Additive manufacturing (AM) has been envisioned by many as a driving factor of the next industrial revolution. Potential benefits of AM adoption include the production of low-volume, customized, complicated parts/products, supply chain efficiencies, shortened time-to-market, and environmental sustainability. Work remains, however, for AM to reach the status of a full production-ready technology. Whereas the ability to create unique 3D geometries has been generally proven, production challenges remain, including lack of (1) data manageability through information management systems, (2) traceability to promote product producibility, process repeatability, and part-to-part reproducibility, and (3) accountability through mature certification and qualification methodologies. To address these challenges in part, this paper discusses the building of data models to support the development of validation and conformance methodologies in AM. We present an AM information map that leverages informatics to facilitate part producibility, process repeatability, and part-to-part reproducibility in an AM process. We present three separate case studies to demonstrate the importance of establishing baseline data structures and part provenance through an AM digital thread.