Visual Analytics Science And Technology Research Articles

Using the VAST Challenge in Undergraduate CS Research

The Visual Analytics Science and Technology (VAST) Challenge is a yearly competition designed to push forward visual analytics research through synthetic, yet realistic analytic tasks. In this pape...

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

A comparative approach to enhance information interaction design of visual analytics systems

This paper introduces a novel comparative strategy to access, synthesize, and redesign a mobile visual analytics (VA) system. Designing, evaluating, and improving VA tools are challenging because of the exploratory and unpredicted nature of their users' analysis activities in a real context. Often the system development approach is running rounds of iteration based on one or a few design ideas and related references. Inspired by ideation and design selection from design-thinking literature, we start to redesign systems from comparison and filtering based on a broad range of design ideas. This approach focuses on the information interaction design of systems; integrates design principles from information design, sensorial design, and interaction design as guidelines; compares VA systems at the component level; and seeks unique and adaptive design solutions. The Visual Analytics Benchmark Repository provides a rich collection of the Visual Analytics Science and Technology (VAST) challenges submission reports and videos. For each challenge design problem, there are multiple creative and mature design solutions. Based on this resource, we conducted a series of empirical user studies to understand the user experience by comparing different design solutions, enhanced one visual analytics system design MobileAnalymator by synthesizing new features and removing redundant functions, and accessed the redesign outcomes with the same comparative approach.

The VAST Challenge: history, scope, and outcomes: An introduction to the Special Issue

The annual Visual Analytics Science and Technology (VAST) challenge provides Visual Analytics researchers, developers, and designers an opportunity to apply their best tools and techniques against invented problems that include a realistic scenario, data, tasks, and questions to be answered. Submissions are processed much like conference papers, contestants are provided reviewer feedback, and excellence is recognized with awards. A day-long VAST Challenge workshop takes place each year at the IEEE VAST conference to share results and recognize outstanding submissions. Short papers are published each year in the annual VAST proceedings. Over the history of the challenge, participants have investigated a wide variety of scenarios, such as bioterrorism, epidemics, arms smuggling, social unrest, and computer network attacks, among many others. Contestants have been provided with large numbers of realistic but synthetic Coast Guard interdiction records, intelligence reports, hospitalization records, microblog records, personal RFID tag locations, huge amounts of cyber security log data, and several hours of video. This paper describes the process for developing the synthetic VAST Challenge datasets and conducting the annual challenges. This paper also provides an introduction to this special issue of Information Visualization, focusing on the impacts of the VAST Challenge.

Guest Editors' Introduction: Special Section on the IEEE Conference on Visual Analytics Science and Technology (VAST)

Visual Analytics (VA) is an evolving field that, at its core, is directed to the science of analytical reasoning supported by highly interactive visual interfaces. The IEEE Conference on Visual Analytics Science and Technology (IEEE VAST), founded in 2006 as the IEEE Symposium on Visual Analytics Science and Technology, is the first international conference dedicated to advances in Visual Analytics Science and Technology. The IEEE Transactions on Visualization and Computer Graphics (TVCG) has recognized and honored the importance of Visual Analytics from the beginning, and invites the authors of the best conference papers to submit substantively extended versions of VAST papers to the journal. For these papers, TVCG applies the usual standard in asking for more than 30% new material and insights compared to the conference paper. This special section presents the extended versions of the best papers of IEEE VAST 2011, which took place in October 2011 in Providence, Rhode Island, USA. These papers were selected together with the best paper award selection committee, which was composed of three members who reviewed the top papers and their peer reviews. The three selected papers went through the regular and standard reviewing process of TVCG. The papers presented here reflect the diversity of the growing field of visual analytics. Collectively, the set of papers exemplify three components that are central to visual analytics as a field. the Guest Editors then provide an overview of the technical articles and features presented in this issue.

BANKSAFE: Visual analytics for big data in large-scale computer networks

The enormous growth of data in the last decades led to a wide variety of different database technologies. Nowadays, we are capable of storing vast amounts of structured and unstructured data. To address the challenge of exploring and making sense out of big data using visual analytics, the tight integration of such backend services is needed. In this article, we introduce BANKSAFE, which was built for the VAST Challenge 2012 and won the outstanding comprehensive submission award. BANKSAFE is based on modern database technologies and is capable of visually analyzing vast amounts of monitoring data and security-related datasets of large-scale computer networks. To better describe and demonstrate the visualizations, we utilize the Visual Analytics Science and Technology (VAST) Challenge 2012 as case study. Additionally, we discuss lessons learned during the design and development of BANKSAFE, which are also applicable to other visual analytics applications for big data.

Guest Editors' Introduction: Special Section on the IEEE Conference on Visual Analytics Science and Technology (VAST)

The articles in this special section contain selected papers from the IEEE Conference on Visual Analytics Science and Technology (VAST).

Developing guidelines for assessing visual analytics environments

In this article, we develop guidelines for evaluating visual analytics environments based on a synthesis of reviews for the entries to the 2009 Visual Analytics Science and Technology (VAST) Symposium Challenge and from a user study with professional intelligence analysts. By analyzing the 2009 VAST Challenge reviews, we gained a better understanding of what is important to our reviewers, both visualization researchers and professional analysts. We also report on a small user study with professional analysts to determine the important factors that they use in evaluating visual analysis systems. We also looked at guidelines developed by researchers in various domains and synthesized the results from these three efforts into an initial set for use by others in the community. One challenge for future visual analytics systems is to help in the generation of reports. In our user study, we also worked with analysts to understand the criteria they used to evaluate the quality of analytic reports. We propose that this knowledge will be useful as researchers look at systems to automate some of the report generation.1 From these two efforts, we produced some initial guidelines for evaluating visual analytics environments and for the evaluation of analytic reports. It is important to understand that these guidelines are initial drafts and are limited in scope as the visual analytics systems we evaluated were used in specific tasks. We propose these guidelines as a starting point for the Visual Analytics Community.

Guest Editor's Introduction: Special Section on the IEEE Symposium on Visual Analytics Science and Technology (VAST)

Guest Editor's Introduction: Special Section on the IEEE Symposium on Visual Analytics Science and Technology (VAST)

Guest Editor's Introduction: Special Section on the IEEE Symposium on Visual Analytics Science and Technology (VAST)

The three papers in this special section were originally presented at the IEEE Symposium on Visual Analytics Science and Technology (VAST) in Columbus, Ohio, in October 2008.

Advancing User-Centered Evaluation of Visual Analytic Environments through Contests

In this paper, the authors describe the Visual Analytics Science and Technology (VAST) Symposium contests run in 2006 and 2007 and the VAST 2008 and 2009 challenges. These contests were designed to provide researchers with a better understanding of the tasks and data that face potential end users. Access to these end users is limited because of time constraints and the classified nature of the tasks and data. In that respect, the contests serve as an intermediary, with the metrics and feedback serving as measures of utility to the end users. The authors summarize the lessons learned and the future directions for VAST Challenges.

Evaluating Visual Analytics at the 2007 VAST Symposium Contest

The second Visual Analytics Science and Technology (VAST) contest's data consisted of a heterogeneous synthetic collection of news articles with additional supporting files. It also contained a scenario with embedded threats that provided ground truth. Using visual analytic tools, participants sought evidence of illegal and terrorist activities. The authors report the results and lessons learned.

Visual Analytics Science and Technology

It is an honor to welcome you to the first theme issue of information visualization (IVS) dedicated entirely to the study of visual analytics. It all started from the establishment of the U.S. Department of Homeland Security (DHS) sponsored National Visualization and Analytics Center™ (NVAC™) at the Pacific Northwest National Laboratory (PNNL) in 2004. In 2005, under the leadership of NVAC, a team of the world’s best and brightest multidisciplinary scholars coauthored its first research and development (R&D) agenda Illuminating the Path, which defines the study as “the science of analytical reasoning facilitated by interactive visual interfaces.” Among the most exciting, challenging, and educational events developed since then was the first IEEE Symposium on Visual Analytics Science and Technology (VAST) held in Baltimore, Maryland in October 2006. This theme issue features seven outstanding articles selected from the IEEE VAST proceedings and a commentary article contributed by Jim Thomas, the director of NVAC, on the status and progress of the center.