Collaboration is an effective approach to problem solving. Most large-scale scientific investigations are highly interdisciplinary and collaborative, with project investigators often geographically distributed. For example, ITER 1 is a joint international research and development project that aims to demonstrate the scientific and technical feasibility of fusion power. The partners in the project are distributed in more than ten countries, and it is imperative that they share their creations and findings since greater advances are only made with collective efforts. Similarly, I am participating in the U.S. Department of Energy's SciDAC (Scientific Discovery through Advanced Computing) program 2, which sponsors a dozen high-profile science projects. Each of the project teams involves researchers from several different universities and national laboratories. Clearly, there is an explicit need to provide support for collaborative work. How can these researchers effectively share their data, problem solving strategies, and research findings without time and place constraint? The answer is web-based collaboratories, which have been created for many major science projects. However, most of these collaboratories are simply data repositories with web interfaces. For instance, users do not get to see the associations between data and users, which are as valuable as the data itself. These associations can be large and very complex, and thus hard to comprehend. Visualization can play a key role in both knowledge discovery and managing potentially complex and high-dimensional collaborative workspace. I have been thinking about how to address the need to support collaborative data analysis and visualization, and how to direct the visualization research community towards the development of such needed technologies. I am going to describe some of the ongoing efforts to facilitate sharing visualization resources that will provide the eventual support for the kind of collaborative workspace I have in mind.
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Creating a collaborative space to share data, visualization, and knowledge
Ma, Kwan-Liu
Follow ACM SIGGRAPH Computer Graphics
, Volume 41 (4)
Association for Computing Machinery – Nov 1, 2007
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