摘要: We have been studying DoD acquisition decision-making since 2009. The U.S. DoD acquisition process is extremely complex. There are three key processes that must work in concert to deliver capabilities: determining warfighters' req... 展开 We have been studying DoD acquisition decision-making since 2009. The U.S. DoD acquisition process is extremely complex. There are three key processes that must work in concert to deliver capabilities: determining warfighters' requirements/needs, the DoD budget planning, and the procurement of final products. Each process produces large amounts of information (Big Data). There is a critical need for automation, validation, and discovery to help acquisition professionals, decision-makers, and researchers understand the important content within large data sets and optimize DoD resources throughout the processes. Lexical Link Analysis (LLA) can help, by applying automation to reveal and depict--to decisionmakers--the correlations, associations, and program gaps across all or subsets of acquisition programs over many years. This enables strategic understanding of data gaps and potential trends, and can inform managers where areas might have higher program risk and how resource and big data management might affect the desired return on investment among projects. In this paper, we describe new developments in analytics and visualization, how LLA is adaptive to Big Data Architecture and Analytics (BDAA), and needs for Big Acquisition Data used in Defense Acquisition Visibility Environment (DAVE). 收起