@article {17515, title = {A Temporal Pattern Search Algorithm for Personal History Event Visualization}, journal = {Knowledge and Data Engineering, IEEE Transactions on}, volume = {24}, year = {2012}, month = {2012/05//}, pages = {799 - 812}, abstract = {We present Temporal Pattern Search (TPS), a novel algorithm for searching for temporal patterns of events in historical personal histories. The traditional method of searching for such patterns uses an automaton-based approach over a single array of events, sorted by time stamps. Instead, TPS operates on a set of arrays, where each array contains all events of the same type, sorted by time stamps. TPS searches for a particular item in the pattern using a binary search over the appropriate arrays. Although binary search is considerably more expensive per item, it allows TPS to skip many unnecessary events in personal histories. We show that TPS{\textquoteright}s running time is bounded by O(m2n lg(n)), where m is the length of (number of events) a search pattern, and n is the number of events in a record (history). Although the asymptotic running time of TPS is inferior to that of a nondeterministic finite automaton (NFA) approach (O(mn)), TPS performs better than NFA under our experimental conditions. We also show TPS is very competitive with Shift-And, a bit-parallel approach, with real data. Since the experimental conditions we describe here subsume the conditions under which analysts would typically use TPS (i.e., within an interactive visualization program), we argue that TPS is an appropriate design choice for us.}, keywords = {automaton-based approach, binary search, bit-parallel approach, data visualisation, electronic health records, event array, finite automata, interactive visualization program, Lifelines2 visualization tool, medical information systems, NFA approach, nondeterministic finite automaton, O(m2n lg(n)) problem, pattern matching, personal history event visualization, Shift-And approach, temporal pattern search algorithm, time stamp}, isbn = {1041-4347}, doi = {10.1109/TKDE.2010.257}, author = {Wang,T. D and Deshpande, Amol and Shneiderman, Ben} } @conference {17181, title = {Group-in-a-Box Layout for Multi-faceted Analysis of Communities}, booktitle = {Privacy, Security, Risk and Trust (PASSAT), 2011 IEEE Third International Conference on and 2011 IEEE Third International Confernece on Social Computing (SocialCom)}, year = {2011}, month = {2011/10/09/11}, pages = {354 - 361}, publisher = {IEEE}, organization = {IEEE}, abstract = {Communities in social networks emerge from interactions among individuals and can be analyzed through a combination of clustering and graph layout algorithms. These approaches result in 2D or 3D visualizations of clustered graphs, with groups of vertices representing individuals that form a community. However, in many instances the vertices have attributes that divide individuals into distinct categories such as gender, profession, geographic location, and similar. It is often important to investigate what categories of individuals comprise each community and vice-versa, how the community structures associate the individuals from the same category. Currently, there are no effective methods for analyzing both the community structure and the category-based partitions of social graphs. We propose Group-In-a-Box (GIB), a meta-layout for clustered graphs that enables multi-faceted analysis of networks. It uses the tree map space filling technique to display each graph cluster or category group within its own box, sized according to the number of vertices therein. GIB optimizes visualization of the network sub-graphs, providing a semantic substrate for category-based and cluster-based partitions of social graphs. We illustrate the application of GIB to multi-faceted analysis of real social networks and discuss desirable properties of GIB using synthetic datasets.}, keywords = {Algorithm design and analysis, category based social graph partitions, clustered graphs, clustering, Clustering algorithms, Communities, data visualisation, force-directed, gender, geographic location, graph layout algorithms, graph theory, group-in-a-box, group-in-a-box layout, Image edge detection, Layout, meta-layout, multifaceted community analysis, network subgraph visualization, network visualization, pattern clustering, profession, semantic substrates, Social network services, social networking (online), social networks, treemap space filling technique, Visualization}, isbn = {978-1-4577-1931-8}, doi = {10.1109/PASSAT/SocialCom.2011.139}, author = {Rodrigues,E.M. and Milic-Frayling,N. and Smith,M. and Shneiderman, Ben and Hansen,D.} } @conference {17306, title = {NetVisia: Heat Map \& Matrix Visualization of Dynamic Social Network Statistics \& Content}, booktitle = {Privacy, Security, Risk and Trust (PASSAT), 2011 IEEE Third International Conference on and 2011 IEEE Third International Confernece on Social Computing (SocialCom)}, year = {2011}, month = {2011/10/09/11}, pages = {19 - 26}, publisher = {IEEE}, organization = {IEEE}, abstract = {Visualizations of static networks in the form of node-link diagrams have evolved rapidly, though researchers are still grappling with how best to show evolution of nodes over time in these diagrams. This paper introduces NetVisia, a social network visualization system designed to support users in exploring temporal evolution in networks by using heat maps to display node attribute changes over time. NetVisia{\textquoteright}s novel contributions to network visualizations are to (1) cluster nodes in the heat map by similar metric values instead of by topological similarity, and (2) align nodes in the heat map by events. We compare NetVisia to existing systems and describe a formative user evaluation of a NetVisia prototype with four participants that emphasized the need for tool tips and coordinated views. Despite the presence of some usability issues, in 30-40 minutes the user evaluation participants discovered new insights about the data set which had not been discovered using other systems. We discuss implemented improvements to NetVisia, and analyze a co-occurrence network of 228 business intelligence concepts and entities. This analysis confirms the utility of a clustered heat map to discover outlier nodes and time periods.}, keywords = {business intelligence concept, business intelligence entity, competitive intelligence, data visualisation, dynamic networks, dynamic social network, heat map, Heating, Image color analysis, Information Visualization, Layout, matrix visualization, measurement, NetVisia system, network evolution, network visualization, node-link diagrams, outlier node, social network content, Social network services, social network statistics, social networking (online), social networks, static network visualization, time period, topological similarity, Training, usability, user evaluation, User interfaces}, isbn = {978-1-4577-1931-8}, doi = {10.1109/PASSAT/SocialCom.2011.216}, author = {Gove,R. and Gramsky,N. and Kirby,R. and Sefer,E. and Sopan,A. and Dunne,C. and Shneiderman, Ben and Taieb-Maimon,M.} } @conference {17484, title = {Visual Analysis of Temporal Trends in Social Networks Using Edge Color Coding and Metric Timelines}, booktitle = {Privacy, Security, Risk and Trust (PASSAT), 2011 IEEE Third International Conference on and 2011 IEEE Third International Confernece on Social Computing (SocialCom)}, year = {2011}, month = {2011/10/09/11}, pages = {549 - 554}, publisher = {IEEE}, organization = {IEEE}, abstract = {We present Net EvViz, a visualization tool for analysis and exploration of a dynamic social network. There are plenty of visual social network analysis tools but few provide features for visualization of dynamically changing networks featuring the addition or deletion of nodes or edges. Our tool extends the code base of the Node XL template for Microsoft Excel, a popular network visualization tool. The key features of this work are (1) The ability of the user to specify and edit temporal annotations to the network components in an Excel sheet, (2) See the dynamics of the network with multiple graph metrics plotted over the time span of the graph, called the Timeline, and (3) Temporal exploration of the network layout using an edge coloring scheme and a dynamic Time slider. The objectives of the new features presented in this paper are to let the data analysts, computer scientists and others to observe the dynamics or evolution in a network interactively. We presented Net EvViz to five users of Node XL and received positive responses.}, keywords = {Color, computer scientists, data analysts, data visualisation, Data visualization, dynamic social network, dynamic timeslider, edge color coding, excel sheet, Image coding, image colour analysis, Layout, measurement, metric timelines, Microsoft excel, multiple graph metrics, Net EvViz, network components, network layout, network visualization tool, NodeXL template, social networking (online), temporal trends, Twitter, Visualization}, isbn = {978-1-4577-1931-8}, doi = {10.1109/PASSAT/SocialCom.2011.212}, author = {Khurana,U. and Nguyen,Viet-An and Hsueh-Chien Cheng and Ahn,Jae-wook and Chen,Xi and Shneiderman, Ben} } @conference {17423, title = {The state of visual analytics: Views on what visual analytics is and where it is going}, booktitle = {2010 IEEE Symposium on Visual Analytics Science and Technology (VAST)}, year = {2010}, month = {2010/10/25/26}, pages = {257 - 259}, publisher = {IEEE}, organization = {IEEE}, abstract = {In the 2005 publication "Illuminating the Path" visual analytics was defined as "the science of analytical reasoning facilitated by interactive visual interfaces." A lot of work has been done in visual analytics over the intervening five years. While visual analytics started in the United States with a focus on security, it is now a worldwide research agenda with a broad range of application domains. This is evidenced by efforts like the European VisMaster program and the upcoming Visual Analytics and Knowledge Discovery (VAKD) workshop, just to name two.There are still questions concerning where and how visual analytics fits in the large body of research and applications represented by the VisWeek community. This panel will present distinct viewpoints on what visual analytics is and its role in understanding complex information in a complex world. The goal of this panel is to engender discussion from the audience on the emergence and continued advancement of visual analytics and its role relative to fields of related research. Four distinguished panelists will provide their perspective on visual analytics focusing on what it is, what it should be, and thoughts about a development path between these two states. The purpose of the presentations is not to give a critical review of the literature but rather to give a review on the field and to provide a contextual perspective based on the panelists{\textquoteright} years of experience and accumulated knowledge.}, keywords = {analytical reasoning, Data analysis, data mining, data visualisation, European VisMaster program, interactive visual interfaces, knowledge discovery, United States, visual analytics, VisWeek community}, isbn = {978-1-4244-9488-0}, doi = {10.1109/VAST.2010.5649078}, author = {May,R. and Hanrahan,P. and Keim,D. A and Shneiderman, Ben and Card,S.} } @conference {17162, title = {Finding comparable temporal categorical records: A similarity measure with an interactive visualization}, booktitle = {IEEE Symposium on Visual Analytics Science and Technology, 2009. VAST 2009}, year = {2009}, month = {2009/10/12/13}, pages = {27 - 34}, publisher = {IEEE}, organization = {IEEE}, abstract = {An increasing number of temporal categorical databases are being collected: Electronic Health Records in healthcare organizations, traffic incident logs in transportation systems, or student records in universities. Finding similar records within these large databases requires effective similarity measures that capture the searcher{\textquoteright}s intent. Many similarity measures exist for numerical time series, but temporal categorical records are different. We propose a temporal categorical similarity measure, the M\&M (Match \& Mismatch) measure, which is based on the concept of aligning records by sentinel events, then matching events between the target and the compared records. The M\&M measure combines the time differences between pairs of events and the number of mismatches. To accom-modate customization of parameters in the M\&M measure and results interpretation, we implemented Similan, an interactive search and visualization tool for temporal categorical records. A usability study with 8 participants demonstrated that Similan was easy to learn and enabled them to find similar records, but users had difficulty understanding the M\&M measure. The usability study feedback, led to an improved version with a continuous timeline, which was tested in a pilot study with 5 participants.}, keywords = {data visualisation, Educational institutions, Feedback, Information retrieval, interactive search tool, interactive systems, interactive visualization tool, large databases, M\&M Measure, Match \& Mismatch measure, Medical services, numerical time series, parameters customization, Particle measurements, Similan, similarity measure, Similarity Search, temporal categorical databases, Temporal Categorical Records, temporal databases, Testing, Time measurement, time series, transportation, usability, very large databases, visual databases, Visualization}, isbn = {978-1-4244-5283-5}, doi = {10.1109/VAST.2009.5332595}, author = {Wongsuphasawat,K. and Shneiderman, Ben} } @conference {17168, title = {First Steps to Netviz Nirvana: Evaluating Social Network Analysis with NodeXL}, booktitle = {International Conference on Computational Science and Engineering, 2009. CSE {\textquoteright}09}, volume = {4}, year = {2009}, month = {2009/08/29/31}, pages = {332 - 339}, publisher = {IEEE}, organization = {IEEE}, abstract = {Social Network Analysis (SNA) has evolved as a popular, standard method for modeling meaningful, often hidden structural relationships in communities. Existing SNA tools often involve extensive pre-processing or intensive programming skills that can challenge practitioners and students alike. NodeXL, an open-source template for Microsoft Excel, integrates a library of common network metrics and graph layout algorithms within the familiar spreadsheet format, offering a potentially low-barrier-to-entry framework for teaching and learning SNA. We present the preliminary findings of 2 user studies of 21 graduate students who engaged in SNA using NodeXL. The majority of students, while information professionals, had little technical background or experience with SNA techniques. Six of the participants had more technical backgrounds and were chosen specifically for their experience with graph drawing and information visualization. Our primary objectives were (1) to evaluate NodeXL as an SNA tool for a broad base of users and (2) to explore methods for teaching SNA. Our complementary dual case-study format demonstrates the usability of NodeXL for a diverse set of users, and significantly, the power of a tightly integrated metrics/visualization tool to spark insight and facilitate sense-making for students of SNA.}, keywords = {Computer science, computer science education, data visualisation, Data visualization, Educational institutions, graph drawing, graph layout algorithm, Information services, Information Visualization, Internet, Libraries, Microsoft Excel open-source template, MILC, multi-dimensional in-depth long-term case studies, Netviz Nirvana, NodeXL, Open source software, Programming profession, SNA, social network analysis, Social network services, social networking (online), spreadsheet programs, structural relationship, teaching, visual analytics, visualization tool, Web sites}, isbn = {978-1-4244-5334-4}, doi = {10.1109/CSE.2009.120}, author = {Bonsignore,E. M and Dunne,C. and Rotman,D. and Smith,M. and Capone,T. and Hansen,D. L and Shneiderman, Ben} } @article {17238, title = {Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines}, journal = {IEEE Computer Graphics and Applications}, volume = {29}, year = {2009}, month = {2009/06//May}, pages = {39 - 51}, abstract = {Evaluating visual-analytics systems is challenging because laboratory-based controlled experiments might not effectively represent analytical tasks. One such system, Social Action, integrates statistics and visualization in an interactive exploratory tool for social network analysis. This article describes results from long-term case studies with domain experts and extends established design goals for information visualization.}, keywords = {case studies, Control systems, Data analysis, data mining, data visualisation, Data visualization, data-mining, design guidelines, Employment, exploration, Filters, Guidelines, Information Visualization, insights, laboratory-based controlled experiments, Performance analysis, social network analysis, Social network services, social networking (online), social networks, SocialAction, statistical analysis, Statistics, visual analytics, visual-analytics systems, Visualization}, isbn = {0272-1716}, doi = {10.1109/MCG.2009.44}, author = {Perer,A. and Shneiderman, Ben} } @article {17397, title = {Temporal Summaries: Supporting Temporal Categorical Searching, Aggregation and Comparison}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {15}, year = {2009}, month = {2009/12//Nov}, pages = {1049 - 1056}, abstract = {When analyzing thousands of event histories, analysts often want to see the events as an aggregate to detect insights and generate new hypotheses about the data. An analysis tool must emphasize both the prevalence and the temporal ordering of these events. Additionally, the analysis tool must also support flexible comparisons to allow analysts to gather visual evidence. In a previous work, we introduced align, rank, and filter (ARF) to accentuate temporal ordering. In this paper, we present temporal summaries, an interactive visualization technique that highlights the prevalence of event occurrences. Temporal summaries dynamically aggregate events in multiple granularities (year, month, week, day, hour, etc.) for the purpose of spotting trends over time and comparing several groups of records. They provide affordances for analysts to perform temporal range filters. We demonstrate the applicability of this approach in two extensive case studies with analysts who applied temporal summaries to search, filter, and look for patterns in electronic health records and academic records.}, keywords = {Aggregates, Collaborative work, Computational Biology, Computer Graphics, Data analysis, data visualisation, Data visualization, Databases, Factual, Displays, Event detection, Filters, Heparin, History, Human computer interaction, Human-computer interaction, HUMANS, Information Visualization, Interaction design, interactive visualization technique, Medical Records Systems, Computerized, Pattern Recognition, Automated, Performance analysis, Springs, temporal categorical data visualization, temporal categorical searching, temporal ordering, temporal summaries, Thrombocytopenia, Time factors}, isbn = {1077-2626}, doi = {10.1109/TVCG.2009.187}, author = {Wang,T. D and Plaisant, Catherine and Shneiderman, Ben and Spring, Neil and Roseman,D. and Marchand,G. and Mukherjee,V. and Smith,M.} } @article {17250, title = {Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {14}, year = {2008}, month = {2008/10//Sept}, pages = {999 - 1014}, abstract = {Databases often contain uncertain and imprecise references to real-world entities. Entity resolution, the process of reconciling multiple references to underlying real-world entities, is an important data cleaning process required before accurate visualization or analysis of the data is possible. In many cases, in addition to noisy data describing entities, there is data describing the relationships among the entities. This relational data is important during the entity resolution process; it is useful both for the algorithms which determine likely database references to be resolved and for visual analytic tools which support the entity resolution process. In this paper, we introduce a novel user interface, D-Dupe, for interactive entity resolution in relational data. D-Dupe effectively combines relational entity resolution algorithms with a novel network visualization that enables users to make use of an entity{\textquoteright}s relational context for making resolution decisions. Since resolution decisions often are interdependent, D-Dupe facilitates understanding this complex process through animations which highlight combined inferences and a history mechanism which allows users to inspect chains of resolution decisions. An empirical study with 12 users confirmed the benefits of the relational context visualization on the performance of entity resolution tasks in relational data in terms of time as well as users{\textquoteright} confidence and satisfaction.}, keywords = {algorithms, Computer Graphics, D-Dupe, data visualisation, database management systems, Databases, Factual, graphical user interface, Graphical user interfaces, human-centered computing, Image Interpretation, Computer-Assisted, Information Storage and Retrieval, Information Visualization, interactive entity resolution, relational context visualization, Relational databases, relational entity resolution algorithm, User interfaces, user-centered design, User-Computer Interface, visual analytic tool}, isbn = {1077-2626}, doi = {10.1109/TVCG.2008.55}, author = {Kang,Hyunmo and Getoor, Lise and Shneiderman, Ben and Bilgic,M. and Licamele,L.} } @conference {17360, title = {Similarity-Based Forecasting with Simultaneous Previews: A River Plot Interface for Time Series Forecasting}, booktitle = {Information Visualization, 2007. IV {\textquoteright}07. 11th International Conference}, year = {2007}, month = {2007/07/04/6}, pages = {191 - 196}, publisher = {IEEE}, organization = {IEEE}, abstract = {Time-series forecasting has a large number of applications. Users with a partial time series for auctions, new stock offerings, or industrial processes desire estimates of the future behavior. We present a data driven forecasting method and interface called similarity-based forecasting (SBF). A pattern matching search in an historical time series dataset produces a subset of curves similar to the partial time series. The forecast is displayed graphically as a river plot showing statistical information about the SBF subset. A forecasting preview interface allows users to interactively explore alternative pattern matching parameters and see multiple forecasts simultaneously. User testing with 8 users demonstrated advantages and led to improvements.}, keywords = {data driven forecasting method, data visualisation, Data visualization, Economic forecasting, forecasting preview interface, Graphical user interfaces, historical time series dataset, Laboratories, new stock offerings, partial time series, pattern matching, pattern matching search, Predictive models, river plot interface, Rivers, similarity-based forecasting, Smoothing methods, Technological innovation, Testing, time series, time series forecasting, Weather forecasting}, isbn = {0-7695-2900-3}, doi = {10.1109/IV.2007.101}, author = {Buono,P. and Plaisant, Catherine and Simeone,A. and Aris,A. and Shneiderman, Ben and Shmueli,G. and Jank,W.} } @article {16983, title = {Balancing Systematic and Flexible Exploration of Social Networks}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {12}, year = {2006}, month = {2006/10//Sept}, pages = {693 - 700}, abstract = {Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks}, keywords = {Aggregates, algorithms, attribute ranking, Cluster Analysis, Computer Graphics, Computer simulation, Coordinate measuring machines, coordinated views, Data analysis, data visualisation, Data visualization, exploratory data analysis, Filters, Gain measurement, graph theory, Graphical user interfaces, Information Storage and Retrieval, interactive graph visualization, matrix algebra, matrix overview, Models, Biological, Navigation, network visualization, Pattern analysis, Population Dynamics, Social Behavior, social network analysis, Social network services, social networks, social sciences computing, Social Support, SocialAction, software, statistical analysis, statistical methods, User-Computer Interface}, isbn = {1077-2626}, doi = {10.1109/TVCG.2006.122}, author = {Perer,A. and Shneiderman, Ben} } @article {17189, title = {Hierarchical Layouts for Photo Libraries}, journal = {IEEE Multimedia}, volume = {13}, year = {2006}, month = {2006/12//Oct}, pages = {62 - 72}, abstract = {We use an annotated digital photo collection to demonstrate a two-level auto-layout technique consisting of a central primary region with secondary regions surrounding it. Because the object sizes within regions can only be changed in discrete units, we refer to them as quantum content. Our real-time algorithms enable a compelling interactive display as users resize the canvas, or move and resize the primary region}, keywords = {annotated digital photo collection, auto-layout technique, bi-level hierarchies, Computer science, data visualisation, digital libraries, document image processing, Information Visualization, interactive algorithms, interactive displays, Libraries, Lifting equipment, Organization Charts, photo collections, photo layouts, photo library, Photography, quantum content, Silver, Springs, User interfaces, Web pages}, isbn = {1070-986X}, doi = {10.1109/MMUL.2006.83}, author = {Kustanowitz,J. and Shneiderman, Ben} } @article {17272, title = {Knowledge discovery in high-dimensional data: case studies and a user survey for the rank-by-feature framework}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {12}, year = {2006}, month = {2006/06//May}, pages = {311 - 322}, abstract = {Knowledge discovery in high-dimensional data is a challenging enterprise, but new visual analytic tools appear to offer users remarkable powers if they are ready to learn new concepts and interfaces. Our three-year effort to develop versions of the hierarchical clustering explorer (HCE) began with building an interactive tool for exploring clustering results. It expanded, based on user needs, to include other potent analytic and visualization tools for multivariate data, especially the rank-by-feature framework. Our own successes using HCE provided some testimonial evidence of its utility, but we felt it necessary to get beyond our subjective impressions. This paper presents an evaluation of the hierarchical clustering explorer (HCE) using three case studies and an e-mail user survey (n=57) to focus on skill acquisition with the novel concepts and interface for the rank-by-feature framework. Knowledgeable and motivated users in diverse fields provided multiple perspectives that refined our understanding of strengths and weaknesses. A user survey confirmed the benefits of HCE, but gave less guidance about improvements. Both evaluations suggested improved training methods}, keywords = {case study, Computer aided software engineering, Computer Society, Data analysis, data mining, data visualisation, Data visualization, database management systems, e-mail user survey, Genomics, Helium, Hierarchical Clustering Explorer, hierarchical clustering explorer., high-dimensional data, Histograms, Information visualization evaluation, interactive systems, interactive tool, knowledge discovery, multivariate data, Rank-by-feature framework, Scattering, Testing, user interface, User interfaces, user survey, visual analytic tools, visual analytics, visualization tools}, isbn = {1077-2626}, doi = {10.1109/TVCG.2006.50}, author = {Seo,Jinwook and Shneiderman, Ben} } @article {17307, title = {Network Visualization by Semantic Substrates}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {12}, year = {2006}, month = {2006/10//Sept}, pages = {733 - 740}, abstract = {Networks have remained a challenge for information visualization designers because of the complex issues of node and link layout coupled with the rich set of tasks that users present. This paper offers a strategy based on two principles: (1) layouts are based on user-defined semantic substrates, which are non-overlapping regions in which node placement is based on node attributes, (2) users interactively adjust sliders to control link visibility to limit clutter and thus ensure comprehensibility of source and destination. Scalability is further facilitated by user control of which nodes are visible. We illustrate our semantic substrates approach as implemented in NVSS 1.0 with legal precedent data for up to 1122 court cases in three regions with 7645 legal citations}, keywords = {Automatic control, data visualisation, Data visualization, Displays, Filters, Graphical user interfaces, Information Visualization, information visualization designers, Law, legal citations, Legal factors, legal precedent data, network visualization, NVSS 1.0, scalability, semantic substrate, Terminology, Tunneling, user-defined semantic substrates}, isbn = {1077-2626}, doi = {10.1109/TVCG.2006.166}, author = {Shneiderman, Ben and Aris,A.} } @article {16949, title = {A telescope for high-dimensional data}, journal = {Computing in Science \& Engineering}, volume = {8}, year = {2006}, month = {2006/04//March}, pages = {48 - 53}, abstract = {Muscular dystrophy is a degenerative disease that destroys muscles and ultimately kills its victims. Researchers worldwide are racing to find a cure by trying to uncover the genetic processes that cause it. Given that a key process is muscle development, researchers at a consortium of 10 institutions are studying 1,000 men and women, ages 18 to 40 years, to see how their muscles enlarge with exercise. The 150 variables collected for each participant will make this data analysis task challenging for users of traditional statistical software tools. However, a new approach to visual data analysis is helping these researchers speed up their work. At the University of Maryland{\textquoteright}s Human-Computer Interaction Library, we developed an interactive approach to let researchers explore high-dimensional data in an orderly manner, focusing on specific features one at a time. The rank-by-feature framework lets them adjust controls to specify what they{\textquoteright}re looking for, and then, with only a glance, they can spot strong relationships among variables, find tight data clusters, or identify unexpected gaps. Sometimes surprising outliers invite further study as to whether they represent errors or an unusual outcome. Similar data analysis problems come up in meteorology, finance, chemistry, and other sciences in which complex relationships among many variables govern outcomes. The rank-by-feature framework could be helpful to many researchers, engineers, and managers because they can then steer their analyses toward the action}, keywords = {Chemistry, Data analysis, data mining, data visualisation, degenerative disease, Degenerative diseases, diseases, Finance, genetic process, Genetics, high-dimensional data, interactive data analysis, medical computing, Meteorology, muscle, muscle development, Muscles, muscular dystrophy, Rank-by-feature framework, software, software libraries, software tools, Telescopes, visual data, visual data analysis}, isbn = {1521-9615}, doi = {10.1109/MCSE.2006.21}, author = {Shneiderman, Ben} } @conference {16951, title = {A Visual Interface for Multivariate Temporal Data: Finding Patterns of Events across Multiple Histories}, booktitle = {Visual Analytics Science And Technology, 2006 IEEE Symposium On}, year = {2006}, month = {2006/11/31/Oct. }, pages = {167 - 174}, publisher = {IEEE}, organization = {IEEE}, abstract = {Finding patterns of events over time is important in searching patient histories, Web logs, news stories, and criminal activities. This paper presents PatternFinder, an integrated interface for query and result-set visualization for search and discovery of temporal patterns within multivariate and categorical data sets. We define temporal patterns as sequences of events with inter-event time spans. PatternFinder allows users to specify the attributes of events and time spans to produce powerful pattern queries that are difficult to express with other formalisms. We characterize the range of queries PatternFinder supports as users vary the specificity at which events and time spans are defined. Pattern Finder{\textquoteright}s query capabilities together with coupled ball-and-chain and tabular visualizations enable users to effectively query, explore and analyze event patterns both within and across data entities (e.g. patient histories, terrorist groups, Web logs, etc.)}, keywords = {ball-and-chain visualization, Chromium, Computer science, Data analysis, data visualisation, Data visualization, Database languages, event pattern discovery, Graphical user interfaces, History, Information Visualization, Medical treatment, multivariate temporal data, Pattern analysis, pattern recognition, PatternFinder integrated interface, Query processing, query visualization, result-set visualization, Spatial databases, tabular visualization, temporal pattern discovery, temporal pattern searching, Temporal query, user interface, User interfaces, visual databases, visual interface}, isbn = {1-4244-0591-2}, doi = {10.1109/VAST.2006.261421}, author = {Fails,J. A and Karlson,A. and Shahamat,L. and Shneiderman, Ben} } @conference {17444, title = {Turning information visualization innovations into commercial products: lessons to guide the next success}, booktitle = {IEEE Symposium on Information Visualization, 2005. INFOVIS 2005}, year = {2005}, month = {2005/10/23/25}, pages = {241 - 244}, publisher = {IEEE}, organization = {IEEE}, abstract = {As information visualization matures as an academic research field, commercial spinoffs are proliferating, but success stories are harder to find. This is the normal process of emergence for new technologies, but the panel organizers believe that there are certain strategies that facilitate success. To teach these lessons, we have invited several key figures who are seeking to commercialize information visualization tools. The panelists make short presentations, engage in a moderated discussion, and respond to audience questions.}, keywords = {Books, commercial development, commercial product, Computer interfaces, Computer science, data visualisation, Data visualization, Educational institutions, exploratory data analysis, information visualization innovation, information visualization tool, innovation management, Laboratories, Management training, new technology emergence, Technological innovation, technology transfer, Turning, User interfaces}, isbn = {0-7803-9464-X}, doi = {10.1109/INFVIS.2005.1532153}, author = {Shneiderman, Ben and Rao,R. and Andrews,K. and Ahlberg,C. and Brodbeck,D. and Jewitt,T. and Mackinlay,J.} } @conference {17155, title = {Extending the utility of treemaps with flexible hierarchy}, booktitle = {Eighth International Conference on Information Visualisation, 2004. IV 2004. Proceedings}, year = {2004}, month = {2004/07/14/16}, pages = {335 - 344}, publisher = {IEEE}, organization = {IEEE}, abstract = {Treemaps are a visualization technique for presenting hierarchical information on two-dimensional displays. Prior implementations limit the visualization to pre-defined static hierarchies. Flexible hierarchy, a new capability of Treemap 4.0, enables users to define various hierarchies through dynamically selecting a series of data attributes so that they can discover patterns, clusters and outliers. This work describes the design and implementation issues of flexible hierarchy. It then reports on a usability study, which led to enhancements to the interface.}, keywords = {2D displays, Computer displays, Computer science, data visualisation, Data visualization, Educational institutions, flexible hierarchy, graphical user interface, Graphical user interfaces, hierarchical information, Nominations and elections, Switches, Tree data structures, Tree graphs, Treemap 4.0, Two dimensional displays, usability, visualization technique}, isbn = {0-7695-2177-0}, doi = {10.1109/IV.2004.1320166}, author = {Chintalapani,G. and Plaisant, Catherine and Shneiderman, Ben} } @conference {17159, title = {Facilitating understanding of information visualizations: emerging principles and examples}, booktitle = {Eighth International Conference on Information Visualisation, 2004. IV 2004. Proceedings}, year = {2004}, month = {2004/07/14/16}, publisher = {IEEE}, organization = {IEEE}, abstract = {Summary form only given. The enthusiasm for information visualization has generated a wide variety of interesting tools for multi-dimensional, hierarchical, and other kinds of visualizations. However, some designs are readily accepted as understandable and useful, while others are perceived as confusing and useless. Controlled studies have begun to sort of some of the issues, but the insights of designers and usability tests are contributing interesting cognitive hypotheses for researchers and practical guidelines for developers. This paper offers examples of what works and what doesn{\textquoteright}t with a preliminary set of principles that might have wide applicability.}, keywords = {Computer science, data visualisation, Educational institutions, Guidelines, hierarchical visualization, HUMANS, Information Visualization, Laboratories, multidimensional visualization, Portable computers, Testing, usability, User interfaces, Visualization}, isbn = {0-7695-2177-0}, doi = {10.1109/IV.2004.1320117}, author = {Shneiderman, Ben} } @conference {16944, title = {A Rank-by-Feature Framework for Unsupervised Multidimensional Data Exploration Using Low Dimensional Projections}, booktitle = {IEEE Symposium on Information Visualization, 2004. INFOVIS 2004}, year = {2004}, month = {2004///}, pages = {65 - 72}, publisher = {IEEE}, organization = {IEEE}, abstract = {Exploratory analysis of multidimensional data sets is challenging because of the difficulty in comprehending more than three dimensions. Two fundamental statistical principles for the exploratory analysis are (1) to examine each dimension first and then find relationships among dimensions, and (2) to try graphical displays first and then find numerical summaries (D.S. Moore, (1999). We implement these principles in a novel conceptual framework called the rank-by-feature framework. In the framework, users can choose a ranking criterion interesting to them and sort 1D or 2D axis-parallel projections according to the criterion. We introduce the rank-by-feature prism that is a color-coded lower-triangular matrix that guides users to desired features. Statistical graphs (histogram, boxplot, and scatterplot) and information visualization techniques (overview, coordination, and dynamic query) are combined to help users effectively traverse 1D and 2D axis-parallel projections, and finally to help them interactively find interesting features}, keywords = {axis-parallel projections, boxplot, color-coded lower-triangular matrix, computational complexity, computational geometry, Computer displays, Computer science, Computer vision, Data analysis, data mining, data visualisation, Data visualization, Displays, dynamic query, Educational institutions, exploratory data analysis, feature detection, feature detection/selection, Feature extraction, feature selection, graph theory, graphical displays, histogram, Information Visualization, interactive systems, Laboratories, Multidimensional systems, Principal component analysis, rank-by-feature prism, scatterplot, statistical analysis, statistical graphics, statistical graphs, unsupervised multidimensional data exploration, very large databases}, isbn = {0-7803-8779-3}, doi = {10.1109/INFVIS.2004.3}, author = {Seo,J. and Shneiderman, Ben} } @article {17259, title = {Interactively exploring hierarchical clustering results [gene identification]}, journal = {Computer}, volume = {35}, year = {2002}, month = {2002/07//}, pages = {80 - 86}, abstract = {To date, work in microarrays, sequenced genomes and bioinformatics has focused largely on algorithmic methods for processing and manipulating vast biological data sets. Future improvements will likely provide users with guidance in selecting the most appropriate algorithms and metrics for identifying meaningful clusters-interesting patterns in large data sets, such as groups of genes with similar profiles. Hierarchical clustering has been shown to be effective in microarray data analysis for identifying genes with similar profiles and thus possibly with similar functions. Users also need an efficient visualization tool, however, to facilitate pattern extraction from microarray data sets. The Hierarchical Clustering Explorer integrates four interactive features to provide information visualization techniques that allow users to control the processes and interact with the results. Thus, hybrid approaches that combine powerful algorithms with interactive visualization tools will join the strengths of fast processors with the detailed understanding of domain experts}, keywords = {algorithmic methods, arrays, Bioinformatics, biological data sets, biology computing, Data analysis, data mining, data visualisation, Data visualization, DNA, Fluorescence, gene functions, gene identification, gene profiles, Genetics, Genomics, Hierarchical Clustering Explorer, hierarchical systems, interactive exploration, interactive information visualization tool, interactive systems, Large screen displays, meaningful cluster identification, metrics, microarray data analysis, pattern clustering, pattern extraction, Process control, Sensor arrays, sequenced genomes, Tiles}, isbn = {0018-9162}, doi = {10.1109/MC.2002.1016905}, author = {Seo,Jinwook and Shneiderman, Ben} } @conference {17859, title = {Scheduling multiple data visualization query workloads on a shared memory machine}, booktitle = {Parallel and Distributed Processing Symposium., Proceedings International, IPDPS 2002, Abstracts and CD-ROM}, year = {2002}, month = {2002///}, pages = {11 - 18}, publisher = {IEEE}, organization = {IEEE}, abstract = {Query scheduling plays an important role when systems are faced with limited resources and high workloads. It becomes even more relevant for servers applying multiple query optimization techniques to batches of queries, in which portions of datasets as well as intermediate results are maintained in memory to speed up query evaluation. We present a dynamic query scheduling model based on a priority queue implementation using a directed graph and a strategy for ranking queries. We examine the relative performance of several ranking strategies on a shared-memory machine using two different versions of an application, called the Virtual Microscope, for browsing digitized microscopy images}, keywords = {Atomic force microscopy, Biomedical informatics, Computer science, Data analysis, data visualisation, Data visualization, datasets, deductive databases, digitized microscopy image browsing, directed graph, directed graphs, dynamic query scheduling model, Educational institutions, high workloads, image database, limited resources, multiple data visualization query workloads, multiple query optimization, performance, priority queue, Processor scheduling, Query processing, query ranking, Relational databases, scheduling, shared memory machine, shared memory systems, Virtual Microscope, visual databases}, isbn = {0-7695-1573-8}, doi = {10.1109/IPDPS.2002.1015482}, author = {Andrade,H. and Kurc, T. and Sussman, Alan and Saltz, J.} } @conference {17101, title = {Dynamic queries and brushing on choropleth maps}, booktitle = {Fifth International Conference on Information Visualisation, 2001. Proceedings}, year = {2001}, month = {2001///}, pages = {757 - 764}, publisher = {IEEE}, organization = {IEEE}, abstract = {Users who must combine demographic, economic or other data in a geographic context are often hampered by the integration of tabular and map representations. Static, paper-based solutions limit the amount of data that can be placed on a single map or table. By providing an effective user interface, we believe that researchers, journalists, teachers, and students can explore complex data sets more rapidly and effectively. This paper presents Dynamaps, a generalized map-based information visualization tool for dynamic queries and brushing on choropleth maps. Users can use color coding to show a variable on each geographic region, and then filter out areas that do not meet the desired criteria. In addition, a scatterplot view and a details-on-demand window support overviews and specific fact-finding}, keywords = {brushing, business, cartography, choropleth maps, color coding, colour graphics, complex data sets, Computational Intelligence Society, Computer science, data visualisation, Data visualization, demographic data, Demography, Dynamaps, dynamic queries, economic data, Educational institutions, geographic information system, geographic information systems, Joining processes, map representations, map-based information visualization, Query processing, Scattering, scatterplot view, tabular representations, user interface, User interfaces, World Wide Web}, isbn = {0-7695-1195-3}, doi = {10.1109/IV.2001.942141}, author = {Dang,G. and North,C. and Shneiderman, Ben} } @conference {16466, title = {Optimized seamless integration of biomolecular data}, booktitle = {Proceedings of the IEEE 2nd International Symposium on Bioinformatics and Bioengineering Conference, 2001}, year = {2001}, month = {2001/11/04/6}, pages = {23 - 32}, publisher = {IEEE}, organization = {IEEE}, abstract = {Today, scientific data is inevitably digitized, stored in a variety of heterogeneous formats, and is accessible over the Internet. Scientists need to access an integrated view of multiple remote or local heterogeneous data sources. They then integrate the results of complex queries and apply further analysis and visualization to support the task of scientific discovery. Building a digital library for scientific discovery requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web, as well as data that is locally materialized in warehouses or is generated by software. We consider several tasks to provide optimized and seamless integration of biomolecular data. Challenges to be addressed include capturing and representing source capabilities; developing a methodology to acquire and represent metadata about source contents and access costs; and decision support to select sources and capabilities using cost based and semantic knowledge, and generating low cost query evaluation plans}, keywords = {analysis, Bioinformatics, biology computing, cost based knowledge, Costs, Data analysis, data mining, data visualisation, Data visualization, Data warehouses, decision support, digital library, Educational institutions, information resources, Internet, low cost query evaluation plans, Mediation, meta data, metadata, molecular biophysics, multiple local heterogeneous data sources, multiple remote heterogeneous data sources, optimized seamless biomolecular data integration, scientific discovery, scientific information systems, semantic knowledge, software libraries, visual databases, Visualization}, isbn = {0-7695-1423-5}, doi = {10.1109/BIBE.2001.974408}, author = {Eckman,B. A and Lacroix,Z. and Raschid, Louiqa} } @article {17842, title = {Visualization of large data sets with the Active Data Repository}, journal = {IEEE Computer Graphics and Applications}, volume = {21}, year = {2001}, month = {2001/08//Jul}, pages = {24 - 33}, abstract = {We implement ray-casting-based volume rendering and isosurface rendering methods using the Active Data Repository (ADR) for visualizing out-of-core data sets. We have developed the ADR object-oriented framework to provide support for applications that employ range queries with user-defined mapping and aggregation operations on large-scale multidimensional data. ADR targets distributed-memory parallel machines with one or more disks attached to each node. It is designed as a set of modular services implemented in C++, which can be customized for application-specific processing. The ADR runtime system supports common operations such as memory management, data retrieval, and scheduling of processing across a parallel machine}, keywords = {active data repository, ADR runtime system, Algorithm design and analysis, application-specific processing, C++, data mining, data retrieval, data visualisation, Data visualization, distributed-memory parallel machines, Indexing, Information retrieval, isosurface rendering, Isosurfaces, large data sets, large-scale multidimensional data, Memory management, modular services, out-of-core data sets, parallel machine, Parallel machines, Partitioning algorithms, ray-casting-based volume rendering, Rendering (computer graphics), Runtime, software libraries, storage management}, isbn = {0272-1716}, doi = {10.1109/38.933521}, author = {Kurc, T. and Catalyurek,U. and Chang,Chialin and Sussman, Alan and Saltz, J.} } @conference {12197, title = {Domain name based visualization of Web histories in a zoomable user interface}, booktitle = {11th International Workshop on Database and Expert Systems Applications, 2000. Proceedings}, year = {2000}, month = {2000///}, pages = {591 - 598}, publisher = {IEEE}, organization = {IEEE}, abstract = {Users of hypertext systems like the World Wide Web (WWW) often find themselves following hypertext links deeper and deeper, only to find themselves {\textquotedblleft}lost{\textquotedblright} and unable to find their way back to the previously visited pages. We have implemented a Web browser companion called Domain Tree Browser (DTB) that builds a tree structured visual navigation history while browsing the Web. The Domain Tree Browser organizes the URLs visited based on the domain name of each URL and shows thumbnails of each page in a zoomable window}, keywords = {Computer science, data visualisation, domain name, domain name based visualization, Domain Tree Browser, Educational institutions, History, hypermedia, hypertext links, hypertext systems, information resources, Navigation, online front-ends, thumbnails, Tree graphs, tree structured visual navigation history, Uniform resource locators, URLs, User interfaces, Visualization, Web browser companion, Web histories, Web pages, World Wide Web, zoomable user interface, zoomable window}, isbn = {0-7695-0680-1}, doi = {10.1109/DEXA.2000.875085}, author = {Gandhi,R. and Kumar,G. and Bederson, Benjamin B. and Shneiderman, Ben} } @conference {17056, title = {Design and evaluation of incremental data structures and algorithms for dynamic query interfaces}, booktitle = {IEEE Symposium on Information Visualization, 1997. Proceedings}, year = {1997}, month = {1997/10/21/21}, pages = {81 - 86}, publisher = {IEEE}, organization = {IEEE}, abstract = {A dynamic query interface (DQI) is a database access mechanism that provides continuous real-time feedback to the user during query formulation. Previous work shows that DQIs are elegant and powerful interfaces to small databases. Unfortunately, when applied to large databases, previous DQI algorithms slow to a crawl. We present a new incremental approach to DQI algorithms and display updates that work well with large databases, both in theory and in practice.}, keywords = {Algorithm design and analysis, Bars, Computer science, continuous real-time feedback, Data structures, data visualisation, Data visualization, database access mechanism, Displays, DQI algorithms, dynamic query interfaces, Feedback, Graphical user interfaces, Heuristic algorithms, incremental data structures, Information Visualization, large databases, Manipulator dynamics, NASA, query formulation, query languages, Query processing, real-time systems, small databases, User interfaces, very large databases, visual databases, visual languages}, isbn = {0-8186-8189-6}, doi = {10.1109/INFVIS.1997.636790}, author = {Tanin,E. and Beigel,R. and Shneiderman, Ben} } @conference {17412, title = {The eyes have it: a task by data type taxonomy for information visualizations}, booktitle = {, IEEE Symposium on Visual Languages, 1996. Proceedings}, year = {1996}, month = {1996/09/03/6}, pages = {336 - 343}, publisher = {IEEE}, organization = {IEEE}, abstract = {A useful starting point for designing advanced graphical user interfaces is the visual information seeking Mantra: overview first, zoom and filter, then details on demand. But this is only a starting point in trying to understand the rich and varied set of information visualizations that have been proposed in recent years. The paper offers a task by data type taxonomy with seven data types (one, two, three dimensional data, temporal and multi dimensional data, and tree and network data) and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts)}, keywords = {advanced graphical user interface design, Art, data mining, data type taxonomy, data visualisation, Data visualization, Displays, Eyes, Graphical user interfaces, Information filtering, Information filters, information visualizations, multi dimensional data, Multimedia databases, network data, Taxonomy, visual databases, visual information seeking, visual programming}, isbn = {0-8186-7508-X}, doi = {10.1109/VL.1996.545307}, author = {Shneiderman, Ben} } @conference {17943, title = {Voxel based object simplification}, booktitle = {Proceedings of the 6th conference on Visualization {\textquoteright}95}, series = {VIS {\textquoteright}95}, year = {1995}, month = {1995///}, pages = {296{\textendash} - 296{\textendash}}, publisher = {IEEE Computer Society}, organization = {IEEE Computer Society}, address = {Washington, DC, USA}, abstract = {Presents a simple, robust and practical method for object simplification for applications where gradual elimination of high-frequency details is desired. This is accomplished by sampling and low-pass filtering the object into multi-resolution volume buffers and applying the marching cubes algorithm to generate a multi-resolution triangle-mesh hierarchy. Our method simplifies the genus of objects and can also help existing object simplification algorithms achieve better results. At each level of detail, a multi-layered mesh can be used for an optional and efficient antialiased rendering.}, keywords = {antialiased rendering, antialiasing, buffer storage, data visualisation, high-frequency detail elimination, low-pass filtering, low-pass filters, marching cubes algorithm, mesh generation, multi-layered mesh, multi-resolution triangle-mesh hierarchy, multi-resolution volume buffers, object genus, Rendering (computer graphics), sampling, Smoothing methods, voxel based object simplification}, isbn = {0-8186-7187-4}, url = {http://dl.acm.org/citation.cfm?id=832271.833850}, author = {He,Taosong and Hong,Lichan and Kaufman,A. and Varshney, Amitabh and Wang,S.} } @conference {14760, title = {Dynamic program instrumentation for scalable performance tools}, booktitle = {Scalable High-Performance Computing Conference, 1994., Proceedings of the}, year = {1994}, month = {1994/05//}, pages = {841 - 850}, publisher = {IEEE}, organization = {IEEE}, abstract = {Presents a new technique called {\textquoteleft}dynamic instrumentation{\textquoteright} that provides efficient, scalable, yet detailed data collection for large-scale parallel applications. Our approach is unique because it defers inserting any instrumentation until the application is in execution. We can insert or change instrumentation at any time during execution by modifying the application{\textquoteright}s binary image. Only the instrumentation required for the currently selected analysis or visualization is inserted. As a result, our technique collects several orders of magnitude less data than traditional data collection approaches. We have implemented a prototype of our dynamic instrumentation on the CM-5, and present results for several real applications. In addition, we include recommendations to operating system designers, compiler writers, and computer architects about the features necessary to permit efficient monitoring of large-scale parallel systems}, keywords = {Application software, binary image, compiler writing, Computer architecture, Computer displays, Computerized monitoring, Concurrent computing, data acquisition, data collection, data visualisation, Data visualization, dynamic program instrumentation, efficient monitoring, executing program, Instruments, large-scale parallel applications, Large-scale systems, operating system design, Operating systems, parallel programming, program analysis, program diagnostics, program visualization, Programming profession, Sampling methods, scalable performance tools, software tools}, isbn = {0-8186-5680-8}, doi = {10.1109/SHPCC.1994.296728}, author = {Hollingsworth, Jeffrey K and Miller, B. P and Cargille, J.} }