Real‐world systems change continuously. In domains such as traffic monitoring or cyber security, such changes occur within short time scales. This results in a streaming data problem and leads to unique challenges for the human in the loop, as analysts have to ingest and make sense of dynamic patterns in real time. While visualizations are being increasingly used by analysts to derive insights from streaming data, we lack a thorough characterization of the human‐centred design problems and a critical analysis of the state‐of‐the‐art solutions that exist for addressing these problems. In this paper, our goal is to fill this gap by studying how the state of the art in streaming data visualization handles the challenges and reflect on the gaps and opportunities. To this end, we have three contributions in this paper: (i) problem characterization for identifying domain‐specific goals and challenges for handling streaming data, (ii) a survey and analysis of the state of the art in streaming data visualization research with a focus on how visualization design meets challenges specific to change perception and (iii) reflections on the design trade‐offs, and an outline of potential research directions for addressing the gaps in the state of the art.
This study compared proverb processing across three groups, i.e. patients with fluent aphasia (APH), patients with Alzheimer's Disease (AD), and normal control subjects (NC). Proverb stimuli were used to examine the effects of group membership and proverb familiarity in two presentation formats (i.e. spontaneous versus multiple-choice) on performance. The sensitivity of linguistic and cognitive measures as predictors of ability to interpret proverbs was also investigated. In relation to NC subjects, patients with fluent APH exhibited significant difficulty formulating responses for familiar and unfamiliar spontaneous proverbs, whereas patients with AD demonstrated lower performance only on the unfamiliar proverbs. On the multiple-choice paradigm, however, patients with APH exhibited minimal difficulty. Conversely, the patients with AD manifested significant problems selecting the correct abstract response for familiar proverbs. With regard to predictors, language was relevant to familiar proverb interpretations and to proverbs presented in the spontaneous format. Cognition was a sensitive predictor for unfamiliar proverb interpretations and to the multiple-choice format. Deficits on the proverb tasks are discussed with reference to the potential breakdown of underlying linguistic and cognitive processes. The present data support the diagnostic value of proverbs in elucidating brain-behaviour relationships.
SummaryDespite the growth of the visual analytics (VA) field, there has been limited systematic testing and evaluation to determine the effectiveness of VA solutions for improving knowledge discovery and decision making. The VA community acknowledges the need for a more scientific foundation to guide research on and evaluation of VA tools. A practical methodology and framework will not only inform the design of VA systems but also facilitate establishment of metrics to evaluate their effectiveness. This report describes the findings of a research project with the following scientific and operational objectives in support of the VA community: (a) Enhance understanding of the role of VA in knowledge discovery and insight; (b) Identify more rigorous scientific methods to evaluate effectiveness of VA tools; and (c) Inform design of deployable VA solutions based on this theoretical foundation.U.S. Department of Homeland Security end users do not merely want more displays and tools; they need operational/deployable solutions that enhance information processing and decision making. There is also a need for user testing methodologies and metrics to assess performance effectiveness of VA tools in operationally relevant contexts. To this end, the present research examined scientific literature in cognitive science, human factors, and related fields to identify concepts and research results that inform the application of VA technologies to meet operational challenges. By updating previous taxonomies for VA approaches and applications, we hope to provide a more comprehensive framework and benchmarks for this expanding field.In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions.The following conclusions and recommendations are provided for advancing the VA field and for continuing and expanding this research program in cognitive foundations for VA.Recommendations for future research:• More research is needed on sensemaking/problem solving and the analytic process to help align visualization technologies and representation techniques to user's mental models and thought processes.• Research is required to advance the science and engineering practices of VA tool evaluation.• Research is needed to develop more effective means of communicating the results of analyses to stakeholders (intuitive and natural ways of conveying findings as well as providing rationale and background information supporting the decisions and recommendations).• A more directed application of cognitive theories and results of empirical research on critical decisio...
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 illequipped 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. Research HighlightsDesign insights and evaluation results for the TreatmentExplorer suggest that patients may experience better knowledge gains if designers: Show outcomes and side effects graphically Use staged-animation with guided narration Begin each narration from the same state Follow a consistent narration order Provide both replay and skip-through options Explain one data point per stage Give users control over the flow of narration
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