Calendar

When:
February 17, 2015
Location:
Online
Details:

Brown Dog: A search engine for the other 99 percent

Date:     Tuesday, February 17, 2015

Time:    1:00 to 2:30 pm (EST)

 Remote participation is available. Instructions to join our meeting remotely using WebEx are at the end of this message.

Abstract

The persistent growth of “Big Data” presents challenges that include not only the large quantities of digital data produced, but also the large variety of the data. This variety presents a significant challenge to ensuring future scientific reproducibility, especially in what is often referred to as “long-tail” data. Inadequate curation of data, for example, can result in undocumented representations of data or many different representations for similar data types. For future users, without the understanding provided by the original data creator or software, this data becomes difficult or impossible to explore. Another reoccurring problem for use of big data is difficulty in searching, finding, filtering, and comparing data. Without a consistent and uniform index over all the data, or at least associated metadata, such actions become prohibitively difficult.

 

Brown Dog addresses these and similar considerations through the development of a set of services for data format conversion, metadata extraction from existing data, and the generation of indexes over uncurated collections of data. Brown Dog provides the framework for an extensible suite of new and existing tools working together to accomplish these tasks. Domain researchers using the scalable and usable Brown Dog system will be able to apply the whole suite of tools to data collections in order to find and “unlock” previously inaccessible data. During the talk we will go over the Brown Dog services and their constituent components, as well as discuss the projects’ three scientific use cases and a general public use case that will also contribute to the sustainability of Brown Dog.

About The Speaker

Kenton McHenry

Senior Research Scientist

National Center for Supercomputing Applications

University of Illinois at Urbana-Champaign

Kenton McHenry received a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 2008 after completing a B.S. in Computer Science from California State University of San Bernardino. Kenton's background is in computer vision and artificial intelligence having done work in the areas of image segmentation, object/material recognition, and 3D reconstruction. He is currently a Senior Research Scientist at the National Center for Supercomputing Applications (NCSA) where he co-leads the Innovative Software and Data Analysis Division (ISDA) and holds an Adjunct Assistant Professor position in the Department of Computer Science at the University of Illinois at Urbana-Champaign.  Kenton has applied his experience in computer vision, AI, and machine learning towards research and development in software cyberinfrastructure for digital preservation, auto-curation, and the providing of access to contents in large unstructured digital collections (e.g. image collections).  Kenton serves as PI/Co-PI on a number of awards from a variety of agencies/organizations ranging from NSF, NIH, NEH, and private sector partners.  Kenton currently serves as the Project Director and PI of NSF CIF21 DIBBs - Brown Dog where his team works on means of making data agnostic to the file formats in which they are stored and providing general purpose easy to use tools to access uncurated collections by the automatic extraction of metadata and signatures from raw file contents.

Instructions to join our meeting remotely using WebEx

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