Automated Portfolio Data Mining

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Project Participants: Advanced Technology International (ATI)

Project Start: December 2020

The ability to leverage information from past Research and Development (R&D) is essential in optimizing efforts, reducing timeframes to achieve desired outcomes, and minimizing rework and duplication of efforts. However, project related information from past NSAM and NSRP projects is spread across multiple disparate data sources and locations without a central location to search from. The objective of this project is to evaluate the functionality and potential benefit of data mining software applications to determine if they provide the functionality required for use as a central searching platform for indexing disparate data sources. The project will reach out to research centers, such as John Hopkins University and the Joint Artificial Intelligence Center (JAIC), and investigate via a market survey, to determine the current capabilities with regard to database connectivity, indexing, and searching without creating or hosting a new centralized database. Other capabilities will be investigated such as web crawling functionality to obtain project related data from public or private facing websites. This project will result in a detailed study on the current state of each identified application, graded on required criteria, and identify additional development efforts when possible.

The Automated Portfolio Data Mining Analysis project evaluated COTs/GOTs software product’s capabilities to connect disparate Naval Shipbuilding and Advance Manufacturing Center (NSAM) and National Shipbuilding Research Program (NSRP) project data sources and provide a central location where users can search, obtain, and display the portfolio data. The project team has installed, AFRL’s HyperThought software applications on a secure sandbox environment and attempted to connect multiple data sources; internal Plone data, internal SharePoint data, internal file repository, and an external data source via public facing website via a web crawler. The project team analyzed the capabilities and security risks of each application against a developed requirements document, grade on by required criteria, and provided ONR a recommendation on how to proceed with follow-on effort.

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