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The practice of extracting knowledge from large volumes of video data suffers from a problem of variety. Security, military, and commercial identification and retrieval are well-traveled paths for identifying very particular objects or people found in recorded footage, yet there are extremely few established technology solutions and use cases for understanding what large-scale video collections can help us discover about contemporary culture and history. This dearth is not due to a lack of imagination on the part of researchers; rather, we contend, in order to grow a common set of instruments, measures, and procedural methods, there is a need for a common gateway into content and analytics for cultural and historical experts to utilize. The Video Analysis Tableau (VAT), formerly the LSVA, is a research project aimed at establishing a software workbench for video analysis, annotation, and visualization, using both current and experimental discovery methods and built on the Medici framework/interface. The VAT employs a host of algorithms for machine reading, in addition to spaces for user generated tagging and annotation; it is currently being expanded into a gateway project in order to foster a strong community of practice that includes researchers in a variety of disciplines.
