368,108 research outputs found

    On Regulatory and Organizational Constraints in Visualization Design and Evaluation

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    Problem-based visualization research provides explicit guidance toward identifying and designing for the needs of users, but absent is more concrete guidance toward factors external to a user's needs that also have implications for visualization design and evaluation. This lack of more explicit guidance can leave visualization researchers and practitioners vulnerable to unforeseen constraints beyond the user's needs that can affect the validity of evaluations, or even lead to the premature termination of a project. Here we explore two types of external constraints in depth, regulatory and organizational constraints, and describe how these constraints impact visualization design and evaluation. By borrowing from techniques in software development, project management, and visualization research we recommend strategies for identifying, mitigating, and evaluating these external constraints through a design study methodology. Finally, we present an application of those recommendations in a healthcare case study. We argue that by explicitly incorporating external constraints into visualization design and evaluation, researchers and practitioners can improve the utility and validity of their visualization solution and improve the likelihood of successful collaborations with industries where external constraints are more present.Comment: 9 pages, 2 figures, presented at BELIV workshop associated with IEEE VIS 201

    Toward a Heuristic Model for Evaluating the Complexity of Computer Security Visualization Interface

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    Computer security visualization has gained much attention in the research community in the past few years. However, the advancement in security visualization research has been hampered by the lack of standardization in visualization design, centralized datasets, and evaluation methods. We propose a new heuristic model for evaluating the complexity of computer security visualizations. This complexity evaluation method is designed to evaluate the efficiency of performing visual search in security visualizations in terms of measuring critical memory capacity load needed to perform such tasks. Our method is based on research in cognitive psychology along with characteristics found in a majority of the security visualizations. The main goal for developing this complexity evaluation method is to guide computer security visualization design and compare different visualization designs. Finally, we compare several well known computer security visualization systems. The proposed method has the potential to be extended to other areas of information visualization

    Achieving Evaluation Influence Through Elaboration Likelihood Model-informed Evaluation Product Designs

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    The ultimate purpose of evaluation is social betterment, which is achieved through evaluation influence. Progress has been made in defining the mechanisms of evaluation influence (Mark & Henry, 2004); however, little research has explored how the design of evaluation products trigger these mechanisms. Sister fields such as persuasion psychology can provide guidance to fill this gap. The Elaboration Likelihood Model, a dual-processing model of persuasion, provides insights into how persuasive information is processed and how this processing impacts attitude formation and behavioral intention (Petty & Cacioppo, 1986). By translating the principles of the Elaboration Likelihood Model, this research explores how various data presentation conventions -- minimalist, embellished, and interactive -- impact evaluation influence. In the first phase of this research, minimalist and embellished data visualization conventions did not result in differences in participant experience of the visualization nor different interpretation or attitudinal outcomes; however, motivation to elaborate significantly impacted both participant experiences and outcomes. Additionally, engagement with the data visualization played a role in how participants processed the evaluation findings, with highly engaged individuals basing their evaluand-specific attitudes on the strength of the evaluation findings. The second phase of this research demonstrated no significant differences in attitude strength and donation behaviors between minimalist and embellished data visualization. Instead, donation behaviors were driven by attitudes formed after reading the evaluation findings and motivation to elaborate. The final experiment found that interactive data presentations promoted elaboration and the formation of attitudes based on the strength of the evaluation findings. Additionally, significant differences in attitude persistence and behavioral intent were found based on the strength of evaluation findings; behavioral intent was additionally impacted by motivation to elaborate and engagement with the data presentation. Finally, donation behaviors were driven by motivation to elaborate, engagement with the data presentation, and evaluand-specific attitudes formed after reading the evaluation findings. The results of this research demonstrate that the design of evaluation products and audience characteristics such as motivation to elaborate can be factors impacting evaluation influence. Based on these findings, evaluation practitioners can promote evaluation influence by seeking out opportunities to design products that increase audience involvement to support elaboration processes. The current research also identifies both risks to and opportunities for increased evaluation influence based on the audiences\u27 level of motivation to elaborate, which provide guidance to evaluation practitioners seeking to maximize their evaluation\u27s impact. More broadly, this research advances new directions for research on evaluation influence by providing empirical evidence for influence pathways, for data visualization research by demonstrating the importance of motivation to elaborate to visualization experience and outcomes, and for research on the application of Elaboration Likelihood Model principles within the context of evaluation

    Doctor of Philosophy

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    dissertationThis dissertation establishes a new visualization design process model devised to guide visualization designers in building more effective and useful visualization systems and tools. The novelty of this framework includes its flexibility for iteration, actionability for guiding visualization designers with concrete steps, concise yet methodical definitions, and connections to other visualization design models commonly used in the field of data visualization. In summary, the design activity framework breaks down the visualization design process into a series of four design activities: understand, ideate, make, and deploy. For each activity, the framework prescribes a descriptive motivation, list of design methods, and expected visualization artifacts. To elucidate the framework, two case studies for visualization design illustrate these concepts, methods, and artifacts in real-world projects in the field of cybersecurity. For example, these projects employ user-centered design methods, such as personas and data sketches, which emphasize our teams' motivations and visualization artifacts with respect to the design activity framework. These case studies also serve as examples for novice visualization designers, and we hypothesized that the framework could serve as a pedagogical tool for teaching and guiding novices through their own design process to create a visualization tool. To externally evaluate the efficacy of this framework, we created worksheets for each design activity, outlining a series of concrete, tangible steps for novices. In order to validate the design worksheets, we conducted 13 student observations over the course of two months, received 32 online survey responses, and performed a qualitative analysis of 11 in-depth interviews. Students found the worksheets both useful and effective for framing the visualization design process. Next, by applying the design activity framework to technique-driven and evaluation-based research projects, we brainstormed possible extensions to the design model. Lastly, we examined implications of the design activity framework and present future work in this space. The visualization community is challenged to consider how to more effectively describe, capture, and communicate the complex, iterative nature of data visualization design throughout research, design, development, and deployment of visualization systems and tools

    ANNIS: a linguistic database for exploring information structure

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    In this paper, we discuss the design and implementation of our first version of the database "ANNIS" (ANNotation of Information Structure). For research based on empirical data, ANNIS provides a uniform environment for storing this data together with its linguistic annotations. A central database promotes standardized annotation, which facilitates interpretation and comparison of the data. ANNIS is used through a standard web browser and offers tier-based visualization of data and annotations, as well as search facilities that allow for cross-level and cross-sentential queries. The paper motivates the design of the system, characterizes its user interface, and provides an initial technical evaluation of ANNIS with respect to data size and query processing

    Information Visualization of Metacognitive Skills During the Software Development Process Based on an Adapted Engineering Design Metacognitive Questionnaire

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    In software development, either alone or in a team, there are many aspects that determine the success in developing the software, including each developer\u27s skills. Studies show that the application of metacognition can increase the effectiveness and efficiency of software development. To measure a metacognition skill, there need to be a metacognition measurement tools. One example of this measurement method is adapted engineering design metacognitive questionnaire. However, the respondents feel that existing tools still have not given them any benefits. This research is conducted to develop an information visualization tools for the metacognition measurement from an adapted engineering design metacognitive questionnaire. The research was performed using qualitative method adapted from the user-centered design approach, which is user requirement analysis, design alternatives, prototyping, and evaluation. The finding suggests that with information visualization, the students as the respondents feel the benefits of filling the EDMQ questionnaire. However, from the design standpoint, there are still numerous things that can be improved to make the visualization more informative
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