Sunfall: A Collaborative Visual Analytics System for Astrophysics

Aragon, C.; Bailey, S.; Poon, Sarah; Runge, K.; Thomas, R. C.

doi:10.1109/vast.2007.4389026

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…Garg et al [162] describe a visual analytic framework which uses logic programming as the underlying computing machinery to encode the relations as rules and facts and compute with them. Chen et al [95], Brennan et al [99] and Aragon et al [163] proposed three frameworks for collaborative visual analytics with different focuses. However, these frameworks were designed for a specific domain/problem or data type.…”

Section: ) Infrastructurementioning

confidence: 99%

Visual Analytics: A Comprehensive Overview

Cui

2019

IEEE Access

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With the ever-increasing amount of data, the world has stepped into the era of ''Big Data''. Presently, the analysis of massive and complex data and the extraction of relevant information, have been become essential tasks in many fields of studies, such as health, biology, chemistry, social science, astronomy, and physics. However, compared with the development of data storage and management technologies, our ability to gain useful information from the collected data does not match our ability to collect the data. This gap has led to a surge of research activity in the field of visual analytics. Visual analytics employs interactive visualization to integrate human judgment into algorithmic data-analysis processes. In this paper, the aim is to draw a complete picture of visual analytics to direct future research by examining the related research in various application domains. As such, a novel categorization of visual-analytics applications from a technical perspective is proposed, which is based on the dimensionality of visualization and the type of interaction. Based on this categorization, a comprehensive survey of visual analytics is performed, which examines its evolution from visualization and algorithmic data analysis, and investigates how it is applied in various application domains. In addition, based on the observations and findings gained in this survey, the trends, major challenges, and future directions of visual analytics are discussed.

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Section: ) Infrastructurementioning

confidence: 99%

Visual Analytics: A Comprehensive Overview

Cui

2019

IEEE Access

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“…The separating hyper-plane is sampled in the data space, and projected onto the 2D plane. The work by Aragon et al [23] utilized SVMs as part of a visual analysis system for astrophysics, but provided no general support for SVM exploration. In Ref.…”

Section: Support Vector Machinesmentioning

confidence: 99%

EasySVM: A visual analysis approach for open-box support vector machines

Chen

et al. 2017

Comp. Visual Media

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Support vector machines (SVMs) are supervised learning models traditionally employed for classification and regression analysis. In classification analysis, a set of training data is chosen, and each instance in the training data is assigned a categorical class. An SVM then constructs a model based on a separating plane that maximizes the margin between different classes. Despite being one of the most popular classification models because of its strong performance empirically, understanding the knowledge captured in an SVM remains difficult. SVMs are typically applied in a black-box manner where the details of parameter tuning, training, and even the final constructed model are hidden from the users. This is natural since these details are often complex and difficult to understand without proper visualization tools. However, such an approach often brings about various problems including trial-and-error tuning and suspicious users who are forced to trust these models blindly.The contribution of this paper is a visual analysis approach for building SVMs in an open-box manner. Our goal is to improve an analyst's understanding of the SVM modeling process through a suite of visualization techniques that allow users to have full interactive visual control over the entire SVM training process. Our visual exploration tools have been developed to enable intuitive parameter tuning, training data 2016-12-24; accepted: 2017-01-09 manipulation, and rule extraction as part of the SVM training process. To demonstrate the efficacy of our approach, we conduct a case study using a real-world robot control dataset.

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“…As such methods are still relatively new to the design of CI technologies, there are a growing number of scholars employing human-centered design approaches to successfully understand and design CI tools across a variety of domains, including astrophysics [19,20] and gravitational physics [21].…”

Section: As a Sociotechnical Systemmentioning

confidence: 99%

“…Text-based chat was the most frequently mentioned method of interaction recommended by the students as a way to communicate with other players in game, yet integrating real-time interactions was a continual design hurdle. Coordination of actual scientists in a distributed CI environment is notably also a messy process, highly dependent on the use of appropriate tools for remote communication (e.g., [19,20]). Some players said that communicating with others was the most enjoyable aspect of gameplay, whereas others found communicating with people in a game 'annoying'.…”

Section: Coordinated Communicationmentioning

confidence: 99%

Game design for bioinformatics and cyberinfrastructure learning: a parallel computing case study

Perry

Robinson

Cruz

et al. 2014

Concurrency and Computation

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SUMMARY As a growing number of serious games have been developed for biology and computer science learning, few address the communication and technical challenges that arise in cyberinfrastructure (CI) intensive projects, where multiple‐domain scientists collaborate. This paper describes empirical data collected during a year‐long human‐centered game design process, in which design ideas generated by high‐school students were bridged with bioinformatics and parallel computing learning concepts. Our research shows that ‘fun’ and engaging game elements are actually well suited for addressing the sociotechnical aspects of CI projects. We provide a human‐centered game design methodology, as well as a case study, in which this methodology is applied to the design of parallel computing‐focused mini‐games. This research has implications for integrating large‐scale computing concepts such as shared resources and services into gaming experiences. It also has implications for supporting learning through enjoyable and fun experiences as part of a larger CI collaborative environment. Copyright © 2014 John Wiley & Sons, Ltd.

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Sunfall: A Collaborative Visual Analytics System for Astrophysics

Cited by 6 publications

References 13 publications

Visual Analytics: A Comprehensive Overview

Visual Analytics: A Comprehensive Overview

EasySVM: A visual analysis approach for open-box support vector machines

Game design for bioinformatics and cyberinfrastructure learning: a parallel computing case study

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