The National Science Foundation recently awarded over $10 million dollars to the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. The award will be applied towards research of structuring large collections of data such as images, audio, and video, in which the project has been named ‘Brown Dog’. While it seems popular search engines like Google or Yahoo already do this, they are text based or leverage text metadata. Brown Dog aims to improve on current metadata technologies, which not only leave behind less popular or peculiar file formats, but does not easily provide the ability to search and use contents of digital data.
Brown Dog is aimed at taking un-curated data and organizing it for scientific purposes. The group involved in this project are from scientific departments at U of I. Kenton McHenry, who is part of NCSA’s Image and Spatial Data Analysis Division, is the Principal Investigator on the project. Jong Lee, Praveen Kumar, Barbara Minsker, and Michael Dietze are listed as Co-Principal Investigators on the project. As technologies evolve and change, the proven scientific methodology of reproducing results becomes more challenging in this environment.
Even though this NSF grant and project Brown Dog are focusing on the sciences, a breakthrough in this area would have profound implications in the big data movement. One goal of the project is to automatically tag internal data with metadata, even if the data cannot be touched.
NCSA has a similar project called CompGen, in which they are participating with the University of North Carolina Chapel Hill and Boston University, along with 15 companies. Researchers are developing hardware and software to work and understand data from the human genome.