Collaborative Research: ITR: A Digital Video Collaboratory to Integrate IT Innovations in Video Analysis, Sharing and Collaboration into Scientific Research Communities

Stanford University, Stanford CA

Investigators

Abstract

The proposed effort will build upon prior work by participating institutions in audio and video capture, analysis and collaboration, allowing each institution to make progress more quickly by leveraging each other's respective strengths, capabilities and prior work. The project brings together NSF-funded efforts involving multimedia data in the human sciences: the DIVER project housed at Stanford University, and the TalkBank Project, housed at CMU and the University of Pennsylvania, as well as NSF Middleware and Grid projects. The proposed project will adopt a two-track research approach to designing and implementing the Collaboratory. The first project track is to develop a virtual video repository and video analysis community portal. The second track will produce an open community toolkit that greatly expands generality and capabilities for video analysis, video input and output. In addition to these goals of moving from local to distributed users, tools and data will evolve in an ongoing process of user testing, piloting, and software packaging, involving the community and refining the tools based on their experiences. Project results at each interim milestone will be disseminated broadly for enhancing scientific and technological understanding, especially to conferences and journals and complemented by an open website for sharing ongoing research, technical developments, technical reports and software releases to be downloaded to user communities. Video Collaboratory toolkits will be made available to participating institutions with efforts made to spur adoption that will facilitate multiple communities using collaborative commentary around video. The initial focus of our project is the human sciences, with the aim of leveraging video records to enhance the learning sciences, education, teaching and training. We also expect that video application and infrastructure work can provide significant support to the physical sciences, since video is an important data type for scientific visualization and primary empirical data, and several Grid initiatives use video databases integrally. We anticipate producing open-source video software that can be utilized in the current Grid and Middleware platform initiatives. This could enable a new primary software layer, a set of standards for video analysis and collaboration middleware, and the potential for a substantial broader impact as an outcome of this work.