Time-critical product creation, critical for rover safety, is enabled by the Automated Task Invocation Subsystem/Processing Pipeline (Mars Exploration Rover).

Level 2 product summary plots are used for rapid assessment of instrument product quality and instrument health (Microwave Limb Sounder).

Telemetry downlinked from the spacecraft is converted into data products for scientific analysis, investigation and research (Orbiting Carbon Observatory).

The instrument ground system architecture is comprised of a complex network of components that support the science and engineering communities internal and external to JPL. The size and complexity of instrument ground systems varies by project and instrument, with major design drivers being complexity of algorithms, number of distinct product types generated, data volume and throughput performance. Extensive leveraging and software developed using stringent coding standards to support reuse, facilitates rapid system design and deployment. Well defined interface standards and language- and platform-neutral implementation contribute to flexibility of the instrument ground system.

Instrument ground system capabilities and services include: data product generation, distribution, archive and access; modeling, simulation and visualization of data products; management of databases, processes, resources and archives; and instrument strategic and tactical operations products. Model- and ontology-driven architectures have been used throughout the ground systems within the Instrument and Science Software Systems. Common architectural patterns across systems and domains is important to achieve consistent and multiple-use models.

Automated process control/workflow systems handle high volumes of data for missions that require near real-time processing of complex instrument products. The Process Control Subsystem (PCS) and the Multi-mission Automated Task Invocation Subsystem (MATIS) are distributed frameworks that coordinate and initiate processing of CPU-intensive data products. This automation has eliminated the human-in-the-loop for product generation; thereby, reducing risk and increasing reliability while maximizing project resources.

The challenges of database design and data management have been addressed in the information-centric data systems architecture. This 'grid' technology has focused on: search and retrieval of data sets across missions and NASA centers; access and distribution of data to the science and engineering communities; long-term preservation of data that accommodates evolving data definitions and models; and sharing of data between systems, applications, and domains using different formats and access methods. Robust instrument ground system design has been achieved through collaboration across multiple agencies and the use of systems based on open standards and common formats.