@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}
}
@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 {17258,
	title = {Interactive sonification of choropleth maps},
	journal = {IEEE Multimedia},
	volume = {12},
	year = {2005},
	month = {2005/06//April},
	pages = {26 - 35},
	abstract = {Auditory information is an important channel for the visually impaired. Effective sonification (the use of non-speech audio to convey information) promotes equal working opportunities for people with vision impairments by helping them explore data collections for problem solving and decision making. Interactive sonification systems can make georeferenced data accessible to people with vision impairments. The authors compare methods for using sound to encode georeferenced data patterns and for navigating maps.},
	keywords = {audio signal processing, audio user interfaces, Auditory (non-speech) feedback, auditory information, cartography, choropleth maps, data collections, decision making, Evaluation, Feedback, georeferenced data, Guidelines, handicapped aids, Hardware, HUMANS, information resources, interaction style, Interactive sonification, interactive systems, Navigation, nonspeech audio, problem solving, Problem-solving, sound, universal usability, US Government, User interfaces, vision impairments, World Wide Web},
	isbn = {1070-986X},
	doi = {10.1109/MMUL.2005.28},
	author = {Zhao,Haixia and Smith,B. K and Norman,K. and Plaisant, Catherine and 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}
}
@article {18849,
	title = {IMACS: a case study in real-world planning},
	journal = {Intelligent Systems and their Applications, IEEE},
	volume = {13},
	year = {1998},
	month = {1998/06//may},
	pages = {49 - 60},
	abstract = {This article discusses the complexities of real-world planning and how to create planning systems to address them. IMACS (Interactive Manufacturability Analysis and Critiquing System), an automated designer{\textquoteright}s aid, evaluates machined parts and suggests design modifications to improve their manufacturability, offering advantages over the planning techniques used in classical planning systems},
	keywords = {automated designer{\textquoteright}s aid, CAD/CAM, case study, computer aided analysis, computer aided production planning, design modifications, IMACS, intelligent design assistants, Interactive Manufacturability Analysis and Critiquing System, interactive systems, machined parts evaluation, machining, manufacturability, planning (artificial intelligence), planning systems},
	isbn = {1094-7167},
	doi = {10.1109/5254.683210},
	author = {Gupta,S.K. and Nau, Dana S. and Regli,W. C.}
}
@conference {17335,
	title = {Query previews in networked information systems},
	booktitle = {Proceedings of the Third Forum on Research and Technology Advances in Digital Libraries, 1996. ADL {\textquoteright}96},
	year = {1996},
	month = {1996/05/13/15},
	pages = {120 - 129},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In a networked information system (such as the NASA Earth Observing System-Data Information System (EOS-DIS)), there are three major obstacles facing users in a querying process: network performance, data volume and data complexity. In order to overcome these obstacles, we propose a two phase approach to query formulation. The two phases are the Query Preview and the Query Refinement. In the Query Preview phase, users formulate an initial query by selecting rough attribute values. The estimated number of matching data sets is shown, graphically on preview bars which allows users to rapidly focus on a manageable number of relevant data sets. Query previews also prevent wasted steps by eliminating zero hit queries. When the estimated number of data sets is long enough, the initial query is submitted to the network which returns the metadata of the data sets for further refinement in the Query Refinement phase. The two phase approach to query formulation overcomes slow network performance, and reduces the data volume and data complexity, problems. This approach is especially appropriate for users who do not have extensive knowledge about the data and who prefer an exploratory method to discover data patterns and exceptions. Using this approach, we have developed dynamic query user interfaces to allow users to formulate their queries across a networked environment},
	keywords = {Computer networks, data complexity, data mining, data patterns, data volume, dynamic query user interfaces, Educational institutions, EOS-DIS, exploratory method, Information retrieval, Information services, Information systems, Intelligent networks, interactive systems, Laboratories, Manipulator dynamics, matching data sets, NASA Earth Observing System-Data Information System, Network performance, networked environment, networked information systems, query formulation, query preview, query refinement, querying process, rough attribute values, User interfaces, visual databases, zero hit queries},
	isbn = {0-8186-7403-2},
	doi = {10.1109/ADL.1996.502522},
	author = {Donn,K. and Plaisant, Catherine and Shneiderman, Ben}
}
@article {17301,
	title = {Multiparty Grammars and Related Features for Defining Interactive Systems},
	journal = {IEEE Transactions on Systems, Man and Cybernetics},
	volume = {12},
	year = {1982},
	month = {1982/03//},
	pages = {148 - 154},
	abstract = {Multiparty grammars are introduced which contain labeled nonterminals to indicate the party that produces the terminal string. For interactive person-computer systems, both the user commands and system responses can be described by the linked BNF grammars. Multiparty grammars may also be used to describe communication among several people (by way of computers or in normal dialogue), network protocols among several machines, or complex interactions involving several people and machines. Visual features such as underlining, reversal, blinking, and color, window declarations, and dynamic operations dependent on cursor movement are also covered.},
	keywords = {Application software, Computer aided instruction, Computer displays, Computer languages, Computer networks, Debugging, HUMANS, interactive systems, Protocols, Writing},
	isbn = {0018-9472},
	doi = {10.1109/TSMC.1982.4308798},
	author = {Shneiderman, Ben}
}
@article {17195,
	title = {Human Factors Experiments in Designing Interactive Systems},
	journal = {Computer},
	volume = {12},
	year = {1979},
	month = {1979/12//},
	pages = {9 - 19},
	abstract = {Successful industrial design gracefully unites esthetics and function at minimum cost. However, designers face special problems when they apply their skills to interactive computer systems.},
	keywords = {Application software, Computer languages, Design engineering, Home computing, human factors, interactive systems, Process design, Testing},
	isbn = {0018-9162},
	doi = {10.1109/MC.1979.1658571},
	author = {Shneiderman, Ben}
}
