JCJC SIMI 2 - JCJC - SIMI 2 - Science informatique et applications

Connect, Collaborate, Analyze : From Individual Work to Collaborative Visual Analytics – FITOC

FITOC : From Individual to Collaborative Work

Connect, Collaborate, Analyze: From Individual Work to Collaborative Visual Analytics

Research challenges and goals

The goal of our research is to devise technologies which best enable face-to-face collaborative data analysis as an integral part of the continuum between single-user asynchronous and multi-user synchronous work. The main challenge of this research is the lack of design considerations on how data analysis phases of individual and collaborative work relate to each other. We need to understand when people switch between both types of analysis, for which types of questions and tasks, what types of data analysis collaborations they want to engage in, and how these can be best supported by technology.

We will use a combination of software design and pre- and post-design evaluations. We will conduct fundamental research in several areas related to the design of visualization tools and workspaces. Specifically we will address: infrastructure challenges which will deliver results on the underlying software and algorithms necessary to bridge between single-user to multi-user visualization tools, interaction challenges which will deliver results on interaction mechanisms for the shared workspaces to give each individual team member effective access to shared resources while dropping in- and out of a collaborative workspace, visualization challenges which will deliver results on the changes necessary to visualization for the collaborative workspace. Finally, our work on evaluation challenges will provide results on how to best evaluate tools across the boundary of individual to joint work – an evaluation topic which has so far received no previous research attention in the visualization community.

Our results will include: a) clear guiding design considerations for developing visualizations systems which are useful and usable for both individual as well as collaborative work, b) practical tools on which to build for promoting collaborative visualization use in a variety of application domains, c) results from validation and iterative improvement of the techniques which are meant to bridge between individual and collaborative work.

Research on the support for collaboration in visual analytics is still in its infancy and has been named one of the grand research challenges in the field of visual analytics. Currently no dedicated research exists, to our knowledge, which addressed the space between individual and collaborative work for data analysis. This proposal is one promising step in this direction and will help the field’s knowledge in this area to mature.

The work has so far led to one international conference publication, one workshop publication, as well as one prototype demonstration at an international conference.

Making sense of large and complex data sources is becoming increasingly essential in many different domains. The problem is increasing to an extent that individuals can no longer find all answers or solutions in these datasets alone but have to collaborate in order to increase the effectiveness, efficiency, and quality of their work. This proposal focuses around visualization research and the notion of data analysis as a social process. Vision is our most dominant sense and a large part of our brain is devoted to processing visual information. Visualizations of information are, thus, powerful instruments to help us view, explore, and understand data, validate results, and explain complex relationships. Social exchanges around data are fairly common, people gather information together, discuss it, share it, form joint decisions based on it, or present it to others. Ultimately, supporting this collaborative nature of data analysis in new technology contexts can empower humans to more effectively and intuitively make use of information whenever and wherever it is needed the most.

Yet, currently, a large amount of data analysis work is conducted by individuals with few visualization tools that can help them to analyze data in face-to-face meetings. Those tools that do exist provide no easy solution to bridge the gap between individual and team work situations. In order to make collaboration effortless and worth undertaking, individuals have to be able to fluidly switch in and out of collaboration with others, to bring their own data, its visual representations, as well as all data modifications and annotations to a shared meeting where both data and representations can not only be presented but also interacted with, modified, and further analyzed together with others.

In this project, we address this research challenge. The project addresses fundamental problems of technological infrastructure and the design of data representation and interaction to build a bridge between individual and team work for visual data analysis. The goal is to improve the effectiveness and efficiency of experts moving in and out of face-to-face computer-supported collaborative data analysis to most effectively make sense of, explore, and analyze their data. The goals is to empower information workers to make use of the potential of both, their current single-user workspaces and technology-enhanced collaboration spaces.

We will tackle this challenge through a stream of interconnected research modules, starting from fundamentally extending visualization toolkits for collaborative work and researching the necessary interaction and visualization mechanisms that will allow for a seamless and effortless setup of face-to-face data analysis with visualizations. We will provide both fundamental and applied contributions and evaluate our work in order to ensure its validity.

This project will build upon our rich hardware setting – featuring the large Wall-Size display WILD [1] and several tabletops – and our connections to world-leading groups working on that domain: the Canadian SurfNet network (http://www.nsercsurfnet.org/), the VACCINE Visual Analytics center at Purdue (http://www.purdue.edu/dp/vaccine/) and the Microsoft Research VIBE team (http://research.microsoft.com/en-us/groups/vibe/). It will be conducted at the AVIZ INRIA Research Team which is a leading French group in the Visual Analytics area, specialized in toolkits for information visualization and large-scale visual analytics applications.

Project coordination

Petra ISENBERG (INRIA Saclay) – petra.isenberg@inria.fr

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


INRIA Saclay-Île de France / EPI AVIZ INRIA Saclay

Help of the ANR 229,644 euros
Beginning and duration of the scientific project: - 48 Months

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