Case Study




United States



10x Increase in engineering productivity

Engineers no longer spend valuable time manually pulling and wrestling with data and are able to answer questions and make adjustments more quickly

Reduced risk

Stardog enables cross-functional activities across multiple datasets allowing for the identification and subsequent mitigation of previously unrecognized risks

Saved time

The Knowledge Graph reduces back and forth and allows for faster review processes, keeping rockets on schedule for launch

Building a rocket is a complex endeavor of precision, involving huge numbers of people, vast amounts of disparate data, many interconnected pieces, and no margin for error. Using Stardog, NASA can quickly make fully informed mission-critical decisions, improving engineering design while reducing cost and risk.

The Challenge

A successful rocket launch is the product of many interdependent parts and systems that must all work together perfectly. Even small changes to one system can significantly impact another seemingly unrelated system.

For example, engineers must ensure that humans will be able to tolerate the rocket’s vibrations and have created a complex mathematical model that verifies the precise calibration of acceptable vibration. This requires a range of inputs about the amount of vibration that will be generated, as well as information about the impact that a slight change in vibration has on the human body, all of which needs to be aligned with project data on factors like schedule and cost.

It typically took NASA engineers weeks to pull the relevant data manually from each dataset, analyze and qualify it, and create a report. If a review board asked a new question or if the scope changed in any way, the engineers had to go back to the drawing board and repeat the whole process. Because every question created an entirely new project that needed its own complex assessment, the review cycle was long and costly. NASA engineers spent lots of valuable time wrestling with the data. Change became more expensive and riskier due to the connectedness and complexity of the data.

"NASA engineers spent lots of valuable time wrestling with the data. Change became costlier and riskier due to the connectedness and complexity of the data."

The Solution

NASA implemented Stardog’s Enterprise Knowledge Platform to provide the systems engineering and integration community with a unified view across the various engineering disciplines.

Stardog’s Knowledge Graph Platform allows NASA to manage, query, and analyze data at scale. The Knowledge Graph creates an abstract layer of knowledge over disparate data systems and organizes and represents information using entities(nodes) and relationships between those entities (edges). This consolidates redundant data gathering processes carried out by multiple teams into a single process in a central location. With consolidated data, NASA can harness the power of inference. This ability to spot patterns and surface hidden relationships can be the engine behind risk analysis, fraud detection, recommendation systems, and many more.

The Knowledge Graph can perform systems engineering tasks such as the closure of requirements, verification, validation, gap analysis, and various data products reporting. Using Stardog, a NASA engineer can find a requirement verification, associated hazard, intersection with a math model, and associated monitoring condition in seconds, without writing a single query, manually navigate silos, run exports, or integrate data by hand.

"Since implementing Stardog, NASA engineers have saved countless hours assembling the answers they need from interconnected data. What took weeks to compile now takes seconds."

The Results

Stardog’s Knowledge Graph goes beyond highlighting associations between datasets and within the data; it brings robust features to power NASA’s Artemis missions:

Data virtualization speeds time to insight: Stardog’s virtual graph and rich data services provide access to data without changing existing NASA processes or its ability to select best-of-breed tools.

Reusable data modeling creates insight: Stardog uses declarative graph modeling and rules to knit together the data relationships and overcome limits in the source systems. The modeling includes Stardog Rules for describing and optimizing specific relationships in the graph. Declarative graph modeling also enables traceability of individual data sources to compare and verify data pedigrees.

Data quality and assurance without writing code: Integrity Constraint Validation is built into the platform and flags potential errors and gaps in the Knowledge Graph and can highlight problems within a specific data source.

AI and ML create contextual knowledge & data lineage: Stardog combines the power of graphs with a knowledge toolkit fusing machine learning, reasoning, and rules for contextualized insight of all the data. SPARQL and PATH queries support a broader range of graph queries and analysis of complex reports.

NASA-grade operations workflow: Stardog is fully integrated into the NASA operations workflow with backup, restore, and single sign-on capability.

Since implementing Stardog, NASA engineers have saved countless hours assembling the answers they need from interconnected data. What took weeks to compile now takes seconds. NASA engineers can ask new questions, explore data, and examine the connectedness of data and the impact of changes throughout the mission, from the earliest flight modeling stages to launch and beyond. With Stardog providing complete traceability of data, issues within data sources come to light that would have been impossible to spot manually.

With all these benefits, engineering groups using Stardog have seen a 10x increase in productivity, allowing for improved designs while reducing cost and risk.

The Future

NASA continues to incorporate data from new missions and programs and is transitioning to a Knowledge Graph first approach in many areas. This will allow teams to work more efficiently and collaboratively, accelerating advances in space technology and innovation

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