Design and Implementation of the NASA Psyche Discovery Mission Science Data Center

Abstract—The NASA Psyche Discovery Mission is currently cruising towards a rendezvous with the asteroid (16) Psyche, the largest M-class asteroid in the main asteroid belt [1]. The spacecraft instrument suite consists of a magnetometer, gamma ray and neutron spectrometers, multispectral imagers, and radio science experiments, all designed to unravel the history of (16) Psyche [2,3]. The resulting data products generated by the mission (e.g., images; spectroscopic, magnetic, and gravity field data; shape models; geologic maps, etc.) will be delivered to the Small Bodies Node of the NASA Planetary Data System (PDS) for long-term archiving [4]. The Psyche mission’s Science Data Center (SDC), part of the JPL Psyche Mission System, is the point of contact for all data sharing and archiving activities. Here we describe the design and implementation of the SDC, which was guided by many factors: supporting mission requirements related to data warehousing; performing data dissemination and archiving; adhering to federal, NASA, and ASU cybersecurity guidelines; and following industry best practices. Given the long baseline of the mission (launch in October 2023 and arrival at the asteroid in mid-2029), the system needs to be easily maintainable and upgradable during the mission’s lifetime. The SDC is located on the Tempe campus of ASU, with connections to the mission’s Ground Data System at JPL and is available to the Psyche team via a web portal utilizing purpose-built tools. The SDC leverages heritage tools, concepts, and lessons learned from previous ASU instrument operations, such as for the Lunar Reconnaissance Orbiter Cameras on LRO, the Mastcam cameras on the Mars Science Laboratory rover, and the Mastcam-Z cameras on the Mars 2020 rover. We describe the heritage, principles, and requirements that guided the design and initial development of the Psyche Science Data Center, including real-world examples of the SDCs data portal, RESTful interface, in-house scripts, and early data products. The design of the SDC is centered around a relational database, with a schema to model the many files that are ingested and tracked, as well as their relationships to the PDS bundles being aggregated and delivered. The SDC disseminates data products to the Psyche Team for science investigations through a web-based portal, which also includes a RESTful interface that allows team members to upload, download and search data using in-house scripts. The three instrument teams make heavy use of the RESTful interface for uploading their PDS products. The web portal also makes mosaics and individual image products available to the team using Web Mapping Service technology. Most of the tools developed for the SDC are written in Python, using virtual environments to minimize the need to configure and maintain Python at the system level. These adhere to the UNIX philosophy of software development: make each program do one thing well, expect output (when generated) to become input to another tool, and test early and refactor as needed.