IEEE VIS Research Articles

VISPubComPAS: a comparative analytical system for visualization publication data

For an unfamiliar field, researchers who are looking for interdisciplinary collaboration or students who are going to start their research career often need to look for top research affiliations and domain experts according to the publication of top conferences or journals in this field. Further comparative analysis of affiliations or experts with similar achievements is also needed in order to find suitable collaborators or supervisors. In this work, we provide comprehensive visual analysis of research affiliations and domain experts based on papers accepted by the IEEE VIS from 1990 to 2018. First, we extract multi-word keywords from title and abstract automatically and then extract topics using LDA model based on these keywords. Second, we extract relationship between authors and affiliations based on co-author analysis. Third, we design and implement VISPubComPAS, a requirement-driven analysis system to (1) help users discover top affiliations and experts of required keywords; (2) visualize the relationships and statistics of these affiliations and experts; (3) compare two selected affiliations or experts of interest in detail by visualization. Finally, we conduct use cases and user reviews to demonstrate the effectiveness of VISPubComPAS.

Visualization and the Digital Humanities.

For the past two years, researchers from the visualization community and the digital humanities have come together at the IEEE VIS conference to discuss how both disciplines can work together to push research goals in their respective disciplines. In this paper, we present our experiences as a result of this collaboration.

Frontier of Information Visualization and Visual Analytics in 2016

Visualization has evolved into a flourishing research field in recent 30 years. There are substantial visualization methodologies and applications published every year. Most of literature surveys focus on reviewing the state-of-art techniques in a certain direction in-depth. In this work, we conduct a cross-section survey by taking all the latest literatures as a whole, to obtain insights into the ecology of Information Visualization and Visual Analytics field in 2016. Center around 70-related publications in the IEEE VIS, we perform a mixed quantitative and qualitative analysis to report the current research progress, including statistical overview as well as detailed research topics.

Visual Analysis of Relationships between Heterogeneous Networks and Texts: An Application on the IEEE VIS Publication Dataset

The visual exploration of large and complex network structures remains a challenge for many application fields. Moreover, a growing number of real-world networks is multivariate and often interconnected with each other. Entities in a network may have relationships with elements of other related datasets, which do not necessarily have to be networks themselves, and these relationships may be defined by attributes that can vary greatly. In this work, we propose a comprehensive visual analytics approach that supports researchers to specify and subsequently explore attribute-based relationships across networks, text documents and derived secondary data. Our approach provides an individual search functionality based on keywords and semantically similar terms over the entire text corpus to find related network nodes. For examining these nodes in the interconnected network views, we introduce a new interaction technique, called Hub2Go, which facilitates the navigation by guiding the user to the information of interest. To showcase our system, we use a large text corpus collected from research papers listed in the visualization publication dataset that consists of 2752 documents over a period of 25 years. Here, we analyze relationships between various heterogeneous networks, a bag-of-words index and a word similarity matrix, all derived from the initial corpus and metadata.

VISTopic: A visual analytics system for making sense of large document collections using hierarchical topic modeling

Effective analysis of large text collections remains a challenging problem given the growing volume of available text data. Recently, text mining techniques have been rapidly developed for automatically extracting key information from massive text data. Topic modeling, as one of the novel techniques that extracts a thematic structure from documents, is widely used to generate text summarization and foster an overall understanding of the corpus content. Although powerful, this technique may not be directly applicable for general analytics scenarios since the topics and topic–document relationship are often presented probabilistically in models. Moreover, information that plays an important role in knowledge discovery, for example, times and authors, is hardly reflected in topic modeling for comprehensive analysis. In this paper, we address this issue by presenting a visual analytics system, VISTopic, to help users make sense of large document collections based on topic modeling. VISTopic first extracts a set of hierarchical topics using a novel hierarchical latent tree model (HLTM) (Liu et al., 2014). In specific, a topic view accounting for the model features is designed for overall understanding and interactive exploration of the topic organization. To leverage multi-perspective information for visual analytics, VISTopic further provides an evolution view to reveal the trend of topics and a document view to show details of topical documents. Three case studies based on the dataset of IEEE VIS conference demonstrate the effectiveness of our system in gaining insights from large document collections.

A report from VIS 2016

IEEE VIS 2016 brought together researchers and practitioners to discuss the latest developments in visualization and visual analytics research and their applications. The authors describe the highlights of the 2016 event.

Preface

The papers in this special issue were presented at IEEE VIS 2016, held during October 23-28, 2016 in Baltimore, MD. VIS contains three conferences, held concurrently: the IEEE Visual Analytics Science and Technology Conference (IEEE VAST 2016), the IEEE Information Visualization Conference (IEEE InfoVis 2016), and the IEEE Scientific Visualization Conference (IEEE SciVis2016).

Highlights from the IEEE VIS 2013 Arts Program (VISAP’13): Part 2

This special section in Leonardo highlights presentations and artworks from the IEEE VIS Arts Program, or VISAP, which includes both an art exhibition and peer-reviewed papers sessions. Together they provide a forum that encourages dialog about the relationship between aesthetics and visualization, and for discussing the potential roles of artists, humanities scholars and designers in foundational research in information visualization. The IEEE VIS conference is the premier venue for advances in visualization, bringing together researchers and practitioners from academia, government, and industry to explore their shared interests in tools, techniques and technology. VISAP, taking part concurrently within the larger IEEE VIS conference each year, provides an opportunity for artists and scholars to interact with these communities and to learn about the latest developments in visualization, while at the same time exposing visualization researchers to current topics and trends in the media arts. The theme for VISAP’13 was Art+Experiment. Visualization research encompasses not only data representation, but also the development of interaction techniques, explorations of display aesthetics and examinations of applied perception. Increasingly, empirical justification for new visualization techniques is derived through well-designed experiments. What might it mean for an art installation to produce experimental results? Could an artwork be expressive, challenging and conceptual, yet simultaneously rigorous, practical and empirical? We invited artists and researchers to think about the connections and chasms between art and research, and to explore the nature of experimental design and creative experimentation. Featured in this special section are a selection of the VISAP’13 artists and authors who approached the theme of Art+Experiment in a compelling way. VISAP’13 took place from 13–18 October 2013 in Atlanta, Georgia. It was co-chaired by Angus Forbes and Lauren Thorson. For more information about VISAP’13: .

Analytic provenance for sensemaking: a research agenda.

Sensemaking is a process of finding meaning from information that often involves activities such as information foraging and hypothesis generation. It can be valuable to maintain a history of the data and reasoning involved. This history, commonly known as provenance information, can be a resource for reflection-in-action' during analysis, supporting collaboration between analysts, and can help trace data quality and uncertainty through the analysis process. Currently, there is limited work on utilizing analytic provenance, which captures the interactive data exploration and human reasoning process, to support sensemaking. This article presents and extends the research challenges discussed in a IEEE VIS 2014 workshop on this topic to provide an agenda for sensemaking analytic provenance.

Visual inspection of multivariate volume data based on multi-class noise sampling

Visualizing multivariate volume data is useful when the user wants to inspect the correlational distributions of multiple variables in a spatial field. Existing solutions commonly rely on color blending or weaving techniques to show multiple variables on a sampling point, probably causing heavy visual confusion. This paper presents an alternative solution that employs a multi-class sampling technique to generate spatially separated sampling points for multiple variables and illustrates the sampling points of each variable individually. We combine this new sampling scheme with the conventional direct volume rendering mode, iso-surface mode, and the cutting plane mode to support interactive inspection of volumetric distributions of multiple variables. The effectiveness of our approach is demonstrated with the IEEE VIS Contest 2004 Hurricane dataset and a 3D nuclear fusion simulation dataset.

Visualization as Seen through its Research Paper Keywords.

We present the results of a comprehensive multi-pass analysis of visualization paper keywords supplied by authors for their papers published in the IEEE Visualization conference series (now called IEEE VIS) between 1990-2015. From this analysis we derived a set of visualization topics that we discuss in the context of the current taxonomy that is used to categorize papers and assign reviewers in the IEEE VIS reviewing process. We point out missing and overemphasized topics in the current taxonomy and start a discussion on the importance of establishing common visualization terminology. Our analysis of research topics in visualization can, thus, serve as a starting point to (a) help create a common vocabulary to improve communication among different visualization sub-groups, (b) facilitate the process of understanding differences and commonalities of the various research sub-fields in visualization, (c) provide an understanding of emerging new research trends, (d) facilitate the crucial step of finding the right reviewers for research submissions, and (e) it can eventually lead to a comprehensive taxonomy of visualization research. One additional tangible outcome of our work is an online query tool (http://keyvis.org/) that allows visualization researchers to easily browse the 3952 keywords used for IEEE VIS papers since 1990 to find related work or make informed keyword choices.

State of the Journal

IEEE Transactions on Visualization and Computer Graphics (TVCG) has published more papers in 2013 than in any previous year. TVCG continues to be in an excellent state. For the first time, the entire proceedings of IEEE VAST 2013 papers became part of the VIS special issue of TVCG. At the start of October 2013, TVCG had received more than 265 regular submissions, more than last year at the same time. This year we also observed a healthy number of 150 and 402 submissions to the IEEE VR Conference issue and the VIS conference issue that contains the Proceedings of the IEEE Information Visualization, Scientific Visualization, and Visual Analytics Science and Technology 2013 Conferences, respectively. We are expecting a total of nearly 900 submissions to TVCG by the end of 2013. A total of 137 articles were published in the first 10 regular issues with 1,769 printed pages, and the VR and VIS special issues containing 21 and 101 conference papers, respectively. All submissions in both special issues went through a rigorous two-round journalquality review process. Practically all the 2012 papers have also been decided. From the 293 regular submissions (including 20 extended versions of Best Papers from several top venues in graphics and visualization), 76 regular papers and all 20 special section papers were eventually accepted; 86 out of 333 SciVis plus InfoVis conference submissions were published in the VIS special issue. TVCG continues to offer authors a remarkably effi cient processing of submitted manuscripts: The average time from submission to fi rst decision is about three months and the average time from submission to publication as a preprint in the digital library is about seven months. Its 2012 impact factor is 1.895 with the largest number of total publications appeared two years prior. During 2013, the authors of TVCG regular papers were invited to give an oral presentation of their recent work at TVCG’s partner conferences. A total of 35 TVCG papers were presented at the IEEE Virtual Reality Conference, ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games, ACM SIGGRAPH/Eurographics Symposium on Computer Animation, Pacifi c Graphics, and IEEE VIS 2013.