Institute for Systems Research Technical Reports

Permanent URI for this collectionhttp://hdl.handle.net/1903/4376

This archive contains a collection of reports generated by the faculty and students of the Institute for Systems Research (ISR), a permanent, interdisciplinary research unit in the A. James Clark School of Engineering at the University of Maryland. ISR-based projects are conducted through partnerships with industry and government, bringing together faculty and students from multiple academic departments and colleges across the university.

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Author: search.filters.author.Shneiderman, Ben

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Now showing 1 - 10 of 92
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    Using Categorical Information in Multidimensional Data Sets: Interactive Partition and Cluster Comparison
    (2005) Seo, Jinwook; Shneiderman, Ben; ISR
    Multidimensional data sets often include categorical information. When most columns have categorical information, clustering the data set by similarity of categorical values can reveal interesting patterns in the data set. However, when the data set includes only a small number (one or two) of categorical columns, the categorical information is probably more useful as a way to partition the data set. For example, researchers might be interested in gene expression data for healthy vs. diseased patients or stock performance for common, preferred, or convertible shares. For these cases, we present a novel way to utilize the categorical information together with clustering algorithms. Instead of incorporating categorical information into the clustering process, we can partition the data set according to categorical information. Clustering is then performed with each subset to generate two or more clustering results, each of which is homogeneous (i.e. only includes the same categorical value for the categorical column). By comparing the partitioned clustering results, users can get meaningful insights into the data set: users can identify an interesting group of items that are differentially/similarly expressed in two different homogeneous partitions. The partition can be done in two different directions: (1) by rows if categorical information is available for each column (e.g. some columns are from disease samples and other columns are from healthy samples) or (2) by a column if a column contains categorical information (e.g. a column represents a categorical attribute such as colors or sex). We designed and implemented an interface to facilitate this interactive partition-based clustering results comparison. Coordination between clustering results displays and comparison results overview enables users to identify interesting clusters, and a simple grid display clearly reveals correspondence between two clusters.
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    Bi-Level Hierarchical Layouts for Photo Libraries: Algorithms for Design Optimization with Quantum Content
    (2005) Kustanowitz, Jack; Shneiderman, Ben; ISR
    A frequently-used layout for a collection of two-dimensional, fixed aspect-ratio objects, such as photo thumbnails, is the grid, in which rows and columns are configured to match the allowed space. However, in cases where these objects have some group relationship among them, it can be advantageous to show this relationship in the layout, rather than in textual captions. We use an annotated digital photo collection as a case study of an auto-layout technique in which a two-level hierarchy is generated, consisting of a primary, central region with secondary regions (typically 2-12 regions) surrounding it. We show that given specific requirements, this technique is also optimal, in the sense that it will generate the largest size for the objects. Since all objects are the same size we refer to them as quantum content. These algorithms are designed to be real-time, enabling a compelling interactive display as users resize the canvas, or move and resize the primary region. The interactive redisplay also occurs as users add regions or objects to a secondary region.
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    Knowledge Discovery in High Dimensional Data: Case Studies and a User Survey for an Information Visualization Tool
    (2005) Seo, Jinwook; Shneiderman, Ben; ISR
    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 3-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 email 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.
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    Using Rhythms of Relationships to Understand Email Archives
    (2005) Perer, Adam; Shneiderman, Ben; Oard, Douglas; ISR
    Due to email ubiquitous nature, millions of users are intimate with the technology. However, most users are only familiar with managing their own email, which is an inherently different task than exploring an email archive. Historians and social scientists believe that email archives are important artifacts for understanding the individuals and communities they represent. In order to understand the conversations evidenced in an archive, context is needed. In this paper, we present a new way to gain this necessary context: analyzing the temporal rhythms of social relationships. We provide methods for constructing meaningful rhythms from the email headers by identifying relationships and interpreting their attributes. With these visualization techniques, email archive explorers can uncover insights that may have been otherwise hidden in the archive. We apply our methods to an individual fifteen-year email archive, which consists of about 45,000 messages and over 4,000 relationships.
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    Generating and Querying Semantic Web Environments for Photo Libraries (2005)
    (2005) Axelrod, Adam; Golbeck, Jennifer; Shneiderman, Ben; ISR
    Online photo libraries require a method to efficiently search a collection of photographs, and retrieve photos with similar attributes. Our motivation was to incorporate an existing collection of over 250 photographs of over 200 faculty members and events spanning 7 decades into a library called CS PhotoHistory that is available in hypertext and on the Semantic Web. In this paper, we identify challenges related to making this repository available on the Semantic Web, including issues of automation, modeling, and expressivity. Using CS PhotoHistory as a case study, we describe the process of creating an ontology and a querying interface for interacting with a digital photo library on the Semantic Web.
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    Representing Unevenly-Spaced Time Series Data for Visualization and Interactive Exploration (2005)
    (2005) Aris, Aleks; Shneiderman, Ben; Plaisant, Catherine; Shmueli, Galit; Jank, Wolfgang; ISR
    Visualizing time series data is useful to support discovery of relations and patterns in financial, genomic, medical and other applications. In most time series, measurements are equally spaced over time. This paper discusses the challenges for unevenly-spaced time series data and presents four methods to represent them: sampled events, aggregated sampled events, event index and interleaved event index. We developed these methods while studying eBay auction data with TimeSearcher. We describe the advantages, disadvantages, choices for algorithms and parameters, and compare the different methods. Since each method has its advantages, this paper provides guidance for choosing the right combination of methods, algorithms, and parameters to solve a given problem for unevenly-spaced time series. Interaction issues such as screen resolution, response time for dynamic queries, and meaning of the visual display are governed by these decisions.
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    Meaningful Presentations of Photo Libraries: Rationale and Applications of Bi-Level Radial Quantum Layouts (2005)
    (2005) Kustanowitz, Jack; Shneiderman, Ben; ISR
    Searching photo libraries can be made more satisfying and successful if search results are presented in a way that allows users to gain an overview of the photo categories. Since photo layouts on computer displays are the primary way that users get an overview, we propose a novel approach to show more photos in meaningful groupings. Photo layouts can be linear strips, or zoomable three dimensional arrangements, but the most common form is the flat two-dimensional grid. This paper introduces a novel bi-level hierarchical layout with motivating examples. In a bi-level hierarchy, one region is designated for primary content, which can be a single photo, text, graphic, or combination. Adjacent to that primary region, groups of photos are placed radially in an ordered fashion, such that the relationship of the single primary region to its many secondary regions is immediately apparent. A compelling aspect is the interactive experience in which the layout is dynamically resizable, allowing users to rapidly, incrementally, and reversibly alter the dimensions and content. It can accommodate hundreds of photos in dozens of regions, can be customized in a corner or center layout, and can scale from an element on a web page to a large poster size. On typical displays (1024 x 1280 or 1200 x 1600 pixels), bi-level radial quantum layouts can conveniently accommodate 2-20 regions with tens or hundreds of photos per region.
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    Categorized Graphical Overviews for Web Search Results: An Exploratory Study using U.S. Government Agencies as a Meaningful and Stable Structure (2004)
    (2005) Kules, Bill; Shneiderman, Ben; ISR
    Search engines are very effective at generating long lists of results that are highly relevant to user-provided query terms . But the lack of effective overviews presents challenges to users who seek to understand these results, especially for a complex task such as learning about a topic area, which requires gaining overviews of and exploring large sets of search results, identifying unusual documents, and understanding their context. Categorizing the results into comprehensible visual displays using meaningful and stable classifications can support user exploration and understanding of large sets of search results. This extended abstract presents a set of principles that we are developing for search result visualization. It also describes an exploratory study that investigated categorized overviews of search results for complex search tasks within the domain of U. S. government web sites, using a hierarchy based on the federal government organization.
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    Show Me! Guidelines for Producing Recorded Demonstrations (2005)
    (2005) Plaisant, Catherine; Shneiderman, Ben; ISR
    Although recorded demonstrations (screen capture animations with narration) have become a popular form of instruction for user interfaces, little work has been done to describe guidelines for their design. Based on our experience in several projects, we offer a starting set of guidelines for the design of recorded demonstrations. Technical guidelines encourage users to keep file sizes small, strive for universal usability, and ensure user control etc. and provide tips to achieve those goals. Content guidelines include: create short demonstrations that focus on tasks, highlight each step with auditory and visual cues, synchronize narration and animation carefully, and create demonstrations with a clear beginning, middle, and end.
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    The limits of speech recognition: Understanding acoustic memory and appreciating prosody (2000)
    (2005) Shneiderman, Ben; ISR
    Human-human relationships are rarely a good model for the design of effective user interfaces. Spoken language is effective for human-human interaction (HHI), but it often has severe limitations when applied to human-computer interaction (HCI). Speech is slow for presenting information, it is difficult to review or edit, and it interferes with other cognitive tasks. However speech has proven to be useful for store-and-forward messages, alerts in busy environments, and input-output for blind or motor-impaired users. Speech recognition for control is helpful for hands-busy, eyes-busy, mobilityrequired, or hostile environments and it shows promise for use in telephone-based services. Dictation input is increasingly accurate, but adoption outside the disabled users community has been slow compared to visual interfaces. Obvious physical problems include fatigue from speaking continuously and the disruption in an office filled with people speaking.

    By understanding the cognitive processes surrounding human acoustic memory and processing, interface designers may be able to integrate speech more effectively and guide users more successfully. Then by appreciating the differences between HHI and HCI designers may be able to choose appropriate applications for human use of speech with computers. The key distinction may be the rich emotional content conveyed by prosody -- the pacing, intonation, and amplitude in spoken language. Prosody is potent for HHI, but may be disruptive for HCI.