Project Lead: Aaron Marburg, Applied Physics Laboratory
eScience Liaisons: Bernease Herman and Valentina Staneva
The publicly available data generated by CamHD have enormous scientific potential, with the capacity to support a wide range of geological, biological, hydrological, and oceanographic investigations using image analysis methods. However, the large size of the video archive and the lack of co-located computing infrastructure at the CI constitute a significant barrier to CamHD science. For end users, downloading this immense dataset for local analysis represents a significant burden in terms of time, bandwidth, and data storage costs. To fully realize the potential of the CamHD system for long-time-series investigations using image analysis, a co-located storage and computing solution must be developed.
