SAGE2: A New Approach for Data Intensive Collaboration Using Scalable Resolution Shared Displays

Marrinan, Thomas; Aurisano, Jillian; Nishimoto, Arthur; Bharadwaj, Krishna; Mateevitsi, Victor; Renambot, Luc; Лонг, Линг; Johnson, Andrew; Leigh, Jason

doi:10.4108/icst.collaboratecom.2014.257337

Cited by 94 publications

(42 citation statements)

References 19 publications

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“…The conceptually closest work to ours is SAGE2 [19], which shares many of the design objectives with our framework. The creators of SAGE2 state that among their key objectives are (1) integration of multi-user applications, (2) enhanced real-time distance collaboration, and (3) a reduced barrier to entry.…”

Section: Discussionmentioning

confidence: 99%

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Collaborative distributed cognition using a seamless desktop infrastructure

Geymayer

Schmalstieg

2016

2016 Workshop on Immersive Analytics (IA)

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Figure 1: The tiled display in our visualization laboratory is build from 24 monitors (50" diameter, 1920x1080 resolution.) ABSTRACTInexpensive displays make large, tiled displays attractive for visual analysis and collaborative investigation. Especially in multi-user environments, the increased space allows to better organize the findings and results and, therefore, helps to improve collaboration. One important requirement is that all users can navigate seamlessly on the whole display space, while employing the standard software they are familiar with. In this paper, we present a seamless desktop infrastructure for distributed cognition and collaboration. Our infrastructure only uses standard hardware and software. By choosing a minimally invasive, web-centric approach, we can integrate existing web applications and visual analysis software with little or no effort into our system. We can even leverage existing synchronization mechanisms built into many web applications today.

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Section: Discussionmentioning

confidence: 99%

“…More recent systems, like Panelrama [33] and PolyChrome [3], allow splitting the user interface across multiple devices, but require a deeper integration with the individual applications. SAGE2 [19] also makes heavy use of modern web technologies, and provides a multi-user interaction capable windowing system running in the browser.…”

Section: Related Workmentioning

confidence: 99%

Collaborative distributed cognition using a seamless desktop infrastructure

Geymayer

Schmalstieg

2016

2016 Workshop on Immersive Analytics (IA)

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“…Scalable Amplified Group Environment (SAGE2) is an open-source visualization middleware developed by EVL (Electronic Visualization Laboratory) at the University of Illinois at Chicago [6]. SAGE2 has three major features.…”

Section: Scalable Amplified Group Environment (Sage2)mentioning

confidence: 99%

“…Visualization middleware and applications have various kinds of packages such as Scalable Amplified Group Environment (SAGE2) [6], ParaView [7] and COllaborative VIsualization and Simulation Environment (COVISE) [8], each of which depends on the different particular versions of system libraries and graphic libraries to use a hardware acceleration with GPU. The conflicts of library versions among different visualization middleware and applications can cause trouble in the operation of a TDW.…”

Section: Introductionmentioning

confidence: 99%

A Switching Mechanism of Visualization Middleware and Application Using Docker

Ishida¹,

Kido²,

Date³

et al. 2017

Proceedings of International Symposium on Grids and Clouds (ISGC) 2017 — PoS(ISGC2017)

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A Tiled Display Wall (TDW) is one of the visualization systems, which is appropriate for visualization of large-scale data. Although the scientific area needs an easier and cheaper TDW than the current one, a large-scale TDW is still too expensive to build individually. Given that, it is advisable to share the large-scale TDW among scientists who need to use it. To share a TDW, a variety of visualization middleware and applications should be installed on it because scientists use a different one of them depending on their data and purpose. However, there is a problem that it is difficult to coexist multiple visualization middleware and applications on a TDW because there are conflicts of library versions among them. To solve this problem, we propose a switching mechanism of visualization middleware and application using Docker. By using the proposed mechanism, administrators just need to deploy Docker images with visualization middleware and applications on a TDW, and then users can use them without the conflict problem. In the evaluation, the proposed mechanism is shown to have practically and scalability.

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“…R, Matlab) and data visualization tools have been developed to assist data scientists during the EDA process, but are mostly desktop-based and do not provide support for collaborative analysis. Over time, researchers have repeatedly tried to propose immersive technologies (such as CAVE systems [23][24][25]51], powerwalls [52,53], and virtual and augmented reality headsets) as a possible solution for specific data science tasks, defining a research area known as Immersive Analytics [19,54]. The technological improvements and hardware commoditization of head-mounted-displays (HMDs) of the past few years have reignited interest in applying these devices to domains such as EDA, and a few companies have even proposed some first VR-based commercial solutions [1,5].…”

Section: Introductionmentioning

confidence: 99%

Immersive Insights: A Hybrid Analytics System forCollaborative Exploratory Data Analysis

Cavallo¹,

Dholakia²,

Havlena³

et al. 2019

25th ACM Symposium on Virtual Reality Software and Technology

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Figure 1: Immersive Insights is a collaborative, hybrid analytics system for exploratory data analysis. The application, implemented in a Dataspace environment [18], leverages multimodal interaction and combines the use of technologies such as 1) high-resolution movable screens to visualize statistical information, 2) a central projection table providing an overview of the current analysis, and 3) an augmented reality view to visualize and interact with high-dimensional data. ABSTRACTIn the past few years, augmented reality (AR) and virtual reality (VR) technologies have experienced terrific improvements in both accessibility and hardware capabilities, encouraging the application of these devices across various domains. While researchers have demonstrated the possible advantages of AR and VR for certain data science tasks, it is still unclear how these technologies would perform in the context of exploratory data analysis (EDA) at large. In particular, we believe it is important to better understand which level of immersion EDA would concretely benefit from, and to quantify the contribution of AR and VR with respect to standard analysis workflows.In this work, we leverage a Dataspace reconfigurable hybrid reality environment to study how data scientists might perform EDA in a co-located, collaborative context. Specifically, we propose the design and implementation of Immersive Insights, a hybrid analytics system combining high-resolution displays, table projections, and augmented reality (AR) visualizations of the data.We conducted a two-part user study with twelve data scientists, in which we evaluated how different levels of data immersion affect the EDA process and compared the performance of Immersive Insights with a state-of-the-art, non-immersive data analysis system.

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SAGE2: A New Approach for Data Intensive Collaboration Using Scalable Resolution Shared Displays

Cited by 94 publications

References 19 publications

Collaborative distributed cognition using a seamless desktop infrastructure

Collaborative distributed cognition using a seamless desktop infrastructure

A Switching Mechanism of Visualization Middleware and Application Using Docker

Immersive Insights: A Hybrid Analytics System forCollaborative Exploratory Data Analysis

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