Advanced manufacturing science and application is a critical area for the National Institute of Standards and Technology (NIST) mission, supporting measurement science research and development. The Additive Manufacturing Benchmark (AMBench) test series provides high-quality data and modeling outputs for exchange with a broad community of industry, partners and academia. These digital products are sourced from multiple organizations each generating controlled sets of experimental instrumentation data or computational models, subsequently analysed, processed and assembled into the AM Bench test series collection. Early in the AM Bench series 2022 development, the implementation of FAIR data architecture was introduced to provide more flexibility for discovery and access. In charting the course, a suite of tools and a semantic data model were developed to ensure provenance of the outputs, including build products, derived specimens and measurements. AM Bench measurement data is deposited in the NIST Public Data Repository (PDR). This is complemented by a public searchable catalog of semantically structured metadata. It was recognized early in development with the AMBench 2022 test series project, the scale and complexity of data would benefit from a system which brings compute to data. The Johns Hopkins public SciServer collaborative platform supports dynamically provisioned compute in an environment colocated with the AM Bench data. A new manufacturing application domain was established in SciServer and the AMBench test series volume was created through a mirror of the PDR datasets. The AMBench 2022 test series data management provides the groundwork for the project team and collaborators to explore more advanced models including digital twins and integration with AI tools. Data analytics across these platforms demonstrate the power of interoperable systems and form a strong foundation for the AM Bench 2025 test series to accelerate broader advanced manufacturing application.