Computer graphics has a long history. Industrial organizations and laboratories drove significant improvements as they adapted and assembled basic capabilities into complex interactive applications. Of particular concern in the early days was providing interactive 3-D applications for computer-aided design and engineering. This article describes the experience of two early industry practitioners who built successful 1970s interactive 3-D systems.

Parametric modeling systems are widely used in architectural design.Their use for designing complex built environments raises important practical challenges when composed by multiple people with diverse interests and using mostly unverified computational modules.Through a case study, we investigate possible concerns identifiable from a real-world collaborative design setting and how such concerns can be revealed through interactive data visualizations of parametric models.We then present our approach for resolving these concerns using a design analytic workflow for examine their reliability and validity.We summarize the lessons learnt from the case study, such as the importance of an abundance of test cases, reproducible design instances, accessing and interacting with data during all phases of design, and seeking high cohesion and decoupling between design geometry and evaluation components.We suggest a systematic integration of design modeling and analytics for enhancing a reliable design decision-making.

Technology transfer is often focused on how to get novel technology transferred into an industrial using group or company. We focus in this paper on the target of the process and present guidelines which can help assess the likelihood of a successful transfer.

This SpringerBrief explains how efficient and effective interactive visualization and visual analytics tools can enable the significance of the data to be understood, particularly in time-critical situations, such as weather forecasting, the stock exchange, and security threats.

Large, high-resolution displays (LHRDs) have been shown to enable increased productivity over conventional monitors. Previous work has identified the benefits of LHRDs for Visual Analytics tasks, where the user is analyzing complex data sets. However, LHRDs are fundamentally different from desktop and mobile computing environments, presenting some unique usability challenges and opportunities, and need to be better understood. There is thus a need for additional studies to analyze the impact of LHRD size and display resolution on content spatialization strategies and Visual Analytics task performance. We present the results of two studies of the effects of physical display size and resolution on analytical task successes and also analyze how participants spatially cluster visual content in different display conditions. Overall, we found that navigation technique preferences differ significantly among users, that the wide range of observed spatialization types suggest several different analysis techniques are adopted, and that display size affects clustering task performance whereas display resolution does not.

The 2016 Visualization Technical Achievement Award goes to David Ebert in recognition of foundational work in visual analytics, both through development of fundamental predictive techniques and as Director of the Purdue/DHS Visual Analytics Center of Excellence.

With many new members joining the CG&A editorial board over the past year, and with a renewed commitment to not only document the state of the art in computer graphics research and applications but to anticipate and where possible foster future areas of scientific discourse and industrial practice, CG&A asked its editorial and advisory council members about where they see their fields of expertise going. The answers compiled here aren't meant to be all encompassing or deterministic when it comes to the opportunities computer graphics and interactive visualization hold for the future. Instead, the goal is to give a more in-depth introduction of members of the editorial board to the CG&A readership and encourage cross-disciplinary discourse toward approaching, complementing, or disputing the visions laid out in this compilation. Here's what the CG&A editorial and advisory council members had to say.

Analysts need to keep track of their analytic findings, observations, ideas, and hypotheses throughout the analysis process. While some visual analytics tools support such note-taking needs, these notes are often represented as objects separate from the data and in a workspace separate from the data visualizations. Representing notes the same way as the data and integrating them with data visualizations can enable analysts to build a more cohesive picture of the analytical process. We created a note-taking functionality called CZNotes within the visual analytics tool CZSaw for analyzing unstructured text documents. CZNotes are designed to use the same model as the data and can thus be visualized in CZSaw's existing data views. We conducted a preliminary case study to observe the use of CZNotes and observed that CZNotes has the potential to support progressive analysis, to act as a shortcut to the data, and supports creation of new data relationships.

We introduce a propagation-based parametric symbolic model approach to supporting analytic provenance. This approach combines a script language to capture and encode the analytic process and a parametrically controlled symbolic model to represent and reuse the logic of the analysis process. Our approach first appeared in a visual analytics system called CZSaw. Using a script to capture the analyst’s interactions at a meaningful system action level allows the creation of a parametrically controlled symbolic model in the form of a Directed Acyclic Graph (DAG). Using the DAG allows propagating changes. Graph nodes correspond to variables in CZSaw scripts, which are results (data and data visualizations) generated from user interactions. The user interacts with variables representing entities or relations to create the next step’s results. Graph edges represent dependency relationships among nodes. Any change to a variable triggers the propagation mechanism to update downstream dependent variables and in turn updates data views to reflect the change. The analyst can reuse parts of the analysis process by assigning new values to a node in the graph. We evaluated this symbolic model approach by solving three IEEE VAST Challenge contest problems (from IEEE VAST 2008, 2009, and 2010). In each of these challenges, the analyst first created a symbolic model to explore, understand, analyze, and solve a particular subproblem and then reused the model via its dependency graph propagation mechanism to solve similar subproblems. With the script and model, CZSaw supports the analytic provenance by capturing, encoding, and reusing the analysis process. The analyst can recall the chronological states of the analysis process with the CZSaw script and may interpret the underlying rationale of the analysis with the symbolic model.

Successful joint industry-university projects are as rewarding as they are rare. Even more rare is the effective transfer of technology from an academic research laboratory to an industrial application. Having the transfer take less than 3 years is rarest of all. This paper describes a case study where a successful joint industry-university project resulted in a considerable reduction in the time to move a new form of technology - Visual Analytics - from university laboratories into multiple industrial uses. Significant events and lessons learned along the way are described from both an industrial and an academic perspective.

Investigative analysts need overviews of large amounts of data, which is a challenge when working with non-numerical data such as document collections. We present Semantic Zoom View (SZV), an interactive document collection visualization implemented as part of the CZSaw visual analytics system. SZV uses a focus + context technique to provide an overview with details on demand through interactive semantic zooming. SZV lets an analyst easily and quickly see the main topics of a document collection while keeping surrounding documents visible for context. Working within a single integrated visualization, an analyst can also quickly find related documents and break a large document collection into smaller meaningful groups. SZV's focus + context technique was compared to an overview + detail version for finding answers within a document collection and results indicated its strength for maintaining visibility of a full overview when document contents are accessed.

Extracting information from text is challenging. Most current practices treat text as a bag of words or word clusters, ignoring valuable linguistic information. Leveraging this linguistic information, we propose a novel approach to visualize textual information. The novelty lies in using state-of-the-art Natural Language Processing (NLP) tools to automatically annotate text which provides a basis for new and powerful interactive visualizations. Using NLP tools, we built a web-based interactive visual browser for human history articles from Wikipedia.

The field of computer graphics combines display hardware, software, and interactive techniques in order to display and interact with data generated by applications. Visualization is concerned with exploring data and information graphically in such a way as to gain information from the data and determine significance. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. Expanding the Frontiers of Visual Analytics and Visualization provides a review of the state of the art in computer graphics, visualization, and visual analytics by researchers and developers who are closely involved in pioneering the latest advances in the field. It is a unique presentation of multi-disciplinary aspects in visualization and visual analytics, architecture and displays, augmented reality, the use of color, user interfaces and cognitive aspects, and technology transfer. It provides readers with insights into the latest developments in areas such as new displays and new display processors, new collaboration technologies, the role of visual, multimedia, and multimodal user interfaces, visual analysis at extreme scale, and adaptive visualization.

This paper describes a course on spatial thinking and communicating designed by an interdisciplinary team and offered to first-year university students. An important goal was to introduce spatial thinking while accommodating the needs of the students from diverse backgrounds, educational goals and career pathways. Students in a first-year interdisciplinary cohort of 340 represented Mechatronics Systems Engineering, Business, Interactive Arts, Communications, and Computing Science. A major feature of the course design was an integrated laboratory, which served to amplify lecture content via practicing exercises aimed at developing their abilities to think and work spatially in 2D and 3D using tools including pencil and paper, digital and physical Lego, and a computer-aided design system. We describe our course design and team-teaching processes, realities that constrained our choices, the tools we use to assist our decision making during course design and delivery, and the structure and function of the teaching team. We also present selected student artifacts to demonstrate how students learned to think spatially. We then identify lessons-learned and revision plans.

research-article Visual analytics and human-computer interaction Share on Authors: Richard Arias-Hernández Simon Fraser University Simon Fraser UniversityView Profile , John Dill Simon Fraser University Simon Fraser UniversityView Profile , Brian Fisher Simon Fraser University Simon Fraser UniversityView Profile , Tera Marie Green Simon Fraser University Simon Fraser UniversityView Profile Authors Info & Claims InteractionsVolume 18Issue 1January + February 2011 pp 51–55https://doi.org/10.1145/1897239.1897249Online:01 January 2011Publication History 5citation2,436DownloadsMetricsTotal Citations5Total Downloads2,436Last 12 Months513Last 6 weeks40 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Jim Thomas, a visionary scientist and inspirational leader, died on 6 August 2010 in Richland, Washington. His impact on the fields of computer graphics, user interface software, and visualization was extraordinary, his ability to personally change people’s lives even more so. He is remembered for his enthusiasm, his mentorship, his generosity, and, most of all, his laughter. This collection of remembrances images him through the eyes of his many friends.

CZSaw [1] is a visual analytics tool for sense-maki ng across entities, entity collections, and relations with a focus on augmenting the analysis process. It uses a variety of flexible data visualizations to represent, explore, and compute n etworks of entities and relations from different perspectives. CZSaw is designed to provide a replayable record of the anal ysis process and to generate a reusable model of the analysis lo g c, structured as a dependency graph. To support these goals, sema ntically meaningful interactions are captured into a script. Replaying this script replays the analysis process, and editing it allows fine control and reuse of the process. Specialized viewe rs are also provided for the dependency graph and for the user’ s history, to provide more visual interaction. This demo shows ho w CZSaw can be used to analyze different types of datasets ( tructured and unstructured data), as well as some strategies (e.g . divide and conquer) used on analysis tasks.