Survey companion websites allow users to explore collected survey information more deeply, as well as update or add entries for papers. These sites can help information stay relevant past the original release date of ...
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ISBN:
(纸本)9798350325577
Survey companion websites allow users to explore collected survey information more deeply, as well as update or add entries for papers. These sites can help information stay relevant past the original release date of the survey paper. However, creating and maintaining a website can be laborious and difficult, especially when authors might not be experienced with programming. We introduce Indy Survey Tool to help authors develop companion websites for survey papers across diverse fields of study. The tool's core aim is to identify correlations between categorizations of papers. To accomplish this, the tool offers multiple combined filters and correlation matrix visualizations that enable users to explore the data from diverse perspectives. The tool's visualizations, list of papers, and filters are harmoniously integrated and highly responsive, providing users with feedback based on their selections. Identifying correlations in survey papers is a pivotal aspect of research, as it can enable the recognition of common combinations of categorizations within the papers-as well as highlight any omissions. The versatility of Indy Survey Tool enables researchers to delve into the correlations between categorizations in survey data, an essential aspect of research that can reveal gaps in the literature and highlight promising areas for future exploration. A preprint and supplemental material for the paper can be found at ***/tdhqn.
Understanding and visualizing principal components without losing multi-dimensional information has been a long-standing challenge until now. Here, we describe a novel lossless visual technique that overcomes such dif...
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ISBN:
(纸本)9798350341614
Understanding and visualizing principal components without losing multi-dimensional information has been a long-standing challenge until now. Here, we describe a novel lossless visual technique that overcomes such difficulties, General Line Coordinates-Principal Components Analysis (GLC-PCA)-an approach that provides much more information about individual cases than other methods, with improved structural readability and comprehensibility for PCA. Experimental case studies and comparisons with other works demonstrate this effect. A software system called MAVERICK implements it.
This study compares two visualization methods for teleoperated assembly tasks regarding the performance and workload of human operators. The two methods were direct view and two-dimensional video stream. In a between-...
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ISBN:
(纸本)9798400703232
This study compares two visualization methods for teleoperated assembly tasks regarding the performance and workload of human operators. The two methods were direct view and two-dimensional video stream. In a between-subjects study design with 42 participants, we evaluated the operator performance of a teleoperated (dis)assembly task and compared the workload that the two visualization methods put on their operators. Performance was measured by task completion time, workload was subjectively measured by NASA-TLX, and objectively by a secondary task (n-back task). The results show that indirect visualization by a video stream leads to signifcantly lower performance. However, no signifcant diferences were found in subjective or objectiveworkload measurements. The results of the evaluations emphasize the importance of system evaluation in specifc use cases and aid in the development of intuitive and efcient human-robot interfaces for teleoperated assembly tasks for non-expert users.
This paper describes the design of a dashboard and analysis pipeline to monitor users of visualization tools in the wild. Our pipeline describes how to extract analysis KPIs from extensive log event data and a mix of ...
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ISBN:
(纸本)9798350325577
This paper describes the design of a dashboard and analysis pipeline to monitor users of visualization tools in the wild. Our pipeline describes how to extract analysis KPIs from extensive log event data and a mix of user types. The resulting three-page dashboard displays live KPIs, helping analysts to understand users, detect exploratory behaviors, plan education interventions, and improve tool features. We propose this case study as a motivation to use the dashboard approach for a more 'casual' monitoring of users and building carer mindsets for visualization tools.
Interpretable interactive visual pattern discovery in lossless 3D visualization is a promising way to advance machine learning. It enables end users who are not data scientists to take control of the model development...
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ISBN:
(纸本)9798350341614
Interpretable interactive visual pattern discovery in lossless 3D visualization is a promising way to advance machine learning. It enables end users who are not data scientists to take control of the model development process as a self-service. It is conducted in 3D General Line Coordinates (GLC) visualization space, which preserves all n-D information in 3D. This paper presents a system which combines three types of GLC: Shifted Paired Coordinates (SPC), Shifted Tripled Coordinates (STC), and General Line Coordinates-Linear (GLC-L) for interactive visual pattern discovery. A transition from 2-D visualization to 3-D visualization allows for a more distinct visual pattern than in 2-D and it also allows for finding the best data viewing positions, which are not available in 2-D. It enables in-depth visual analysis of various class-specific data subsets comprehensible for end users in the original interpretable attributes. Controlling model overgeneralization by end users is an additional benefit of this approach.
In this work, we present GitTruck@Duck;a web-powered software visualization tool that combines hierarchical file structure with configurable software evolution and collaboration metrics on adjustable time ranges. In a...
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ISBN:
(纸本)9798350395693;9798350395686
In this work, we present GitTruck@Duck;a web-powered software visualization tool that combines hierarchical file structure with configurable software evolution and collaboration metrics on adjustable time ranges. In an automated mining process, Git Truck aggregates a system's Git history using an in-memory relational database, along with an algorithm for detecting the renaming of files over time. Users can explore the Git history in a 2D hierarchical visualization of folders and files, where they encode evolution and collaboration metrics (e.g., top contributors or last change date) on the size and color of the marks that represent files. Users can gain fine-grain control over these metrics by specifying the time ranges for inspection.
Draco introduced a constraint-based framework to model visualization design in an extensible and testable form. It provides a way to abstract design guidelines from theoretical and empirical studies and applies the kn...
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ISBN:
(纸本)9798350325577
Draco introduced a constraint-based framework to model visualization design in an extensible and testable form. It provides a way to abstract design guidelines from theoretical and empirical studies and applies the knowledge in automated design tools. However, Draco is challenging to use because there is limited tooling and documentation. In response, we present Draco 2, the successor with (1) a more flexible visualization specification format, (2) a comprehensive test suite and documentation, and (3) flexible and convenient APIs. We designed Draco 2 to be more extensible and easier to integrate into visualization systems. We demonstrate these advantages and believe that they make Draco 2 a platform for future research.
There are situations where we need to understand a person's health register data, get an overview of it and inspect the details of interest, preferably in a short period of time. Typical situations are a doctor se...
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ISBN:
(纸本)9798350341614
There are situations where we need to understand a person's health register data, get an overview of it and inspect the details of interest, preferably in a short period of time. Typical situations are a doctor seeing a patient for the very first time, or a researcher trying to understand what makes a person an outlier in a patient cohort. We have developed a visualization tool, called LifeTrack, that will show a person's whole health register history in a single view. The structure of the LifeTrack data view is based on concepts familiar to the target audience, and allows one to see both the overview and details of the data.
Employee turnover is a significant concern across industries, resulting in wasted training resources and the costs associated with hiring replacements. Understanding the underlying reasons behind employee attrition is...
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ISBN:
(纸本)9798350380170;9798350380163
Employee turnover is a significant concern across industries, resulting in wasted training resources and the costs associated with hiring replacements. Understanding the underlying reasons behind employee attrition is crucial for businesses seeking to address this issue. Employing data analytics solutions can lead to substantial savings in terms of training hours and financial resources. However, in addition to accurate predictions of employee turnover, the explainability of these analytics results is equally important to gain user trust. Many existing data analytics techniques provide predictions and recommendations in an opaque "black box" manner, making it challenging for humans to understand the reasoning behind them. In this paper, we present an explainable artificial intelligence (XAI) solution that combines cutting-edge techniques and enhances them to generate practical and comprehensible explanations for endusers. To assess the effectiveness of our XAI solution, we conduct a case study using real-life employee turnover data. The results demonstrate the practicality and usefulness of our XAI solution in applications such as analyzing employee turnover.
PLUME is an open-source software toolbox (PLUME Recorder, PLUME Viewer, PLUME Python) for recording, replaying, and analyzing behavioral and physiological data from 6DoF (Degrees of Freedom) XR experiments created wit...
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ISBN:
(纸本)9798350374490;9798350374506
PLUME is an open-source software toolbox (PLUME Recorder, PLUME Viewer, PLUME Python) for recording, replaying, and analyzing behavioral and physiological data from 6DoF (Degrees of Freedom) XR experiments created with Unity. This work has been conditionally accepted for presentation at ieee VR 2024 as ieee TVCG paper. The present demonstration aims to showcase the capabilities of PLUME as an easy-to-use, performant tool for XR researchers, and to engage the research community.
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