Grid 2.0: Collaboration and Sharing on the Grid

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$99,683.00
Award Year:
2009
Program:
SBIR
Phase:
Phase I
Contract:
DE-FG02-09ER85398
Agency Tracking Number:
91455
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Galois, Inc.
421 SW Sixth Avenue, Suite 300, Portland, OR, 97204
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
098009918
Principal Investigator:
Donald Stewart
Dr.
(503) 626-6616
dons@galois.com
Business Contact:
Jodee LeRoux
Dr.
(503) 626-6616
jodee@galois.com
Research Institution:
n/a
Abstract
Grid computing makes significant computational and data resources accessible to distributed teams of scientific researchers. In doing so, it also poses a challenge: how best to apply social and collaboration software techniques to improve the efficiency of collaboration between distributed teams working on grid systems. In recent years, new social software technologies have produced breakthroughs in improving the effectiveness of collaboration online. Rather than focusing only on the transfer of information, these technologies enable collaboration on the construction of shared results, while participants still work in a distributed manner. This project will develop interfaces and components to allow social software to operate directly on the data grid, making tagging, social bookmarking, and recommendations available to grid users. Such a system would allow scientists to analyze grid-produced data in a ¿social¿ manner. They could tag objects, bookmark them, and recommend them to colleagues. Commercial Applications and other Benefits as described by the awardee Grid computing is inherently social in the sense of involving multiple, loosely connected parties. Technology that enhances such social collaboration in the area of large datasets would be relevant to industrial and academic scientists. Other beneficiaries include professionals in the intelligence community that need to collaborate on raw intelligence data

* information listed above is at the time of submission.

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