Data Management for Artificial Intelligence Machine Learning Implementation Across the Department of the Navy
Abstract
The private sector continuously harvests and curates key data and its sources so as to ensure the support and development of new operational insights, generated by leveraging data-intensive artificial intelligence machine learning (AI/ML) techniques. Industry culture affirms that all data are valued shared resources, an approach the Navy so far has failed to realize. This capstone explores the Navy's challenging task of creating data availability and quality through research, interviews, and personal expertise. Research focuses on process, technology, and governance, employing a detailed needs assessment, stakeholders' analysis, and functional design. The result is a conceptual framework for a centralized artificial intelligence library (CAIL), designed to match industry's resolute attention to data as a critical commodity. The Navy needs persistent and dynamic digital readiness, so this capstone team, with over 70 years of combined United States naval data expertise, recommends that OVERMATCH consider these findings and generate a system that ensures data availability and quality for the Navy.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2021
- Accession Number
- AD1150951
Entities
People
- Caitlyn R. O'shaughnessy
- Kheng S. Hun
- Obed Matuga
- Robert French
- Wallace Y. Jr Fukumae
Organizations
- Naval Postgraduate School