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GCN : November and December 2014
Unstructured data is the bane of re- searchers everywhere. Although casual Googlers may be frustrated by not be- ing able to open online les, research- ers often need to dig into data trapped in outdated formats and uncurated collections with little or no metadata. And according to IDC, up to 90 percent of big data is "dark," meaning the contents of such les cannot be easily accessed. Thus, the Brown Dog solu- tion to a long-tail problem. Led by Kenton McHenry and Jong Lee of the Image and Spatial Data Analysis division at the National Center for Supercomputer Applications (NCSA) at the University of Illinois at Urbana-Champaign, Brown Dog seeks to develop a service that will make un- curated data accessible. "The information age has made it easy for any- one to create and share vast amounts of digital data, including unstructured collections of images, video and audio as well as documents and spreadsheets," said McHenry. "But the ability to search and use the contents of digital data has become exponentially more dif cult." Brown Dog is working to change that. Recipients in 2013 of a $10 mil- lion, ve-year award from the Na- tional Science Foundation, the UI team recently demonstrated two services to make the contents of uncurated data collections accessible. The rst, called Data Access Proxy (DAP), transforms unreadable les into readable ones by linking together a series of computing and translational operations behind the scenes. Similar to an Internet gateway, the con gura- tion of the DAP would be entered into a user's machine settings. Thereafter, data requests over HTTP would rst be examined by the proxy to determine if the native le format is readable on the client device. If not, the DAP would be called in the background to convert the le into the best possible format readable. The second tool, the Data Tilling Service (DTS), lets individuals search collections of data, using an existing le to discover similar les in the data. For example, while browsing an online image collection, a user could drop an image of three people into the search eld, and the DTS would return images in the collection that also contain three people. If the DTS encounters a le format it is unable to parse, it would use the DAP to make the le accessible. Rather than starting from scratch and constructing a single all-encompassing piece of software, the NCSA team is building on previous software develop- ment work. The project aims to bring together every possible source of automated help already in existence. By patching together such components, they plan to make Brown Dog the "super mutt" of software. "Brown Dog today is developing a 'time machine' set of cyberinfrastructure tools, software and services that respond to the long- standing aspiration of many scienti c, research and educational communities to effectively access, share and apply digital data and infor- mation originating in diverse sources and legacy environ- ments in order to advance contemporary science, research and education," said Robert Chadduck, the program director at NSF who oversees the award. Brown Dog isn't only useful for search- ing the deep web, either. McHenry said the Brown Dog software suite could one day be used to help individuals man- age ever-growing collections of photos, videos and unstructured/uncurated data on the web. "Being at the University of Illinois and NCSA many of us strive to create something that will live on to have the broad impact that the NCSA Mosaic web browser did," McHenry said, referring to the world's rst web browser, which was developed at NCSA.• Brown Dog digs into the deep, dark web GCN NOVEMBER/DECEMBER 2014 • GCN.COM 5 Brown Dog's deep web search system.