Next Generation Data Base Modeled on Human Neurological Processes

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-07-M-0059
Agency Tracking Number: N062-159-0282
Amount: $99,589.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solicitation Year: 2006
Solicitation Topic Code: N06-159
Solicitation Number: 2006.2
Small Business Information
APPLIED TECHNICAL SYSTEMS, INC.
3505 NW Anderson Hill Rd, Suite 200, Silverdale, WA, 98383
DUNS: 004821021
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jon Larson
 Senior Software Engineer
 (360) 698-7100
 jonathan.larson@intelligentdiscover
Business Contact
 Carey Kolb
Title: Director of Operations
Phone: (360) 698-7100
Email: carey.kolb@intelligentdiscovery.com
Research Institution
N/A
Abstract
Current data mining and data analysis applications are designed primarily to address commercial business intelligence requirements. “Business Intelligence (BI) applications include the activities of decision support systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and data mining.” Conventional RDBMS-based BI applications are records-based, transaction oriented, and demand massive resource overhead for table joins and index management. Because relational database management systems (RDBMS) have established themselves as the primary standard for data storage, they have inadvertently become the foundation for data mining. The objective of this SBIR is to develop a novel cell-based approach to database design. This would enable the data model to store, process, and manipulate data much like the human brain, thereby permitting more effective and flexible use of the database and the underlying data. Performance gains are possible with cell based indexing which captures, aggregates, and handles data in native “cellular format” cells vice traditional indexes. Additionally, cellular database techniques facilitate “value pooling,” a dimension that aggregates clusters of cell “associations.” Entity relationship of “link cells” provides a powerful link analysis and knowledge discovery function, and opens the possibility of further advances in innovative data analysis capabilities.

* information listed above is at the time of submission.

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