Generative AI (GenAI) has shifted AI capabilities from discriminative prediction to creative interaction, offering opportunities to augment productivity and innovation. However, realizing these benefits requires navigating risks where development outpaces governance. This article revisits the Six Human-Centered AI (HCAI) Grand Challenges to analyze their relevance in the generative era. Critical new requirements are identified: preserving human autonomy, ensuring operational safety against non-deterministic outputs, and navigating complex intellectual property landscapes. These findings are synthesized into an updated, actionable research agenda for each challenge, serving as a call to action to operationalize these principles. By shifting focus from risk mitigation to human empowerment, this agenda establishes human-centeredness as the organizing principle for a future where GenAI enhances human agency, dignity, and collective flourishing.

Time-stamped event sequences (TSEQs) are time-oriented data without value information, shifting the focus of users to the exploration of temporal event occurrences. TSEQs exist in application domains, such as sleeping behavior, earthquake aftershocks, and stock market crashes. Domain experts face four challenges, for which they could use interactive and visual data analysis methods. First, TSEQs can be large with respect to both the number of sequences and events, often leading to millions of events. Second, domain experts need validated metrics and features to identify interesting patterns. Third, after identifying interesting patterns, domain experts contextualize the patterns to foster sensemaking. Finally, domain experts seek to reduce data complexity by data simplification and machine learning support. We present IVESA, a visual analytics approach for TSEQs. It supports the analysis of TSEQs at the granularities of sequences and events, supported with metrics and feature analysis tools. IVESA has multiple linked views that support overview, sort+filter, comparison, details-on-demand, and metadata relation-seeking tasks, as well as data simplification through feature analysis, interactive clustering, filtering, and motif detection and simplification. We evaluated IVESA with three case studies and a user study with six domain experts working with six different datasets and applications. Results demonstrate the usability and generalizability of IVESA across applications and cases that had up to 1,000,000 events.

Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are human-centered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human well-being, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human’s cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies.

I eagerly support Peter Hancock’s desire to avoid adverse autonomous agent actions, but I think that he should change from his negative and pessimistic view to a more constructive stance about how ...

Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility.

This article attempts to bridge the gap between widely discussed ethical principles of Human-centered AI (HCAI) and practical steps for effective governance. Since HCAI systems are developed and implemented in multiple organizational structures, I propose 15 recommendations at three levels of governance: team, organization, and industry. The recommendations are intended to increase the reliability, safety, and trustworthiness of HCAI systems: (1) reliable systems based on sound software engineering practices, (2) safety culture through business management strategies, and (3) trustworthy certification by independent oversight. Software engineering practices within teams include audit trails to enable analysis of failures, software engineering workflows, verification and validation testing, bias testing to enhance fairness, and explainable user interfaces. The safety culture within organizations comes from management strategies that include leadership commitment to safety, hiring and training oriented to safety, extensive reporting of failures and near misses, internal review boards for problems and future plans, and alignment with industry standard practices. The trustworthiness certification comes from industry-wide efforts that include government interventions and regulation, accounting firms conducting external audits, insurance companies compensating for failures, non-governmental and civil society organizations advancing design principles, and professional organizations and research institutes developing standards, policies, and novel ideas. The larger goal of effective governance is to limit the dangers and increase the benefits of HCAI to individuals, organizations, and society.

People use recommender systems to improve their decisions; for example, item recommender systems help them find films to watch or books to buy. Despite the ubiquity of item recommender systems, they can be improved by giving users greater transparency and control. This article develops and assesses interactive strategies for transparency and control, as applied to event sequence recommender systems, which provide guidance in critical life choices such as medical treatments, careers decisions, and educational course selections. This article’s main contribution is the use of both record attributes and temporal event information as features to identify similar records and provide appropriate recommendations. While traditional item recommendations are based on choices by people with similar attributes, such as those who looked at this product or watched this movie, our event sequence recommendation approach allows users to select records that share similar attribute values and start with a similar event sequence. Then users see how different choices of actions and the orders and times between them might lead to users’ desired outcomes. This paper applies a visual analytics approach to present and explain recommendations of event sequences. It presents a workflow for event sequence recommendation that is implemented in EventAction and reports on three case studies in two domains to illustrate the use of generating event sequence recommendations based on personal histories. It also offers design guidelines for the construction of user interfaces for event sequence recommendation and discusses ethical issues in dealing with personal histories. A demo video of EventAction is available at https://hcil.umd.edu/eventaction.

Recommendation applications can guide users in making important life choices by referring to the activities of similar peers. For example, students making academic plans may learn from the data of similar students, while patients and their physicians may explore data from similar patients to select the best treatment. Selecting an appropriate peer group has a strong impact on the value of the guidance that can result from analyzing the peer group data. In this article, we describe a visual interface that helps users review the similarity and differences between a seed record and a group of similar records and refine the selection. We introduce the LikeMeDonuts, Ranking Glyph, and History Heatmap visualizations. The interface was refined through three rounds of formative usability evaluation with 12 target users, and its usefulness was evaluated by a case study with a student review manager using real student data. We describe three analytic workflows observed during use and summarize how users’ input shaped the final design.

Wrong-patient errors from inadvertent menu selections while using computerized provider order entry (CPOE) systems could have fatal consequences. This study investigated whether the manipulation of CPOE interface design could improve healthcare providers’ ability to recognize patient selection errors and also decrease the time to error recognition. Using a 2 × 2 design, 120 participants were randomly assigned to one of four groups, interacting with different versions of a simulated CPOE: (1) control – standard version; (2) highlighted selection – the selected patient row was highlighted for 2 s, by blanking the rest of the screen; (3) photo – photographs of patients’ faces were displayed in all screens; (4) combined – with photo and highlighted selection. Each participant navigated through five order scenarios. On the last scenario, an error was simulated by directing the participant to a wrong patient. Recognition rates of the wrong-patient error and times to error recognition were significantly improved for the highlighted selection, photo, and combined groups, relative to the control group. These results suggest that the addition of patient photos and highlighted selection could substantially reduce errors in CPOE systems and other applications.

People often seek examples of similar individuals to guide their own life choices. For example, students making academic plans refer to friends; patients refer to acquaintances with similar conditions, physicians mention past cases seen in their practice. How would they want to search for similar people in databases? We discuss the challenge of finding similar people to guide life choices and report on a need analysis based on 13 interviews. Our PeerFinder prototype enables users to find records that are similar to a seed record, using both record attributes and temporal events found in the records. A user study with 18 participants and four experts shows that users are more engaged and more confident about the value of the results to provide useful evidence to guide life choices when provided with more control over the search process and more context for the results, even at the cost of added complexity.

The growing volume and variety of data presents both opportunities and challenges for visual analytics. Addressing these challenges is needed for big data to provide valuable insights and novel solutions for business, security, social media, and healthcare. In the case of temporal event sequence analytics it is the number of events in the data and variety of temporal sequence patterns that challenges users of visual analytic tools. This paper describes 15 strategies for sharpening analytic focus that analysts can use to reduce the data volume and pattern variety. Four groups of strategies are proposed: (1) extraction strategies, (2) temporal folding, (3) pattern simplification strategies, and (4) iterative strategies. For each strategy, we provide examples of the use and impact of this strategy on volume and/or variety. Examples are selected from 20 case studies gathered from either our own work, the literature, or based on email interviews with individuals who conducted the analyses and developers who observed analysts using the tools. Finally, we discuss how these strategies might be combined and report on the feedback from 10 senior event sequence analysts.

Medical treatments carry unique benefits and risks which patients must understand in order to decide which option is best for them. Prior research has demonstrated that patients are ill-equipped to understand the statistical information presented to them through standard decision aids. We describe a prototype decision aid, TreatmentExplorer, which supports patients’ needs by presenting treatment outcome, onset of symptoms and treatment side effects using a novel graphic representation with staged animation and text-only narration. Our prototype also illustrates the use of a data-driven personalization approach by using electronic health record data. We report on expert reviews, a pilot study (⁠|$n=24$|⁠) and a main study (⁠|$n=42$|⁠), which characterize the benefits of TreatmentExplorer over a text-only decision aid as well as a version without staged animation, and conclude with guidelines for designers.

Cohort comparison studies have traditionally been hypothesis driven and conducted in carefully controlled environments (such as clinical trials). Given two groups of event sequence data, researchers test a single hypothesis (e.g., does the group taking Medication A exhibit more deaths than the group taking Medication B?). Recently, however, researchers have been moving toward more exploratory methods of retrospective analysis with existing data. In this article, we begin by showing that the task of cohort comparison is specific enough to support automatic computation against a bounded set of potential questions and objectives, a method that we refer to as High-Volume Hypothesis Testing (HVHT). From this starting point, we demonstrate that the diversity of these objectives, both across and within different domains, as well as the inherent complexities of real-world datasets, still requires human involvement to determine meaningful insights. We explore how visualization and interaction better support the task of exploratory data analysis and the understanding of HVHT results (how significant they are, why they are meaningful, and whether the entire dataset has been exhaustively explored). Through interviews and case studies with domain experts, we iteratively design and implement visualization and interaction techniques in a visual analytics tool, CoCo. As a result of our evaluation, we propose six design guidelines for enabling users to explore large result sets of HVHT systematically and flexibly in order to glean meaningful insights more quickly. Finally, we illustrate the utility of this method with three case studies in the medical domain.

Finding the differences and similarities between two datasets is a common analytics task. With temporal event sequence data, this task is complex because of the many ways single events and event sequences can differ between the two datasets (or cohorts) of records: the structure of the event sequences (e.g., event order, co-occurring events, or event frequencies), the attributes of events and records (e.g., patient gender), or metrics about the timestamps themselves (e.g., event duration). In exploratory analyses, running statistical tests to cover all cases is time-consuming and determining which results are significant becomes cumbersome. Current analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. This paper presents a taxonomy of metrics for comparing cohorts of temporal event sequences, showing that the problem-space is bounded. We also present a visual analytics tool, CoCo (for "Cohort Comparison"), which implements balanced integration of automated statistics with an intelligent user interface to guide users to significant, distinguishing features between the cohorts. Lastly, we describe two early case studies: the first with a research team studying medical team performance in the emergency department and the second with pharmacy researchers.

OBJECTIVE: The primary objective was to evaluate time, number of interface actions, and accuracy on medication reconciliation tasks using a novel user interface (Twinlist, which lays out the medications in five columns based on similarity and uses animation to introduce the grouping - www.cs.umd.edu/hcil/sharp/twinlist) compared to a Control interface (where medications are presented side by side in two columns). A secondary objective was to assess participant agreement with statements regarding clarity and utility and to elicit comparisons. MATERIAL AND METHODS: A 1 × 2 within-subjects experimental design was used with interface (Twinlist or Control) as an independent variable; time, number of clicks, scrolls, and errors were used as dependent variables. Participants were practicing medical providers with experience performing medication reconciliation but no experience with Twinlist. They reconciled two cases in each interface (in a counterbalanced order), then provided feedback on the design of the interface. RESULTS: Twenty medical providers participated in the study for a total of 80 trials. The trials using Twinlist were statistically significantly faster (18%), with fewer clicks (40%) and scrolls (60%). Serious errors were noted 12 and 31 times in Twinlist and Control trials, respectively. DISCUSSION: Trials using Twinlist were faster and more accurate. Subjectively, participants rated Twinlist more favorably than Control. They valued the novel layout of the drugs, but indicated that the included animation would be valuable for novices, but not necessarily for advanced users. Additional feedback from participants provides guidance for further development and clinical implementations. CONCLUSIONS: Cognitive support of medication reconciliation through interface design can significantly improve performance and safety.

Abstract An important part of network analysis is understanding community structures like topological clusters and attribute‐based groups. Standard approaches for showing communities using colour, shape, rectangular bounding boxes, convex hulls or force‐directed layout algorithms remain valuable, however our Group‐in‐a‐Box meta‐layouts add a fresh strategy for presenting community membership, internal structure and inter‐cluster relationships. This paper extends the basic Group‐in‐a‐Box meta‐layout, which uses a Treemap substrate of rectangular regions whose size is proportional to community size. When there are numerous inter‐community relationships, the proposed extensions help users view them more clearly: (1) the Croissant–Doughnut meta‐layout applies empirically determined rules for box arrangement to improve space utilization while still showing inter‐community relationships, and (2) the Force‐Directed layout arranges community boxes based on their aggregate ties at the cost of additional space. Our free and open source reference implementation in NodeXL includes heuristics to choose what we have found to be the preferable Group‐in‐a‐Box meta‐layout to show networks with varying numbers or sizes of communities. Case study examples, a pilot comparative user preference study (nine participants), and a readability measure‐based evaluation of 309 Twitter networks demonstrate the utility of the proposed meta‐layouts.

Visualization has proven to be a useful tool for understanding network structures. Yet the dynamic nature of social media networks requires powerful visualization techniques that go beyond static network diagrams. To provide strong temporal network visualization tools, designers need to understand what tasks the users have to accomplish. This paper describes a taxonomy of temporal network visualization tasks. We identify the 1) entities, 2) properties, and 3) temporal features, which were extracted by surveying 53 existing temporal network visualization systems. By building and examining the task taxonomy, we report which tasks are well covered by existing systems and make suggestions for designing future visualization tools. The feedback from 12 network analysts helped refine the taxonomy.

Social media, particularly Twitter, provides an abundance of real-time data. To account for this volume, researchers often use automated analysis and visualization techniques to produce a high-level overview of a Twitter stream. Existing techniques for understanding Twitter data make use of hashtags or word-pairs and may ignore the complex trends in discussions over time. To remedy this, we present an application of statistical topic modeling and alignment (binned topic models) to group related tweets into automatically generated topics and TopicFlow, an interactive tool to visualize the evolution of these topics. The effectiveness of this visualization for reasoning about large data sets is demonstrated by a usability study with 18 participants.

Analyzing networks involves understanding the complex relationships between entities, as well as any attributes they may have. The widely used node-link diagrams excel at this task, but many are difficult to extract meaning from because of the inherent complexity of the relationships and limited screen space. To help address this problem we introduce a technique called motif simplification, in which common patterns of nodes and links are replaced with compact and meaningful glyphs. Well-designed glyphs have several benefits: they (1) require less screen space and layout effort, (2) are easier to understand in the context of the network, (3) can reveal otherwise hidden relationships, and (4) preserve as much underlying information as possible. We tackle three frequently occurring and high-payoff motifs: fans of nodes with a single neighbor, connectors that link a set of anchor nodes, and cliques of completely connected nodes. We contribute design guidelines for motif glyphs; example glyphs for the fan, connector, and clique motifs; algorithms for detecting these motifs; a free and open source reference implementation; and results from a controlled study of 36 participants that demonstrates the effectiveness of motif simplification.

In our burgeoning world of ubiquitous sensors and affordable data storage, records of timestamped events are being produced across nearly every domain of personal and professional computing. The resulting data surge has created an overarching need to search these records for meaningful patterns of events. This paper reports on a two-part user study, as well as a series of early tests and interviews with clinical researchers, that informed the development of two temporal query interfaces: a basic, menu-based interface and an advanced, graphic-based interface. While the scope of temporal query is very broad, this work focuses on two particularly complex and critical facets of temporal event sequences: intervals (events with both a start time and an end time), and the absence of an event. We describe how users encounter a common set of difficulties when specifying such queries, and propose solutions to help overcome them. Finally, we report on two case studies with epidemiologists at the US Army Pharmacovigilance Center, illustrating how both query interfaces were used to study patterns of drug use.

Vannevar Bush's 1945 book Science: The Endless Frontier, made a sharp distinction between basic (or pure) and applied research, urging strong government support for academic basic research and warning that “applied research invariably drives out pure”. He also suggested the “linear model” in which basic research leads to applied research, and then commercial development. These biased views are still widely held, so a fresh analysis is needed to repair the damage and to provide a guiding framework for scientific researchers across many disciplines. The High-Impact Research framework integrates current concepts that have been voiced by many people: 1) Science research projects that address basic and applied questions, seek theoretical and practical outcomes, and are inspired by curiosity-driven as well as mission-driven goals are likely to have the greatest payoffs. 2) These increased expectations may require teamwork from multidisciplinary participants and from those who are skilled with multiple research methods: randomized controlled trials, ethnographic case studies, automatic logging, retrospective analysis, etc. Teamwork can be difficult, but has a stronger possibility of producing breakthrough results. 3) Since complex problems are resistant to reductionist approaches and small laboratory controlled experiments, high-impact can be achieved by using new research methods that depend on interventions that are evaluated in large-scale systems. Such repeated interventions constitute case studies that can provide evidence to support or falsify hypotheses. Guidelines for promoting and reporting rigorous case studies will accelerate progress.

Visual overviews of tables of numerical and categorical data have been proposed for tables with a single value per cell. This article addresses the problem of exploring tables with columns that consist of cells that are distributions, for example, the distributions of movie ratings or trust ratings in recommender systems, age distributions in demographic data, usage distributions in logs of telephone calls, and so on. This article expands on heatmap approaches and proposes a novel way of displaying and interacting with distribution data. The usability study demonstrates the benefits of the heatmap interface in providing an overview of the data and facilitating the discovery of interesting clusters, patterns, outliers and relationships between columns.

To analyze data such as the US Federal Budget or characteristics of the student population of a University it is common to look for changes over time. This task can be made easier and more fruitful if the analysis is performed by grouping by attributes, such as by Agencies, Bureaus and Accounts for the Budget, or Ethnicity, Gender and Major in a University. We present TreeVersity2, a web based interactive data visualization tool that allows users to analyze change in datasets by creating dynamic hierarchies based on the data attributes. TreeVersity2 introduces a novel space filling visualization (StemView) to represent change in trees at multiple levels--not just at the leaf level. With this visualization users can explore absolute and relative changes, created and removed nodes, and each node's actual values, while maintaining the context of the tree. In addition, TreeVersity2 provides overviews of change over the entire time period, and a reporting tool that lists outliers in textual form, which helps users identify the major changes in the data without having to manually setup filters. We validated TreeVersity2 with 12 case studies with organizations as diverse as the National Cancer Institute, Federal Drug Administration, Department of Transportation, Office of the Bursar of the University of Maryland, or eBay. Our case studies demonstrated that TreeVersity2 is flexible enough to be used in different domains and provide useful insights for the data owners. A TreeVersity2 demo can be found at https://treeversity.cattlab.umd.edu.

Electronic Health Records (EHRs) have emerged as a cost-effective data source for conducting medical research. The difficulty in using EHRs for research purposes, however, is that both patient selection and record analysis must be conducted across very large, and typically very noisy datasets. Our previous work introduced EventFlow, a visualization tool that transforms an entire dataset of temporal event records into an aggregated display, allowing researchers to analyze population-level patterns and trends. As datasets become larger and more varied, however, it becomes increasingly difficult to provide a succinct, summarizing display. This paper presents a series of user-driven data simplifications that allow researchers to pare event records down to their core elements. Furthermore, we present a novel metric for measuring visual complexity, and a language for codifying disjoint strategies into an overarching simplification framework. These simplifications were used by real-world researchers to gain new and valuable insights from initially overwhelming datasets.

Summary form only given. The remarkable adoption of information visualization has triggered worldwide application from researchers, companies, governments, and news media. The public interest in visually rich infographics has raised questions of how best to present insights and what interactive capabilities enable engaging exploration, while maintaining comprehensibility. Government professionals find that compelling visual presentations inform policy making. At the same time researchers and corporate decision makers have increased expectations of how visual analytics can support important discoveries and business decisions. Our research community is racing to deal with complex data, rich questions, and large-scale data streams. This talk will present some success stories and suggest promising research directions.

Gavriel Salvendy (Ed.). Handbook of Human Factors and Ergonomics (4th ed.). Wiley and Sons, 2012. 1,732 pages. ISBN: 978-0-470-52838-9. Reviewed by Ben Shneiderman, Department of Computer Science, ...

Specifying event sequence queries is challenging even for skilled computer professionals familiar with SQL. Most graphical user interfaces for database search use an exact match approach, which is often effective, but near misses may also be of interest. We describe a new similarity search interface, in which users specify a query by simply placing events on a blank timeline and retrieve a similarity-ranked list of results. Behind this user interface is a new similarity measure for event sequences which the users can customize by four decision criteria, enabling them to adjust the impact of missing, extra, or swapped events or the impact of time shifts. We describe a use case with Electronic Health Records based on our ongoing collaboration with hospital physicians. A controlled experiment with 18 participants compared exact match and similarity search interfaces. We report on the advantages and disadvantages of each interface and suggest a hybrid interface combining the best of both.

Keeping up with rapidly growing research fields, especially when there are multiple interdisciplinary sources, requires substantial effort for researchers, program managers, or venture capital investors. Current theories and tools are directed at finding a paper or website, not gaining an understanding of the key papers, authors, controversies, and hypotheses. This report presents an effort to integrate statistics, text analytics, and visualization in a multiple coordinated window environment that supports exploration. Our prototype system, Action Science Explorer (ASE), provides an environment for demonstrating principles of coordination and conducting iterative usability tests of them with interested and knowledgeable users. We developed an understanding of the value of reference management, statistics, citation text extraction, natural language summarization for single and multiple documents, filters to interactively select key papers, and network visualization to see citation patterns and identify clusters. A three‐phase usability study guided our revisions to ASE and led us to improve the testing methods.

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'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.

While journalists often portray discovery as the thrilling insight of a brilliant individual, many discoveries require years of work by competing and collaborating teams. Often large amounts of foundational work are necessary and dialogs among participants help clarify goals. The Social Discovery Framework suggests that (1) there are important processes in building capacity and then seeking solutions and (2) those that initiate requests are often as important as those who seek solutions. The implications of the Social Discovery Framework are that improved social tools to build capacity, initiate requests, and support dialog would accelerate the discovery process as much as the more visible tools for individuals seeking solutions.

Event sequence analysis is an important task in many domains: medical researchers may study the patterns of transfers within the hospital for quality control; transportation experts may study accident response logs to identify best practices. In many cases they deal with thousands of records. While previous research has focused on searching and browsing, overview tasks are often overlooked. We introduce a novel interactive visual overview of event sequences called \emph{LifeFlow}. LifeFlow is scalable, can summarize all possible sequences, and represents the temporal spacing of the events within sequences. Two case studies with healthcare and transportation domain experts are presented to illustrate the usefulness of LifeFlow. A user study with ten participants confirmed that after 15 minutes of training novice users were able to rapidly answer questions about the prevalence and temporal characteristics of sequences, find anomalies, and gain significant insight from the data.

Action Science Explorer (ASE) is a tool designed to support users in rapidly generating readily consumable summaries of academic literature. It uses citation network visualization, ranking and filtering papers by network statistics, and automatic clustering and summarization techniques. We describe how early formative evaluations of ASE led to a mature system evaluation, consisting of an in-depth empirical evaluation with four domain experts. The evaluation tasks were of two types: predefined tasks to test system performance in common scenarios, and user-defined tasks to test the system's usefulness for custom exploration goals. The primary contribution of this paper is a validation of the ASE design and recommendations to provide: easy-to-understand metrics for ranking and filtering documents, user control over which document sets to explore, and overviews of the document set in coordinated views along with details-on-demand of specific papers. We contribute a taxonomy of features for literature search and exploration tools and describe exploration goals identified by our participants.

Though biomedical research often draws on knowledge from a wide variety of fields, few visualization methods for biomedical data incorporate meaningful cross-database exploration. A new approach is offered for visualizing and exploring a query-based subset of multiple heterogeneous biomedical databases. Databases are modeled as an entity-relation graph containing nodes (database records) and links (relationships between records). Users specify a keyword search string to retrieve an initial set of nodes, and then explore intra- and interdatabase links. Results are visualized with user-defined semantic substrates to take advantage of the rich set of attributes usually present in biomedical data. Comments from domain experts indicate that this visualization method is potentially advantageous for biomedical knowledge exploration.

Traditional network analysis tools support analysts in studying a single network. ManyNets offers these analysts a powerful new approach that enables them to work on multiple networks simultaneously. Several thousand networks can be presented as rows in a tabular visualization, and then inspected, sorted and filtered according to their attributes. The networks to be displayed can be obtained by subdivision of larger networks. Examples of meaningful subdivisions used by analysts include ego networks, community extraction, and time-based slices. Cell visualizations and interactive column overviews allow analysts to assess the distribution of attributes within particular sets of networks. Details, such as traditional node-link diagrams, are available on demand. We describe a case study analyzing a social network geared towards film recommendations by means of decomposition. A small usability study provides feedback on the use of the interface on a set of tasks issued from the case study.

This panel will discuss group processes that promote social creativity in science, engineering, arts, and humanities. We will offer positive and negative examples of social creativity projects, while suggesting research directions for dramatically increased social participation. The goal is to develop strategies that would expand resources and opportunities for research and education in social creativity. This requires our community to develop a unified position, then reach out to national science funding agencies, while building the case for the importance of this topic beyond our own community. How can social creativity, collaborative discovery, distributed innovation, and collective intelligence be framed as an international priority to cope with the problems of the 21st century and how can we identify a clear set of research challenges?

Abstract Gaining a rapid overview of an emerging scientific topic, sometimes called research fronts, is an increasingly common task due to the growing amount of interdisciplinary collaboration. Visual overviews that show temporal patterns of paper publication and citation links among papers can help researchers and analysts to see the rate of growth of topics, identify key papers, and understand influences across subdisciplines. This article applies a novel network‐visualization tool based on meaningful layouts of nodes to present research fronts and show citation links that indicate influences across research fronts. To demonstrate the value of two‐dimensional layouts with multiple regions and user control of link visibility, we conducted a design‐oriented, preliminary case study with 6 domain experts over a 4‐month period. The main benefits were being able (a) to easily identify key papers and see the increasing number of papers within a research front, and (b) to quickly see the strength and direction of influence across related research fronts.

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.

Although both statistical methods and visualizations have been used by network analysts, exploratory data analysis remains a challenge. We propose that a tight integration of these technologies in an interactive exploratory tool could dramatically speed insight development. To test the power of this integrated approach, we created a novel social network analysis tool, SocialAction, and conducted four long-term case studies with domain experts, each working on unique data sets with unique problems. The structured replicated case studies show that the integrated approach in SocialAction led to significant discoveries by a political analyst, a bibliometrician, a healthcare consultant, and a counter-terrorism researcher. Our contributions demonstrate that the tight integration of statistics and visualizations improves exploratory data analysis, and that our evaluation methodology for long-term case studies captures the research strategies of data analysts.

Electronic Health Records (EHRs) and other temporal databases contain hidden patterns that reveal important cause-and-effect phenomena. Finding these patterns is a challenge when using traditional query languages and tabular displays. We present an interactive visual tool that complements query formulation by providing operations to align, rank and filter the results, and to visualize estimates of the intervals of validity of the data. Display of patient histories aligned on sentinel events (such as a first heart attack) enables users to spot precursor, co-occurring, and aftereffect events. A controlled study demonstrates the benefits of providing alignment (with a 61% speed improvement for complex tasks). A qualitative study and interviews with medical professionals demonstrates that the interface can be learned quickly and seems to address their needs.

During exploratory data analysis, visualizations are often useful for making sense of complex data sets. However, as data sets increase in size and complexity, static information visualizations decrease in comprehensibility. Interactive techniques can yield valuable discoveries, but current data analysis tools typically support only opportunistic exploration that may be inefficient and incomplete.

Database searches are usually performed with query languages and form fill in templates, with results displayed in tabular lists. However, excitement is building around dynamic queries sliders and other graphical selectors for query specification, with results displayed by information visualization techniques. These filtering techniques have proven to be effective for many tasks in which visual presentations enable discovery of relationships, clusters, outliers, gaps, and other patterns. Scaling visual presentations from millions to billions of records will require collaborative research efforts in information visualization and database management to enable rapid aggregation, meaningful coordinated windows, and effective summary graphics. This paper describes current and proposed solutions (atomic, aggregated, and density plots) that facilitate sense-making for interactive visual exploration of billion record data sets.

We describe the development and evaluation of a tool, iSonic, to assist users with visual impairment in exploring georeferenced data using coordinated maps and tables, augmented with nontextual sounds and speech output. Our in-depth case studies with 7 blind users during 42 hours of data collection, showed that iSonic enabled them to find facts and discover trends in georeferenced data, even in unfamiliar geographical contexts, without special devices. Our design was guided by an Action-by-Design-Component (ADC) framework, which was also applied to scatterplots to demonstrate its generalizability. Video and download is available at www.cs.umd.edu/hcil/iSonic/.

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'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' confidence and satisfaction.

No abstract available.

This paper addresses the problem of making text mining results more comprehensible to humanities scholars, journalists, intelligence analysts, and other researchers, in order to support the analysis of text collections. Our system, FeatureLens1, visualizes a text collection at several levels of granularity and enables users to explore interesting text patterns. The current implementation focuses on frequent itemsets of n-grams, as they capture the repetition of exact or similar expressions in the collection. Users can find meaningful co-occurrences of text patterns by visualizing them within and across documents in the collection. This also permits users to identify the temporal evolution of usage such as increasing, decreasing or sudden appearance of text patterns. The interface could be used to explore other text features as well. Initial studies suggest that FeatureLens helped a literary scholar and 8 users generate new hypotheses and interesting insights using 2 text collections.

Visualizing network data, from tree structures to arbitrarily connected graphs, is a difficult problem in information visualization. A large part of the problem is that in network data, users not only have to visualize the attributes specific to each data item, but also the links specifying how those items are connected to each other. Past approaches to resolving these difficulties focus on zooming, clustering, filtering and applying various methods of laying out nodes and edges. Such approaches, however, focus only on optimizing a network visualization in a single view, limiting the amount of information that can be shown and explored in parallel. Moreover, past approaches do not allow users to cross reference different subsets or aspects of large, complex networks. In this paper, we propose an approach to these limitations using multiple coordinated views of a given network. To illustrate our approach, we implement a tool called DualNet and evaluate the tool with a case study using an email communication network. We show how using multiple coordinated views improves navigation and provides insight into large networks with multiple node and link properties and types.

When hard-to-use computers cause users to become frustrated, it can affect workplace productivity, user mood and interactions with other co-workers. Previous research has examined the frustration that students and their families face in using computers. To learn more about the causes and measure the severity of user frustration with computers in the workplace, we collected modified time diaries from 50 workplace users, who spent an average of 5.1 hours on the computer. In this exploratory research, users reported wasting on average, 42 – 43% of their time on the computer due to frustrating experiences. The largest number of frustrating experiences occurred while using word processors, email and web browsers. The causes of the frustrating experiences, the time lost due to the frustrating experiences, and the effects of the frustrating experiences on the mood of the users are discussed in this paper. Implications for designers, managers, users, information technology staff and policymakers are discussed.

Creativity support tools is a research topic with high risk but potentially very high payoff. The goal is to develop improved software and user interfaces that empower users to be not only more productive but also more innovative. Potential users include software and other engineers, diverse scientists, product and graphic designers, architects, educators, students, and many others. Enhanced interfaces could enable more effective searching of intellectual resources, improved collaboration among teams, and more rapid discovery processes. These advanced interfaces should also provide potent support in hypothesis formation, speedier evaluation of alternatives, improved understanding through visualization, and better dissemination of results. For creative endeavors that require composition of novel artifacts (e.g., computer programs, scientific papers, engineering diagrams, symphonies, artwork), enhanced interfaces could facilitate exploration of alternatives, prevent unproductive choices, and enable easy backtracking. This U.S. National Science Foundation sponsored workshop brought together 25 research leaders and graduate students to share experiences, identify opportunities, and formulate research challenges. Two key outcomes emerged: (a) encouragement to evaluate creativity support tools through multidimensional in-depth longitudinal case studies and (b) formulation of 12 principles for design of creativity support tools.

User frustration with information and computing technology is a pervasive and persistent problem. When computers crash, network congestion causes delays, and poor user interfaces trigger confusion there are dramatic consequences for individuals, organizations, and society. These frustrations, not only cause personal dissatisfaction and loss of self-efficacy, but may disrupt workplaces, slow learning, and reduce participation in local and national communities. Our exploratory study of 107 student computer users and 50 workplace computer users shows high levels of frustration and loss of 1/3–1/2 of time spent. This paper reports on the incident and individual factors that cause of frustration, and how they raise frustration severity. It examines the frustration impacts on the daily interactions of the users. The time lost and time to fix problem, and importance of task, strongly correlate with frustration levels for both student and workplace users. Differences between students and workplace users are discussed in the paper, as are implications for researchers.

Abstract Due to e‐mail's ubiquitous nature, millions of users are intimate with the technology; however, most users are only familiar with managing their own e‐mail, which is an inherently different task from exploring an e‐mail archive. Historians and social scientists believe that e‐mail archives are important artifacts for understanding the individuals and communities they represent. To understand the conversations evidenced in an archive, context is needed. In this article, 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 e‐mail headers by identifying relationships and interpreting their attributes. With these visualization techniques, e‐mail archive explorers can uncover insights that may have been otherwise hidden in the archive. We apply our methods to an individual's 15‐year e‐mail archive, which consists of about 45,000 messages and over 4,000 relationships.

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.

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.

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.

iSonic is an interactive sonification tool for vision impaired users to explore geo-referenced statistical data, such as population or crime rates by geographical regions. Users use a keyboard or a smooth surface touchpad to interact with coordinated map and table views of the data. The integrated use of musical sounds and speech allows users to grasp the overall data trends and to explore the data to get more details. Scenarios of use are described.

The old computing was about what computers could do; the new computing is about what people can do.To accelerate the shift from the old to the new computing designers need to:

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 visually appealing and cognitively effective 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.

This paper describes a pixel‐based technique that enables highly interactive Web choropleth maps for georeferenced data publishing and visual exploration. Instead of delivering geographic knowledge to the client in polygon‐based vector formats, we encode geographic object IDs and shape information into highly compact pixel images (decoding maps). This allows the combination of raster and vector characteristics while avoiding the problems in the currently existing pixel‐based (raster‐image‐based) or vector‐based techniques. Differing from traditional pixel‐based techniques that are static and allow very little user interaction, our pixel‐based technique allows varieties of sub‐second (less than 1 s) interface controls such as dynamic query, dynamic classification, geographic object data identification, user‐setting adjusting, as well as turning on/off layers, panning and zooming, with no or minimum server support. Compared with Web GIS techniques that use vector geographic data, our technique avoids transferring over the network large vector geographic data. It also avoids the non‐trivial client‐side computation to interpret the vector data and render the maps. Our technique features a short initial download time, near‐constant performance scalability for larger numbers of geographic objects, and download‐map‐segment‐only‐when‐necessary which potentially reduces the overall data transfer over the network. As a result, it accommodates general public users with slow modem network connections and low‐end machines, as well as users with fast T‐1 connections and fast machines. The client‐side (browser) is implemented as lightweight Java applets. YMap, an easy‐to‐use, user‐task‐oriented highly interactive mapping tool for visual georeferenced data exploration is implemented using this technique. The performance comparison of YMap to some other vector‐based Web GIS demonstrates the feasibility and benefits of this technique.

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.

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't with a preliminary set of principles that might have wide applicability.

The central thesis of Leonardo's Laptop (MIT Press, 2002) is that designers who are sensitive to human needs are more likely to make the breakthroughs that yield new technologies successes. Therefore, a theory of mobile devices would focus on compact devices that support human relationships, provide salient information, and enable creative expression. The foundations are not only the megahertz of connectivity, but also the usability and universality of interfaces. Demonstrations include digital photo applications, personal info, healthcare, and e-commerce.

MOTIVATION: The most commonly utilized microarrays for mRNA profiling (Affymetrix) include 'probe sets' of a series of perfect match and mismatch probes (typically 22 oligonucleotides per probe set). There are an increasing number of reported 'probe set algorithms' that differ in their interpretation of a probe set to derive a single normalized 'signal' representative of expression of each mRNA. These algorithms are known to differ in accuracy and sensitivity, and optimization has been done using a small set of standardized control microarray data. We hypothesized that different mRNA profiling projects have varying sources and degrees of confounding noise, and that these should alter the choice of a specific probe set algorithm. Also, we hypothesized that use of the Microarray Suite (MAS) 5.0 probe set detection p-value as a weighting function would improve the performance of all probe set algorithms. RESULTS: We built an interactive visual analysis software tool (HCE2W) to test and define parameters in Affymetrix analyses that optimize the ratio of signal (desired biological variable) versus noise (confounding uncontrolled variables). Five probe set algorithms were studied with and without statistical weighting of probe sets using the MAS 5.0 probe set detection p-values. The signal-to-noise ratio optimization method was tested in two large novel microarray datasets with different levels of confounding noise, a 105 sample U133A human muscle biopsy dataset (11 groups: mutation-defined, extensive noise), and a 40 sample U74A inbred mouse lung dataset (8 groups: little noise). Performance was measured by the ability of the specific probe set algorithm, with and without detection p-value weighting, to cluster samples into the appropriate biological groups (unsupervised agglomerative clustering with F-measure values). Of the total random sampling analyses, 50% showed a highly statistically significant difference between probe set algorithms by ANOVA [F(4,10) > 14, p < 0.0001], with weighting by MAS 5.0 detection p-value showing significance in the mouse data by ANOVA [F(1,10) > 9, p < 0.013] and paired t-test [t(9) = -3.675, p = 0.005]. Probe set detection p-value weighting had the greatest positive effect on performance of dChip difference model, ProbeProfiler and RMA algorithms. Importantly, probe set algorithms did indeed perform differently depending on the specific project, most probably due to the degree of confounding noise. Our data indicate that significantly improved data analysis of mRNA profile projects can be achieved by optimizing the choice of probe set algorithm with the noise levels intrinsic to a project, with dChip difference model with MAS 5.0 detection p-value continuous weighting showing the best overall performance in both projects. Furthermore, both existing and newly developed probe set algorithms should incorporate a detection p-value weighting to improve performance. AVAILABILITY: The Hierarchical Clustering Explorer 2.0 is available at http://www.cs.umd.edu/hcil/hce/ Murine arrays (40 samples) are publicly available at the PEPR resource (http://microarray.cnmcresearch.org/pgadatatable.asp http://pepr.cnmcresearch.org Chen et al., 2004).

BACKGROUND: The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data in the midst of discovery increase the challenge of integrating experimental results with information resources. The use of Gene Ontology enables researchers to summarize results of quantitative analyses in this framework, but the limitations of typical browser presentation restrict data access. RESULTS: Here we describe extensions to the treemap design to visualize and query genome data. Treemaps are a space-filling visualization technique for hierarchical structures that show attributes of leaf nodes by size and color-coding. Treemaps enable users to rapidly compare sizes of nodes and sub-trees, and we use Gene Ontology categories, levels of RNA, and other quantitative attributes of DNA microarray experiments as examples. Our implementation of treemaps, Treemap 4.0, allows user-defined filtering to focus on the data of greatest interest, and these queried files can be exported for secondary analyses. Links to model system web pages from Treemap 4.0 enable users access to details about specific genes without leaving the query platform. CONCLUSIONS: Treemaps allow users to view and query the data from an experiment on a single computer monitor screen. Treemap 4.0 can be used to visualize various genome data, and is particularly useful for revealing patterns and details within complex data sets.

Although computers are beneficial to individuals and society, frequently users encounter frustrating experiences when using computers. This study represents an attempt to measure, in 111 participants, the frequency, the cause, and the level of severity of frustrating experiences. The data show that frustrating experiences happen on a frequent basis. The applications in which the frustrating experiences happened most frequently were Web browsing, e-mail, and word processing. The most-cited causes of frustrating experiences were error messages, dropped network connections, long download times, and hard-to-find features. The time lost due to frustrating experiences ranged from 47% to 53% of time spent on a computer, depending on the location and study method. After extreme cases were discarded, the time lost was still above 38%. These disturbing results should be a basis for future study.

This paper describes a novel instantiation of a digital photo library in a public access system. It demonstrates how designers can utilize characteristics of a target user community (social constraints, trust, and a lack of anonymity) to provide capabilities that would be impractical in other types of public access systems. It also presents a compact set of design principles and guidelines for ensuring the immediate usability of public access information systems. These principles and guidelines were derived from our experience developing PhotoFinder Kiosk, a community photo library. Attendees of a major HCI conference (CHI 2001 Conference on Human Factors in Computing Systems) successfully used the tool to browse and annotate collections of photographs spanning 20 years of HCI-related conferences, producing a richly annotated photo history of the field of human-computer interaction. Observations and log data were used to evaluate the tool and develop the guidelines. They provide specific guidance for practitioners, as well as a useful framework for additional research in public access interfaces.

Abstract More than 100 U.S. governmental agencies offer links through FedStats, a centralized Web site that facilitates access to statistical tables, reports, and agencies. This and similar large collections need appropriate interfaces to guide the general public to easily and successfully find information they seek. This paper summarizes the results of 3 empirical studies of alternate organization concepts of the FedStats Topics Web page. Each study had 15 participants. The evolution from 645 alphabetically organized links, to 549 categorically organized links, to 215 categorically organized links tied to portal pages produced a steady rise in successful task completion from 15.6 to 24.4 to 42.2%. User satisfaction also increased. We make recommendations based on these data and our observations of users.

Data sets involving linear ordered sequences are a recurring theme in bioinformatics. Dynamic query tools that support exploration of these data sets can be useful for identifying patterns of interest. This paper describes the use of one such tool - timesearcher - to interactively explore linear sequence data sets taken from two bioinformatics problems. Microarray time course data sets involve expression levels for large numbers of genes over multiple time points. Timesearcher can be used to interactively search these data sets for genes with expression profiles of interest. The occurrence frequencies of short sequences of DNA in aligned exons can be used to identify sequences that play a role in the pre-mRNA splicing. Timesearcher can be used to search these data sets for candidate splicing signals.

Data analysis and visualization is strongly influenced by noise and noise filters. There are multiple sources of "noise" in microarray data analysis, but signal/noise ratios are rarely optimized, or even considered. Here, we report a noise analysis of a novel 13 million oligonucleotide dataset - 25 human U133A (/spl sim/500,000 features) profiles of patient muscle biopsies. We use our recently described interactive visualization tool, the hierarchical clustering explorer (HCE) to systemically address the effect of different noise filters on resolution of arrays into "correct" biological groups (unsupervised clustering into three patient groups of known diagnosis). We varied probe set interpretation methods (MAS 5.0, RMA), "present call" filters, and clustering linkage methods, and investigated the results in HCE. HCE's interactive features enabled us to quickly see the impact of these three variables. Dendrogram displays showed the clustering results systematically, and color mosaic displays provided a visual support for the results. We show that each of these three variables has a strong effect on unsupervised clustering. For this dataset, the strength of the biological variable was maximized, and noise minimized, using MAS 5.0, 10% present call filter, and average group linkage. We propose a general method of using interactive tools to identify the optimal signal/noise balance or the optimal combination of these three variables to maximize the effect of the desired biological variable on data interpretation.

Georges Grinstein Questions often asked when presenting some new model, new theory, new research or new visualization include: How useful or how usable is it? and Have you performed any tests? Visualization is an interface technology and as such includes not just software algorithms and techniques, but computer human interaction issues as well. This makes it draw from both areas, one appearing more focused on utility and the other on usability. One key step in the development of a new theory is the attempt to first solve a problem. That problem or question does not include a section; in some domain it may not even contain a utility one from most people's perspectives. We discuss both sides of the issue to clarify the role of each in the development of new visualization technologies. Position Statement Alfred Kobsa In the HCI literature one can find studies which conclude that ease of use is more important than usefulness (Hubona & Blanton 1996), that the opposite holds true (Liao and Landry 2000), and that ease of use is more important for females while the usefulness is more important for males (Yuen and Ma 2002). In this panel contribution, we will present several user studies with information visualization systems, ranging from lab experiments with closed questions to longitudinal adoption studies with administrative data analysts (Gonzales & Kobsa, 2003; Kobsa 2001, 2003; Mark et al. 2003). -------------------------------------------a e-mail: [email protected] e-mail: [email protected] e-mail: [email protected] e-mail [email protected] e-mail [email protected] Consistent with general HCI research, the results show that both factors are important in certain situations, but do not indicate a clear superiority of one factor over the other. Position Statement Catherine Plaisant Is an airplane a better vehicle than a Jaguar, a mountain bicycle or a kid scooter? It all depends of where you need to go, what your goal for the travel is, how old you are, what terrain you will encounter on the way, how long you can spend learning, and many other parameters. All those vehicles are fairly usable but they all require training except for adults using the scooter, and their utility varies enormously as a function of the task and the user. The average car drivers benefit from years of human factor engineering and a large amount of standardization, allowing them to switch from a pickup truck to a convertible in a snap. Similarly, the success of a visualization tool depends on how well it fits the needs of the users it attempts to serve, and the tasks they want to accomplish. If utility may come first for an expert tool (e.g. for discovery tasks requires days of data examination and manipulation), has to come first in public access information systems that requires immediate usability (e.g. interactive displays of census statistics) otherwise users will walk away frustrated. Usability design principles imply that designers and evaluators understand the needs of users to decide which one of the two utility or comes first, and to set levels of required utility and usability. Utility and are both attainable goals that make each other stronger. Like others, we at the University of Maryland have been developing visualization techniques and have struggled over the years to find the best way to evaluate their benefits. Many evaluations have been controlled experiments and we have found that the most useful evaluations were multi-faceted, including qualitative and quantitative measurements or performance, preference and learnability, and I will be show examples from our research. Often we also find that the observations gathered during the experiment can be as informative as the collected measurements. More recently we have been promoting the development of benchmark datasets and tasks that will allow better comparisons between tools and techniques. We have been involved in the 1st InfoVis contest, which calls for the submission of case studies of pairwise comparison of trees. Three pairs of datasets were provided: philogenies, classifications and file system usage data, 605 Proceedings of the 14th IEEE Visualization Conference (VIS’03) 0-7695-2030-8/03 $ 17.00 © 2003 IEEE and open ended tasks described. Accepted submissions will seed an online repository that can be enhanced over time with additional datasets, tasks, case studies and controlled experiment results. I will report on the results of the contest and reflect on how evaluation repository and benchmark datasets might help us understand how to judge the and utility of our tools. The contest is at: http://www.cs.umd.edu/hcil/iv03contest/ Position Statement Ben Shneiderman The answer to the question of or utility first depends on your definition of usability. For me, is more than the color of widgets and placement of text. Usability is about understanding, stating, and serving user needs. Since these needs are the requirements that shape the tool, they determine the utility. The design of excellent tools depends upon understanding how they will be used; therefore is a pre-requisite for successful utility. Position Statement John T. Stasko If the question is, Which comes first, utility or usability? my answer is yes. Both notions are vitally important in the development of information visualization techniques and systems, and they are just two sides of the same coin. When the field of information visualization formed and first grew, the computer graphics and visualization aspects dominated. More recently, an increasing emphasis on the HCI aspects of the field has emerged as we strive to better understand how people can truly benefit from our ideas. When an information visualization technique is implemented in a system, the component is crucial. Poor interface design can hamper adoption and cloud the utility benefits that may be possible. In information visualization, typically does not equate with the common notion of a system being easy to learn. Information visualization systems are complex and they often will be used extensively for long periods of time. Consequently, making a system efficient and natural to use, making functions and operations visible, and simply paying attention to the user interface are key components. This is especially true in systems where interaction and multiple views are essential. For any information visualization technique to be adopted beyond the initial idea generation, there must be some utility or value in that technique. Our field is not about making pretty pictures. It is about helping people with the complex tasks involved in data analysis and understanding. We need to do a better job of articulating the cognitive tasks that occur in data analysis (location, correlation, emphasis, association, etc.) and articulating how information visualization techniques and systems can help with these tasks. Ultimately, a kind of natural selection will occur: systems with utility and value will be adopted and used, while others will quietly fade away.

The tutorial begins with a model of creative processes and refines it into design principles. Participants will learn of eight ways to improve software that supports human creative processes:

An analysis of the home pages of all fifty US states reveals great variety in key design features that influence efficacy. Some states had excessively large byte counts that would slow users connected by commonly-used 56 K modems. Many web sites had low numbers of or poorly organized links that would make it hard for citizens to find what they were interested in. Features such as search boxes, privacy policies, online help, or contact information need to be added by several states. Our analysis concludes with ten recommendations and finds many further opportunities for individual states to improve their Websites. However still greater benefits will come through collaboration among the states that would lead to consistency, appropriate tagging, and common tools.

An experiment is reported that compared expandable indexes providing full menu context with sequential menus providing only partial context. Menu depth was varied using hierarchies of two, three and four levels deep in an asymmetric structure of 457 root level items. Menus were presented on the World Wide Web within a browser. Participants searched for specific targets. Results suggest that reducing the depth of hierarchies improves performance in terms of speed and search efficiency. Surprisingly, expandable indexes resulted in poorer performance with deeper hierarchies than did sequential menus.

Treemaps, a space-filling method for visualizing large hierarchical data sets, are receiving increasing attention. Several algorithms have been previously proposed to create more useful displays by controlling the aspect ratios of the rectangles that make up a treemap. While these algorithms do improve visibility of small items in a single layout, they introduce instability over time in the display of dynamically changing data, fail to preserve order of the underlying data, and create layouts that are difficult to visually search. In addition, continuous treemap algorithms are not suitable for displaying fixed-sized objects within them, such as images.This paper introduces a new "strip" treemap algorithm which addresses these shortcomings, and analyzes other "pivot" algorithms we recently developed showing the trade-offs between them. These ordered treemap algorithms ensure that items near each other in the given order will be near each other in the treemap layout. Using experimental evidence from Monte Carlo trials and from actual stock market data, we show that, compared to other layout algorithms, ordered treemaps are more stable, while maintaining relatively favorable aspect ratios of the constituent rectangles. A user study with 20 participants clarifies the human performance benefits of the new algorithms. Finally, we present quantum treemap algorithms, which modify the layout of the continuous treemap algorithms to generate rectangles that are integral multiples of an input object size. The quantum treemap algorithm has been applied to PhotoMesa, an application that supports browsing of large numbers of images.

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.

The desire to make computing available to broader populations has historically been a motivation for research and innovation that led to new breakthroughs in usability. Menus, graphical user interfaces and the World Wide Web are examples of innovative technological solutions that have arisen out of the challenge of bringing larger and more diverse groups of users into the world of computing. Universal usability is the latest such challenge: In order to build systems that are universally usable, designers must account for technology variety, user diversity and gaps in user knowledge. These issues are particularly challenging and important in the context of increasing the usability of the World Wide Web. To raise awareness, web designers are urged to provide universal usability statements that offer users information about the usability of their sites. These statements can inform users and thereby reduce frustration and confusion. Further steps toward universal usability might be achieved through research aimed at developing tools that would encourage or promote usability. The paper closes with five proposals for future research.

HTTP server log files provide Web site operators with substantial detail regarding the visitors to their sites. Interest in interpreting this data has spawned an active market for software packages that summarize and analyze this data, providing histograms, pie graphs, and other charts summarizing usage patterns. Although useful, these summaries obscure useful information and restrict users to passive interpretation of static displays. Interactive visualizations can be used to provide users with greater abilities to interpret and explore Web log data. By combining two-dimensional displays of thousands of individual access requests, color, and size coding for additional attributes, and facilities for zooming and filtering, these visualizations provide capabilities for examining data that exceed those of traditional Web log analysis tools. We introduce a series of interactive visualizations that can be used to explore server data across various dimensions. Possible uses of these visualizations are discussed, and difficulties of data collection, presentation, and interpretation are explored.

Voice controlled web browsers allow users to navigate by speaking the text of a link or an associated number instead of clicking with a mouse. One such browser is Conversa, by Conversational Computing. This within subjects study with 18 subjects compared voice browsing with traditional mouse-based browsing. It attempted to identify which of three common hypertext forms (linear slide show, grid/tiled map, and hierarchical menu) are well suited to voice navigation, and whether voice navigation is helped by numbering links. The study shows that voice control adds approximately 50% to the performance time for certain types of tasks. Subjective satisfaction measures indicate that for voice browsing, textual links are preferable to numbered links.

Multiple coordinated visualizations enable users to rapidly explore complex information. However, users often need unforeseen combinations of coordinated visualizations that are appropriate for their data. Snap-Together Visualization enables data users to rapidly and dynamically mix and match visualizations and coordinations to construct custom exploration interfaces without programming. Snap's conceptual model is based on the relational database model. Users load relations into visualizations then coordinate them based on the relational joins between them. Users can create different types of coordinations such as: brushing, drill down, overview and detail view, and synchronized scrolling. Visualization developers can make their independent visualizations snap-able with a simple API.

Annotating photographs is such a time-consuming, tedious and error-prone data entry task that it discourages most owners of personal photo libraries. By allowing the user to drag labels, such as personal names, from a scrolling list and drop them onto a photo, we believe we can make the task faster, easier and more appealing. Since the names are entered in a database, searching for all photos of a friend or family member is dramatically simplified. We describe the user interface design and the database schema to support direct annotation, as implemented in our PhotoFinder prototype.

Networked and local data exploration systems that use command languages, menus, or form fill-in interfaces rarely give users an indication of the distribution of data. This often leads users to waste time, posing queries that have zero-hit or mega-hit results. Query previews are a novel visual approach for browsing databases. Query previews supply users with data distribution information for selected attributes of the database, and give continuous feedback about the size of the result set as the query is being formed. Subsequent refinements might be necessary to narrow the search. As there is a risk that query previews are an additional step, leading to a more complex and slow search process, a within-subjects empirical study was ran with 12 subjects who used interfaces with and without query previews and with minimized network delays. Even with 12 subjects and minimized network delays statistically significant differences were found, showing that query previews could speed up performance 1.6 to 2.1 times and lead to higher user satisfaction.

To date, experimental comparisons of menu layouts have concentrated on variants of hierarchical structures of sequentially presented menus. Simultaneous menus-layouts that present multiple active menus on a screen at the same time-are an alternative arrangement that may be useful in many Web design situations. This article describes an experiment involving a between-subject comparison of simultaneous menus and their traditional sequential counterparts. A total of 20 experienced Web users used either simultaneous or sequential menus in a standard Web browser to answer questions based on U.S. Census data. Our results suggest that appropriate use of simultaneous menus can lead to improved task performance speeds without harming subjective satisfaction measures. For novice users performing simple tasks, the simplicity of sequential menus appears to be helpful, but experienced users performing complex tasks may benefit from simultaneous menus. Design improvements can amplify the benefits of simultaneous menu layouts.

To aid designers of digital library interfaces, we present a framework for the design of information representations in terms of previews and overviews. Previews and overviews are graphic or textual representations of information abstracted from primary information objects. Previews act as surrogates for one or a few objects and overviews represent collections of objects. A design framework is elaborated in terms of the following three dimensions: (1) what information objects are available to users, (2) how information objects are related and displayed, and (3) how users can manipulate information objects. When utilized properly, previews and overviews allow users to rapidly discriminate objects of interest from those not of interest, and to more fully understand the scope and nature of digital libraries. This article presents a definition of previews and overviews in context, provides design guidelines, and describes four example applications.

A challenge for human-computer interaction researchers and user interf ace designers is to construct information technologies that support creativity. This ambitious goal can be attained by building on an adequate understanding of creative processes. This article offers a four-phase framework for creativity that might assist designers in providing effective tools for users: (1)Collect: learn from provious works stored in libraries, the Web, etc.; (2)Relate: consult with peers and mentors at early, middle, and late stages, (3)Create: explore, compose, evaluate possible solutions; and (4)Donate: disseminate the results and contribute to the libraries. Within this integrated framework, this article proposes eight activities that require human-computer interaction research and advanced user interface design. A scenario about an architect illustrates the process of creative work within such an environment.

A challenge for human-computer interaction researchers and user interface designers is to construct information technologies that support creativity. This ambitious goal can be attained by building on an adequate understanding of creative processes. This paper expands on the four-phase genex framework for generating excellence [l]. Within this integrated Mework, this paper proposes eight activities that require human-computer interaction research and advanced user interface design.

There are numerous problems associated with formulating queries on networked information systems. These include increased data volume and complexity, accompanied by slow network access. This article proposes a new approach to a network query user interfaces that consists of two phases: query preview and query refinement. This new approach is based on the concepts of dynamic queries and query previews, which guides users in rapidly and dynamically eliminating undesired records, reducing the data volume to a manageable size, and refining queries locally before submission over a network. Examples of two applications are given: a Restaurant Finder and a prototype for NASA's Earth Observing Systems Data Information Systems (EOSDIS). Data architecture is discussed, and user feedback is presented.

Handwritten codexes or printed books transformed society by allowing users to preserve and transmit information. Today, leather-bound volumes and illuminated manuscripts are giving way to animated image maps and hot links. Vannevarr Bush's memex has inspired the World Wide Web, which provides users with vast information resources and convenient communications. In looking to the future, we might again transform society by building genexes—generators of excellence. Such inspirational environment would empower personal and collaborative creativity by enabling users to: Collect information from an existing domain of knowledge. Create innovations using advanced tools. Consult with peers or mentors in the field. Disseminate the results widely. This article describes how a framework for an integrated set of software tools might support this 4-phase model of creative in science, medicine, the arts, and beyond. Current initiatives are positive and encouraging, but they do not work in an integrated fashion often miss vital components, and are frequently poorly designed. A well-conceived and clearly stated framework could guide design efforts, coordinate planning, and speed development.

Most windowing systems follow the independent overlapping windows approach, which emerged as an answer to the needs of early computer users. Due to advances in computers, display technology, and increased information needs, modern users demand more functionality from window management systems. We propose Elastic Windows with improved spatial layout and rapid multi-window operations as an alternative to current window management strategies. In this approach, multi-window operations are achieved by issuing operations on window groups hierarchically organized in a space-filling tiled layout similar to TreeMaps.1 Sophisticated multi-window operations have been developed to handle fast task-switching and to structure the work environment of users to their rapidly changing needs. We claim that these multi-window operations and the tiled spatial layout dynamics decrease the cognitive load on users by decreasing the number of window operations. This paper describes the Elastic Windows interface in detail and then presents a user study conducted to compare the performance of 12 users with Elastic Windows and traditional Independent Overlapping Windows. User performance was measured in terms of task environment setup, switching, and task execution for 2, 6, and 12 window situations. Elastic Windows users had statistically significantly faster performance for all tasks in 6 and 12 window situations. These results suggest promising possibilities for multiple window operations and hierarchical nesting, which can be applied to the next generation of tiled as well as overlapped window managers. © 1998 John Wiley & Sons, Ltd.

Most windowing systems follow the independent overlapping windows approach, which emerged as an answer to the needs of the 1980s' technology.Due to advances in computers and display technology, and increased information needs, modem users demand more functionality from window management systems.We proposed Elastic Windows with improved spatial layout and rapid multi-window operations as an alternative to current window management strategies for efficient personal role management [12].In this approach, multi-window operations are achieved by issurng operations on window groups hierarchically organized in a space-filling tiled layout.'l%is paper describes the Elastic Windows interface briefly and then presents a study comparing user performance with Elastic Windows and traditional window management techniques for 2, 6, and 12 window situations.Elastic Whdows users had statistically significantly faster performance for all 6 and 12 window situations, for task environment setup, task environment switching, and task execution.For some tasks there was a ten-fold speed-up in performanceThese results suggest promising possibilities for multiple window operations and hierarchical nesting, which can be applied to the next generation of tiled as well as overlapped window managers.

Direct manipulation user interfaces have proven their worth over two decades, but they are still in their youth.Dramatic opportunities exist to develop direct manipulation programming to create end-user programming tools, dynamic queries to perform information search in large databases, and information visualization to support network database browsing.Direct manipulation depends on visual representation of the objects and actions of interest, physical .actions or pointing instead of complex syntax, and rapid incremental reversible operations whose effect on the object of interest is immediately visible.This strategy can lead to user interfaces that are comprehensible, predictable and controllable.Direct manipulation interfaces are seen as more likely candidates to influence advanced user interfaces than adaptive, autonomous, intelligent agents.User control and responsibility are highly desirable.

Article Elastic Windows: a hierarchical multi-window World-Wide Web browser Share on Authors: Eser Kandogan Department of Computer Science, Human-Computer Interaction Laboratory Department of Computer Science, Human-Computer Interaction LaboratoryView Profile , Ben Shneiderman Institute for Advanced Computer Studies, University of Maryland, College Park, MD Institute for Advanced Computer Studies, University of Maryland, College Park, MDView Profile Authors Info & Claims UIST '97: Proceedings of the 10th annual ACM symposium on User interface software and technologyOctober 1997 Pages 169–177https://doi.org/10.1145/263407.263541Published:01 October 1997 27citation762DownloadsMetricsTotal Citations27Total Downloads762Last 12 Months12Last 6 weeks4 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Designing user interfaces with consistent visual and textual properties is difficult. To demonstrate the harmful effects of inconsistency, we conducted an experiment with 60 subjects. Inconsistent interface terminology slowed user performance by 10 to 25 percent. Unfortunately, contemporary software tools provide only modest support for consistency control. Therefore, we developed SHERLOCK, a family of consistency analysis tools, which evaluates visual and textual properties of user interfaces. It provides graphical analysis tools such as a dialog box summary table that presents a compact overview of visual properties of all dialog boxes. SHERLOCK provides terminology analysis tools including an interface concordance, an interface spellchecker, and terminology baskets to check for inconsistent use of familiar groups of terms. Button analysis tools include a button concordance and a button layout table to detect variant capitalization, distinct typefaces, distinct colors, variant button sizes, and inconsistent button placements. We describe the design, software architecture, and the use of SHERLOCK. We tested SHERLOCK with four commercial prototypes. The outputs, analysis, and feedback from designers of the applications are presented.

LifeLines provide a general visualization environment for personal histories that can be applied to medical and court records, professional histories and other types of biographical data.A one screen overview shows multiple facets of the records.Aspects, for example medical conditions or legal cases, are displayed as individual time lines, while icons indicate discrete events, such as physician consultations or legal reviews.Line color and thickness illustrate relationships or significance, rescaling tools and filters allow users to focus on part of the information.LifeLines reduce the chances of missing information, facilitate spotting anomalies and trends, streamline access to details, while remaining tailorable and easily transferable between applications.The paper describes the use of LifeLines for youth records of the Maryland Department of Juvenile Justice and also for medical records.User's feedback was collected using a Visual Basic prototype for the youth record.

ABSTRACT This paper offers new principles for visual information seeking (VIS). A key concept is to support browsing, which is distinguished from familiar query composition and information retrieval because of its emphasis on rapid filtering to reduce result sets, progressive refinement of search parameters, continuous reformulation of goals, and visual scanning to identify results. VIS principles developed include: dynamic query filters (query parameters are rapidly adjusted with sliders, buttons, maps, etc.), starfield displays (two-dimensional scatterplots to structure result sets and zooming to reduce clutter), and tight coupling (interrelating query components to preserve display invariants and support progressive refinement combined with an emphasis on using search output to foster search input). A FilmFinder prototype using a movie database demonstrates these principles in a VIS environment.

Research has suggested that rapid, serial, visual presentation of text (RSVP) may be an effective way to scan and search through lists of text strings in search of words, names, etc. The Alphaslider widget employs RSVP as a method for rapidly scanning and searching lists or menus in a graphical user interface environment. The Alphaslider only uses an area less than 7 cm x 2.5 cm. The tiny size of the Alphaslider allows it to be placed on a credit card, on a control panel for a VCR, or as a widget in a direct manipulation based database interface. An experiment was conducted with four Alphaslider designs which showed that novice Alphaslider users could locate one item in a list of 10,000 film titles in 24 seconds on average, an expert user in about 13 seconds.

When some items in a menu are selected more frequently than others, as is often the case, designers or individual users may be able to speed performance and improve preference ratings by placing several high-frequency items at the top of the menu. Design guidelines for split menus were developed and applied. Split menus were implemented and tested in two in situ usability studies and a controlled experiment. In the usability studies performance times were reduced by 17 to 58% depending on the site and menus. In the controlled experiment split menus were significantly faster than alphabetic menus and yielded significantly higher subjective preferences. A possible resolution to the continuing debate among cognitive theorists about predicting menu selection times is offered. We conjecture and offer evidence that, at least when selecting items from pull-down menus, a logarithmic model applies to familiar (high-frequency) items, and a linear model to unfamiliar (low-frequency) items.

Three different interfaces were used to browse a large (1296 items) table of contents. A fully expanded stable interface, expand/contract interface, and multipane interface were studied in a between-groups experiment with 41 novice participants. Nine timed fact retrieval tasks were performed; each task is analyzed and discussed separately. We found that both the expand/contract and multipane interfaces produced significantly faster times than the stable interface for many tasks using this large hierarchy; other advantages of the expand/contract and multipane interfaces over the stable interface are discussed. The animation characteristics of the expand/contract interface appear to play a major role. Refinements to the multipane and expand/contract interfaces are suggested. A predictive model for measuring navigation effort of each interface is presented.

Two studies investigated the effect keyboard size has on typing speed and error rates for touchscreen keyboards using the lift-off strategy. A cursor appeared when users touched the screen and a key was selected when they lifted their finger from the screen. Four keyboard sizes were investigated ranging from 24.6 cm to 6.8 cm wide. Results indicate that novices can type approximately 10 words per minute (WPM) on the smallest keyboard and 20 WPM on the largest. Experienced users improved to 21 WPM on the smallest keyboard and 32 WPM on the largest. These results indicate that, although slower, small touchscreen keyboards can be used for limited data entry when the presence of a regular keyboard is not practical. Applications include portable pocket-sized or palmtop computers, messaging systems, and personal information resources. Results also suggest the increased importance of experience on these smaller keyboards. Research directions are suggested.

As policymakers and technology planners respond to the growing activity in human—computer interaction, a broad perspective may be helpful. This article offers a top-down view of current activities and suggests opportunities and challenges for the continued growth of HCI. Partnerships among universities, corporations, government agencies, and professional societies are proposed. Infrastructure needs to support this new discipline are outlined.

One of the powerful applications of Boolean expression is to allow users to extract relevant information from a database. Unfortunately, previous research has shown that users have difficulty specifying Boolean queries. In an attempt to overcome this limitation, a graphical Filter/Flow representation of Boolean queries was designed to provide users with an interface that visually conveys the meaning of the Boolean operators (AND, OR, and NOT). This was accomplished by implementing a graphical interface prototype that uses the metaphor of water flowing through filters. Twenty subjects having no experience with Boolean logic participated in an experiment comparing the Boolean operations represented in the Filter/Flow interface with a text-only SQL interface. The subjects independently performed five comprehension tasks and five composition tasks in each of the interfaces. A significant difference (p < 0.05) in the total number of correct queries in each of the comprehension and composition tasks was found favoring Filter/Flow. © 1993 John Wiley & Sons, Inc.

We designed, implemented and evaluated a new concept for direct manipulation of databases, called dynamic queries, that allows users to formulate queries with graphical widgets, such as sliders. By providing a graphical visualization of the database and search results, users can find trends and exceptions easily. Eighteen undergraduate chemistry students performed statistically significantly faster using a dynamic queries interface compared to two interfaces both providing form fill-in as input method, one with graphical visualization output and one with all-textual output. The interfaces were used to explore the periodic table of elements and search on their properties.

Article Free Access Share on Anthropomorphism: from Eliza to Terminator 2 Authors: Abbe Don View Profile , Susan Brennan View Profile , Brenda Laurel View Profile , Ben Shneiderman View Profile Authors Info & Claims CHI '92: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsJune 1992 Pages 67–70https://doi.org/10.1145/142750.142760Online:01 June 1992Publication History 25citation1,190DownloadsMetricsTotal Citations25Total Downloads1,190Last 12 Months78Last 6 weeks7 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

No abstract available.

We designed, implemented, and evaluated a new concept for visualizing and searching databases utilizing direct manipulation called dynamic queries. Dynamic queries allow users to formulate queries by adjusting graphical widgets, such as sliders, and see the results immediately. By providing a graphical visualization of the database and search results, users can find trends and exceptions easily. User testing was done with eighteen undergraduate students who performed significantly faster using a dynamic queries interface compared to both a natural language system and paper printouts. The interfaces were used to explore a real-estate database and find homes meeting specific search criteria.

article Free Access Share on Tree visualization with tree-maps: 2-d space-filling approach Author: Ben Shneiderman Univ. of Maryland, College Park Univ. of Maryland, College ParkView Profile Authors Info & Claims ACM Transactions on GraphicsVolume 11Issue 1pp 92–99https://doi.org/10.1145/102377.115768Published:02 January 1992Publication History 955citation7,810DownloadsMetricsTotal Citations955Total Downloads7,810Last 12 Months539Last 6 weeks58 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Hypertext users often suffer from the “lost in hyperspace” problem: disorientation from too many jumps while traversing a complex network. One solution to this problem is improved authoring to create more comprehensible structures. This paper proposes several authoring tools, based on hypertext structure analysis. In many hypertext systems authors are encouraged to create hierarchical structures, but when writing, the hierarchy is lost because of the inclusion of cross-reference links. The first part of this paper looks at ways of recovering lost hierarchies and finding new ones, offering authors different views of the same hypertext. The second part helps authors by identifying properties of the hypertext document. Multiple metrics are developed including compactness and stratum . Compactness indicates the intrinsic connectedness of the hypertext, and stratum reveals to what degree the hypertext is organized so that some nodes must be read before others. Several existing hypertexts are used to illustrate the benefits of each technique. The collection of techniques provides a multifaceted view of the hypertext, which should allow authors to reduce undesired structural complexity and create documents that readers can traverse more easily.

Article Demonstrational interfaces: Coming soon? Share on Authors: Brad A. Myers School of Computer Science, Carnegie Mellon University, Pittsburgh, PA School of Computer Science, Carnegie Mellon University, Pittsburgh, PAView Profile , Allen Cypher Apple Computer, Inc. Apple Computer, Inc.View Profile , David Maulsby University of Calgary University of CalgaryView Profile , David C. Smith Apple Computer, Inc. Apple Computer, Inc.View Profile , Ben Shneiderman University of Maryland University of MarylandView Profile Authors Info & Claims CHI '91: Proceedings of the SIGCHI Conference on Human Factors in Computing SystemsApril 1991 Pages 393–396https://doi.org/10.1145/108844.108966Published:01 March 1991 10citation335DownloadsMetricsTotal Citations10Total Downloads335Last 12 Months4Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

No abstract available.

A method for visualizing hierarchically structured information is described. The tree-map visualization technique makes 100% use of the available display space, mapping the full hierarchy onto a rectangular region in a space-filling manner. This efficient use of space allows very large hierarchies to be displayed in their entirety and facilitates the presentation of semantic information. Tree-maps can depict both the structure and content of the hierarchy. However, the approach is best suited to hierarchies in which the content of the leaf nodes and the structure of the hierarchy are of primary importance, and the content information associated with internal nodes is largely derived from their children.>

This article offers a set of goals for user interface development, followed by scenarios of future developments. The applications include home control, hypermedia, office automation, digital photography, collaborative meetings/classrooms, public access, professional workstations, and medical record keeping. Also, predictions are made for some of the underlying technologies such as User Interface Management Systems, remote control, flexible search, display devices, and touchscreens.

No abstract available.

High resolution touch screens and novel usage strategies have overcome earlier problems with parallax and inaccurate pointing. A study testing the utility of three touch screen strategies within the Hyperties hypertext environment was performed. This provided a replication and extension of an earlier touch screen strategy comparison that focused on small closely‐spaced targets. The experiment compared three touch screen strategies in three experimental tasks that reflect hypertext usage. The results showed that a strategy that only uses the initial impact with the touch screen causes the user to miss the target more than other touch strategies. A statistically significant difference in errors was found. Our results should encourage system implementers and touch screen hardware designers to support “touch mouse” strategies that enable cursor dragging on the touch screen surface.

Richard H.C. Seabrook, Ben Shneiderman; The user interface in a hypertext, multiwindow program browser, Interacting with Computers, Volume 1, Issue 3, 1 De

Menus are largely formatted in a linear fashion listing items from the top to bottom of the screen or window. Pull down menus are a common example of this format. Bitmapped computer displays, however, allow greater freedom in the placement, font, and general presentation of menus. A pie menu is a format where the items are placed along the circumference of a circle at equal radial distances from the center. Pie menus gain over traditional linear menus by reducing target seek time, lowering error rates by fixing the distance factor and increasing the target size in Fitts's Law, minimizing the drift distance after target selection, and are, in general, subjectively equivalent to the linear style.

A study comparing the speed, accuracy, and user satisfaction of three different touch screen strategies was performed. The purpose of the experiment was to evaluate the merits of the more intricate touch strategies that are possible on touch screens that return a continuous stream of touch data. The results showed that a touch strategy providing continuous feedback until a selection was confirmed had fewer errors than other touch strategies. The implications of the results for touch screens containing small, densely-packed targets were discussed.

No abstract available.

This paper offers seven issues and specific challenges for researchers and developers of human-computer interaction. These issues are: interaction styles, input techniques, output organization, response time, error handling, individual differences, explanatory and predictive theories.

Menu selection systems reduce training and memorization, simplify entry of choices, and structure the user's tasks. However, the use of menu selection is no guarantee that novices or experts will be satisfied or able to carry out their work. This article focuses on the multiple design issues in creating successful menu selection systems. These include the primary issue of semantic organization and the host of secondary issues such as response time and display rates, shortcuts for frequent users, titles, phrasing of menu items, graphic layout, and selection mechanisms. Novel approaches such as pop-up menus and embedded menus are covered. Experimental results and design guidelines are presented. © 1986 John Wiley & Sons, Inc.

This paper describes an undergraduate human factors course which emphasizes psychologically oriented experimentation on the human use of computers. The reductionist principles of the scientific method are emphasized throughout the course: lucid statement of testable hypotheses, alteration of independent variables, measurement of dependent variables, selection and assignment of subjects, control for biasing, and statistical testing. Term-length team projects are highly motivating for students and have led to worthwhile research contributions.

Changes in requirements for database systems necessitate schema restructuring, database translation, and application or query program conversion. An alternative to the lengthy manual revision process is proposed by offering a set of 15 transformations keyed to the relational model of data and the relational algebra. Motivations, examples, and detailed descriptions are provided.

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.

Computer systems often contain messages which are imprecise ('SYNTAX ERROR'), hostile ('FATAL ERROR, RUN ABORTED'), cryptic ('IEH291H'), or obscure ('CTL DAMAGE, TRANS ERR'). Such messages may be acceptable to computer professionals who regularly use a specific system, but they lead to frustration for novices and for professionals who are using new features or facilities.We have conducted five studies using COBOL compiler syntax errors and text editor command errors to measure the impact of improving the wording of system messages. The results indicate that increased specificity, more positive tone, and greater clarity can improve correction rates and user satisfaction.An overview of the experimental results will be presented along with guidelines for writing system messages.

Direct manipulation is a style of interaction which has been used by implementers of widely varying systems. Direct manipulation permits novice users access to powerful facilities without the burden of learning to use a complex syntax and lengthy list of commands. Display editors use direct manipulation more than line editors. Form-fill-in is more direct than tag fields and delimiters. Spatial data management is more direct than query-by-example, which is more direct than SEQUEL. Computer arcade games and Visicalc are further examples.Direct manipulation involves three interrelated techniques:1. Provide a physically direct way of moving a cursor or manipulating the objects of interest.2. Present a concrete visual representation of the objects of interest and immediately change the view to reflect operations.3. Avoid using a command language and depend? on operations applied to the cognitive model which is shown on the display.

This paper raises concerns that natural language front ends for computer systems can limit a researcher's scope of thinking, yield inappropriately complex systems, and exaggerate public fear of computers. Alternative modes of computer use are suggested and the role of psychologically oriented controlled experimentation is emphasized. Research methods and recent experimental results are briefly reviewed.

The widespread dissemination of computer and information systems to nontechnically trained individuals requires a new approach to the design and development of database interfaces. This paper provides the motivational background for controlled psychological experimentation in exploring the person/machine interface. Frameworks for the reductionist approach are given, research methods discussed, research issues presented, and a small experiment is offered as an example of what can be accomplished. This experiment is a comparison of natural and artificial language query facilities. Although subjects posed approximately equal numbers of valid queries with either facility, natural language users made significantly more invalid queries which could not be answered from the database that was described.

My father counseled me not to give advice to others. Inspite of that admonition, I have an irrepressible desire to make some highly subjective, potentially pompous remarks about introductory programming language textbooks.

Computer science graduates who become professional programmers will have a direct and substantial influence on the impact of applications, but little in traditional computer science training curriculum prepares them for this serious responsibility. Recognizing this situation, we designed a two term sequence for advanced undergraduates and masters students which would not only provide them with the required academic knowledge. The educational atmosphere that we tried to create resembles the internship phase followed in teacher training, medical schools, law schools, clinical psychology and other disciplines.

Abstract The proliferation of papers on programming methodology focus on the program development process but only hint at the form of the final program. This paper distinguishes between the development process and the program product and presents a catalogue of possible program organizations and data structures with examples drawn from the published literature. The methods for sharing data among modules and a classification scheme for programs and data structures is presented.

The technique of batching searches has been ignored in the context of disk based online data retrieval systems. This paper suggests that batching be reconsidered for such systems since the potential reduction in processor demand may actually reduce response time. An analysis with sample numerical results and algorithms is presented.

Abstract By plotting the key value against the record position in a sorted file and then fitting a least squares polynomial through the points, a fast retrieval technique is determined. The target key of a search is inserted in the polynomial and the first access from the file is made on the basis of the evaluation. Since the maximum deviation can be determined, an efficient local search can be made. If the maximum deviation is less than half the size of the file, polynomial searching is more efficient than binary searching. While this method can be applied in many cases, it is most useful in disk oriented file systems where the goal is to minimize the number of accesses even at the expense of some additional calculation.