margaret %A Yost, Beth %A North, Chris %K Large High Resolution Display %B Human–Computer Interaction %V 24 %N 1 %0 Conference Paper %B Visual Analytics Science and Technology, 2009. IEEE VAST 2009. %D 2009 %T VAST contest dataset use in education %A Whiting, M.A. %A North, Chris %A Endert, Alex %A Scholtz, J. %A Haack, J. %A Varley, C. %A Thomas, J. %K data visualisation %K education %K educational technology %K evaluation metrics %K IEEE visual analytics science and technology %K information analysis %K information analysts %K VAST %K Visual Analytics %B Visual Analytics Science and Technology, 2009. IEEE VAST 2009. %P 115 -122 %R 10.1109/VAST.2009.5333245 %0 Journal Article %J Adv. Eng. Softw. %D 2008 %T Unification of problem solving environment implementation layers with XML-based specifications %A Shu, Jiang %A Watson, Layne T. %A Ramakrishnan, Naren %A Kamke, Frederick A. %A North, Chris %K databases %K problem solving %K XML %B Adv. Eng. Softw. %I Elsevier Science Ltd. %C Oxford, UK, UK %V 39 %P 189–201 %G eng %R http://dx.doi.org/10.1016/j.advengsoft.2007.02.005 %0 Journal Article %D 2008 %T The Value of Information Visualization %A Fekete, Jean-Daniel %A Wijk, Jarke J. %A Stasko, John T. %A North, Chris %K information visualization %I Springer-Verlag %C Berlin, Heidelberg %P 1–18 %@ 978-3-540-70955-8 %G eng %R http://dx.doi.org/10.1007/978-3-540-70956-5_1 %0 Conference Paper %B ACM-SE 45: Proceedings of the 45th annual southeast regional conference %D 2007 %T High-resolution displays enhancing geo-temporal data visualizations %A Booker, John %A Buennemeyer, Timothy %A Sabri, Andrew %A North, Chris %K geospatial %K information visualization %K Intelligence Analysis %K LHRD %B ACM-SE 45: Proceedings of the 45th annual southeast regional conference %I ACM %C New York, NY, USA %P 443–448 %@ 978-1-59593-629-5 %G eng %R http://doi.acm.org/10.1145/1233341.1233421 %0 Journal Article %J Interact. Comput. %D 2007 %T High-resolution gaming: Interfaces, notifications, and the user experience %A Sabri, Andrew %A Ball, Robert %A Fabian, Alain %A Bhatia, Saurabh %A North, Chris %K Games %K LHRD %K Notifications %K User Interfaces %B Interact. Comput. %I Elsevier Science Inc. %C New York, NY, USA %V 19 %P 151–166 %G eng %R http://dx.doi.org/10.1016/j.intcom.2006.08.002 %0 Journal Article %J Information Visualization %D 2007 %T Workshop report: information visualization-human-centered issues in visual representation, interaction, and evalution %A Kerren, Andreas %A Stasko, John T. %A Fekete, Jean-Daniel %A North, Chris %K Evaluation %K Human-Centered %K information visualization %K Visual Analytics %B Information Visualization %I Palgrave Macmillan %V 6 %P 189–196 %G eng %R http://doi.acm.org/10.1145/1375939.1375941 %0 Conference Paper %B GI '06: Proceedings of Graphics Interface 2006 %D 2006 %T Evaluation of viewport size and curvature of large, high-resolution displays %A Shupp, Lauren %A Ball, Robert %A Yost, Beth %A Booker, John %A North, Chris %K Evaluation %K LHRD %B GI '06: Proceedings of Graphics Interface 2006 %I Canadian Information Processing Society %C Toronto, Ont., Canada, Canada %P 123–130 %@ 1-56881-308-2 %G eng %0 Journal Article %J IEEE Transactions on Visualization and Computer Graphics %D 2006 %T An Insight-Based Longitudinal Study of Visual Analytics %A Saraiya, Purvi %A North, Chris %A Lam, Vy %A Duca, Karen %K Evaluation %K GUI %K information visualization %B IEEE Transactions on Visualization and Computer Graphics %I IEEE Educational Activities Department %C Piscataway, NJ, USA %V 12 %P 1511–1522 %G eng %R http://dx.doi.org/10.1109/TVCG.2006.85 %0 Conference Paper %B Proceedings of the IEEE conference on Virtual Reality %D 2006 %T A Survey of Large High-Resolution Display Technologies, Techniques, and Applications %A Ni, Tao %A Schmidt, Greg S. %A Staadt, Oliver G. %A Livingston, Mark A. %A Ball, Robert %A May, Richard %K Evaluation %K information visualization %K LHRD %K User Interfaces %B Proceedings of the IEEE conference on Virtual Reality %S VR '06 %I IEEE Computer Society %C Washington, DC, USA %P 223–236 %@ 1-4244-0224-7 %U http://dx.doi.org/10.1109/VR.2006.20 %R http://dx.doi.org/10.1109/VR.2006.20 %0 Journal Article %J IEEE Transactions on Visualization and Computer Graphics %D 2005 %T An Insight-Based Methodology for Evaluating Bioinformatics Visualizations %A Saraiya, Purvi %A North, Chris %A Duca, Karen %B IEEE Transactions on Visualization and Computer Graphics %I IEEE Educational Activities Department %C Piscataway, NJ, USA %V 11 %P 443–456 %G eng %R http://dx.doi.org/10.1109/TVCG.2005.53 %0 Conference Paper %B Compendium of IEEE Symposium on Information Visualization (InfoVis 2005) %D 2005 %T Tracking User Navigation and Performance on High-Resolution Displays using a Dynamic Real-Time Strategy Game %A Ball, Robert %A Sabri, Andrew %A Michael Varghese %A North, Chris %K game %K Large High Resolution Display %K navigation %K performance %B Compendium of IEEE Symposium on Information Visualization (InfoVis 2005) %8 10/2005 %0 Conference Paper %B INFOVIS '05: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization %D 2005 %T Visualization of Graphs with Associated Timeseries Data %A Saraiya, Purvi %A Lee, Peter %A North, Chris %B INFOVIS '05: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization %I IEEE Computer Society %C Washington, DC, USA %P 30 %@ 0-7803-9464-x %G eng %R http://dx.doi.org/10.1109/INFOVIS.2005.37 %0 Journal Article %J Information Visualization %D 2005 %T Visualizing biological pathways: requirements analysis, systems evaluation and research agenda %A Saraiya, Purvi %A North, Chris %A Duca, Karen %B Information Visualization %I Palgrave Macmillan %V 4 %P 191–205 %G eng %R http://dx.doi.org/10.1057/palgrave.ivs.9500102 %0 Conference Paper %B SIGCSE '04: Proceedings of the 35th SIGCSE technical symposium on Computer science education %D 2004 %T Effective features of algorithm visualizations %A Saraiya, Purvi %A Shaffer, Clifford A. %A McCrickard, D. Scott %A North, Chris %B SIGCSE '04: Proceedings of the 35th SIGCSE technical symposium on Computer science education %I ACM %C New York, NY, USA %P 382–386 %@ 1-58113-798-2 %G eng %R http://doi.acm.org/10.1145/971300.971432 %0 Conference Paper %B INFOVIS '04: Proceedings of the IEEE Symposium on Information Visualization %D 2004 %T An Evaluation of Microarray Visualization Tools for Biological Insight %A Saraiya, Purvi %A North, Chris %A Duca, Karen %B INFOVIS '04: Proceedings of the IEEE Symposium on Information Visualization %I IEEE Computer Society %C Washington, DC, USA %P 1–8 %@ 0-7803-8779-3 %G eng %R http://dx.doi.org/10.1109/INFOVIS.2004.5 %0 Conference Paper %B CHI '03: CHI '03 extended abstracts on Human factors in computing systems %D 2003 %T Dynamic query sliders vs. brushing histograms %A Li, Qing %A Bao, Xiaofeng %A Song, Chen %A Zhang, Jinfei %A North, Chris %B CHI '03: CHI '03 extended abstracts on Human factors in computing systems %I ACM %C New York, NY, USA %P 834–835 %@ 1-58113-637-4 %G eng %R http://doi.acm.org/10.1145/765891.766020 %0 Conference Paper %B CHI '03: CHI '03 extended abstracts on Human factors in computing systems %D 2003 %T Fusion: interactive coordination of diverse data, visualizations, and mining algorithms %A North, Chris %A Conklin, Nathan %A Indukuri, Kiran %A Saini, Varun %A Yu, Qiang %B CHI '03: CHI '03 extended abstracts on Human factors in computing systems %I ACM %C New York, NY, USA %P 626–627 %@ 1-58113-637-4 %G eng %R http://doi.acm.org/10.1145/765891.765897 %0 Conference Paper %B VISSYM '02: Proceedings of the symposium on Data Visualisation 2002 %D 2002 %T An evaluation of information visualization in attention-limited environments %A Somervell, Jacob %A McCrickard, D. Scott %A North, Chris %A Shukla, Maulik %B VISSYM '02: Proceedings of the symposium on Data Visualisation 2002 %I Eurographics Association %C Aire-la-Ville, Switzerland, Switzerland %P 211–216 %@ 1-58113-536-X %G eng %0 Journal Article %J Information Visualization %D 2002 %T Visualization schemas and a web-based architecture for custom multiple-view visualization of multiple-table databases %A North, Chris %A Conklin, Nathan %A Indukuri, Kiran %A Saini, Varun %B Information Visualization %I Palgrave Macmillan %V 1 %P 211–228 %G eng %R http://dx.doi.org/10.1057/palgrave.ivs.9500020 %0 Conference Paper %B INFOVIS '02: Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02) %D 2002 %T Visualization Schemas for Flexible Information Visualization %A North, Chris %A Conklin, Nathan %A Saini, Varun %B INFOVIS '02: Proceedings of the IEEE Symposium on Information Visualization (InfoVis'02) %I IEEE Computer Society %C Washington, DC, USA %P 15 %@ 0-7695-1751-X %G eng %0 Conference Paper %B CHI '01: CHI '01 extended abstracts on Human factors in computing systems %D 2001 %T Component-based, user-constructed, multiple-view visualization %A North, Chris %A Shneiderman, Ben %B CHI '01: CHI '01 extended abstracts on Human factors in computing systems %I ACM %C New York, NY, USA %P 201–202 %@ 1-58113-340-5 %G eng %R http://doi.acm.org/10.1145/634067.634188 %0 Conference Paper %B AVI '00: Proceedings of the working conference on Advanced visual interfaces %D 2000 %T Snap-together visualization: a user interface for coordinating visualizations via relational schemata %A North, Chris %A Shneiderman, Ben %B AVI '00: Proceedings of the working conference on Advanced visual interfaces %I ACM %C New York, NY, USA %P 128–135 %@ 1-58113-252-2 %G eng %R http://doi.acm.org/10.1145/345513.345282 %0 Journal Article %J Int. J. Hum.-Comput. Stud. %D 2000 %T Snap-together visualization: can users construct and operate coordinated visualizations? %A North, Chris %A Shneiderman, Ben %B Int. J. Hum.-Comput. Stud. %I Academic Press, Inc. %C Duluth, MN, USA %V 53 %P 715–739 %G eng %R http://dx.doi.org/10.1006/ijhc.2000.0418 %0 Conference Paper %B NPIVM '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 %D 1999 %T Temporal, geographical and categorical aggregations viewed through coordinated displays: a case study with highway incident data %A Fredrikson, Anna %A North, Chris %A Plaisant, Catherine %A Shneiderman, Ben %B NPIVM '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 %I ACM %C New York, NY, USA %P 26–34 %@ 1-58113-254-9 %G eng %R http://doi.acm.org/10.1145/331770.331780 %0 Journal Article %D 1999 %T User controlled overviews of an image library: a case study of the visible human %A North, Chris %A Shneiderman, Ben %A Plaisant, Catherine %I Morgan Kaufmann Publishers Inc. %C San Francisco, CA, USA %P 570–578 %@ 1-55860-533-9 %G eng %0 Conference Paper %B DL '96: Proceedings of the first ACM international conference on Digital libraries %D 1996 %T User controlled overviews of an image library: a case study of the visible human %A North, Chris %A Shneiderman, Ben %A Plaisant, Catherine %B DL '96: Proceedings of the first ACM international conference on Digital libraries %I ACM %C New York, NY, USA %P 74–82 %@ 0-89791-830-4 %G eng %R http://doi.acm.org/10.1145/226931.226946