A Web Service Implementation for Large-Scale Automation, Visualization, and Real-Time Program-Awareness Via Lexical Link Analysis
Abstract
DoD acquisition is an extremely complex system, comprised of myriad stakeholders, processes, people, activities, and organizational structures. Processes within this complex system are encumbered by the continuous creation of large amounts of unstructured and unformatted acquisition program data, which is narrowly useful, yet difficult to aggregate across the "enterprise." Acquisition analysts and decision-makers must analyze this available data to obtain a complete and understandable picture. This is a kind of systems non-congruence which has been difficult to overcome. For those embedded within the complexities of the acquisition community, this effort represents a daunting, if not impossible, task. We will apply a data-driven automation system, namely, Lexical Link Analysis (LLA), to facilitate acquisition researchers and decision-makers to recognize important connections (concepts) that form patterns derived from dynamic, ongoing data collection. The LLA technology and methodology is used to uncover and display relationships among competing programs and Navy-driven requirements. In the past year, we tested our method using samples of acquisition data for validity. LLA was demonstrated to discover statistically significant correlations, and automatically extract the links that might require expensive manpower to perform otherwise. This year, we started to develop LLA from a demonstration to an operational capability and facilitate a wider range of acquisition research applications. The resulting methodology can facilitate real-time awareness, reduce the workload of decision-makers, and make a profound impact on the long term success of acquisition strategies by revealing the current status of acquisition programs, and connections within and external to contributing or competing interests, as well as inform potential strategic choices available to decision-makers.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 27, 2011
- Accession Number
- ADA633873
Entities
People
- Douglas J. MacKinnon
- Shelley P. Gallup
- Ying Zhao
Organizations
- Naval Postgraduate School