A General Purpose Toolkit for Exploiting Network Data in Diverse Applications Navy SBIR FY2008.1 Sol No.: Navy SBIR FY2008.1 Topic No.: N08-081 Topic Title: A General Purpose Toolkit for Exploiting Network Data in Diverse Applications Proposal No.: N081-081-0633 Firm: Stottler Henke Associates, Inc. 951 Mariner''''s Island Blvd., STE 360 San Mateo, California 94404 Contact: Terrance Goan Phone: (206) 545-1478 Web Site: www.stottlerhenke.com Abstract: Stottler Henke proposes to develop a generalized toolset around a new and innovative network data encoding strategy with the goals of: (1) increasing the scalability of network analysis and visualization tools; (2) fundamentally improving the intelligibility of network models and thereby increasing the accessibility of network science to the broader research community; and (3) providing a more faithful representation of reality in situations where generic modeling approaches may obscure or misrepresent system dynamics and engineered functions. The proposed system, called NetSet, will be comprised of three primary components. First, it will provide the capability to automatically identify recurring and meaningful structures (e.g., Motifs) within complex networks in order to improve the scalability, accuracy, and exploitability of network models. Second, NetSet will move beyond the typical unimodal (i.e., nodes and links) representation and capture broader descriptive features. Last, the proposed system will bridge the current gap between traditional network science and Statistical Relational Learning so as to support a broader range of predictive analysis applications. Our Phase I prototyping will prove the feasibility of our approach and set the stage for the complete implementation of NetSet in Phase II and its subsequent commercialization. Benefits: Complex multi-dimensional networks come up in many contexts: intelligence analysis, computer networking, sociology, fraud detection, epidemiology, biology, criminal investigations, viral marketing, etc. Unfortunately our ability to collect electronic data and information regarding these networks far outstrips our ability to understand them. We see a very significant opportunity to extend our current products with the proposed technology so as to greatly improve the accessibility of complex network modeling and analysis. More specifically, the integration of the multidimensional network visualization system within a comprehensive suite of intelligence gathering and analysis tools will have substantial value to the US military and intelligence community, law enforcement, and a variety of other organizations interested in a diverse set of applications ranging from large computer network monitoring to social network analysis. Return