Description: The DPUQC: Data Pipeline Uncertainty and Quality Control for Trustworthy Space Autonomy creates an updated pipeline that will treat Uncertainty Quantification (UQ) and Sensitivity analysis of models as primary objectives of the pipeline. This will be achieved by augmenting traditional pipelines, which currently handle problems of dynamic scaling, inhomogeneous data formats and data enrichment quite well. While these cloud native solutions have their merits, they do not consider the need to dynamically adjust operations in the presence of significant resource reduction. These pipelines assume that error analysis only the job of the terminal model. DPUQC will address this with a pipeline that pushes annotated data which carries quantifiers of uncertainty along with the data. This will provide data provenance for down stream decisions enabling explainability. The UQ that is transported can be adjust to accommodate changes in resources available to run the pipeline. Model analysis at the terminal edge of the pipeline will test model sensitivity to the variability of the data captured in the UQ, while also providing additional evidence to accept or reject the decision in the form of corroborating decisions from independently trained diagnostic models. The addition of provenance chains with UQ, diagnostic models and UQ model based testing will increase decision trustworthiness as each decision can be cross checked both via the model sensitivity and by comparing to additional evidence the diagnostic models provide. Any decision can be traced to the source that lead to it for diagnostic and quality control purposes.

Benefits: In the era of pioneering lunar exploration and habitation, NASA's Gateway mission represents a monumental step towards a sustainable human presence on the Moon. At the heart of this endeavor lies the International Habitat (I-Hab), a cutting-edge module designed for astronaut habitation and scientific experimentation. Engineered for resilience and efficiency, the I-Hab's thermal control system is critical for maintaining a safe and habitable environment for astronauts, necessitating unparalleled precision in monitoring and maintenance. Our solution, a sophisticated data pipeline for Uncertainty and Quality control of sensor data, is tailored to meet this need, offering an innovative approach to ensuring the thermal integrity and safety of the habitat. Leveraging real-time data analysis through our proposed pipeline, our system is designed to seamlessly integrate with the I-Hab's data sources. DPUCQ is tailored to handle the scalability and reliability that a complex system requires.Since DPUQC can be used to add robust decision-making to any pipeline, it's reasonable to expect that a significant fraction of the data pipeline market, estimated to be 7.1 billion in 2021 and grow 24% by 2030, may adopt such a technology. This is especially true for mission critical data pipelines like those found in military or medical operations. Other groups that require explainable predictions (e.g. Banking compliance or legal decisions) will also require UQ in their pipelines to support explainability. Since much of future the tech innovation will have an AI component (if not directly an AI product), it's reasonable to expect that the appetite for data pipelines may grow even larger.