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Case Study - Robust and flexible database solution for submarines
Rapid decision-making

We created a robust and flexible database solution for submarines to help commanders make quick decisions and ensure data from sensors on board is handled smoothly.

The ability to rapidly understand a contact’s speed, course, classification and closest point of approach (CPA) based on data gathered from various sensors is necessary to provide crews with an edge over adversaries.

We developed a future-proofed backend underpinning the future development of intelligent decision-making software. In turn, this provided significant support for essential submarine operations.

BAE Submarines will now run a test deployment of the software, after which they will refine the product further.

Jon Locke
BAE Systems Submarines
Senior Technologist

“The work has pushed the schedule and delivered a more capable technical solution than would have been possible without the engagement. The service was professional and delivered all that was asked for whilst pushing the creativity of the work done. Personnel were highly knowledgeable, and where knowledge didn’t exist, it was quickly learnt and applied”.

The challenge

Submarine crews depend on data to inform decisions, as visually identifying contacts is often impossible. Crews must perform complex calculations and use experienced-based judgement when classifying contacts and deciding how to proceed.

The ability to rapidly understand a contact’s speed, course, classification and closest point of approach (CPA) based on data gathered from various sensors is necessary to provide crews with an edge over adversaries.

The Approach

We worked closely with the Future Capability team at BAE Submarines, former Submarine Operators and subject matter experts (SMEs) to develop ontologies (the classification and explanation of entities) to build a picture of the requirements for the data model.

Using a phased approach, we built an ontology and tested the model with synthetic data and queries to see how it performed. We held Conversations with former Submarine Operators to discuss whether the model met the operational requirements. After this, the model could be further refined.

Benefits

Better Consistency in data handling
Improved query performance and ease of use from ‘non-technical’ users
Ability to derive ‘hidden’ inference from sensor data
A robust and flexible framework for ingestion and storing of data
Marriage of understanding of data between humans and machine
Extensive supporting documentation to facilitate the use and performance of provided work

the solution

A robust and adaptable ontology was constructed based on extensive consultations with SMEs specialising in submarine operations and ontology development.

This ontology was designed as a structured framework for ingesting incoming submarine sensor data into a graph database. Care was taken to ensure this ontology met the lofty requirements and granularity required to provide keen insight and effective use of incoming data.

A range of extensively tested Cypher query examples was generated to utilise this data and support the client’s understanding of the query execution process. This resulted in a future-proofed backend underpinning the future development of intelligent decision-making software. In turn, this provided significant support for essential submarine operations.

To support adoption, we provided comprehensive documentation regarding the ontology. This included a reference book that detailed specialised terminologies relevant to Submarine operations and the relevant subject area and a series of detailed reports spanning the four critical stages of the project.

Additional documentation and written research materials were regularly provided to the client throughout the project. These resources were provided to keep the client informed of progress and to foster a deeper understanding of the work undertaken, allowing for maximum utilisation of the delivered work for future undertakings.

next steps

BAE Submarines will now run a test deployment of the software, after which they will refine the product further. Artificial Intelligence and Automated Reasoning have been suggested to expand the software’s capabilities further. Techmodal and BAE will collaborate again to achieve this.


Graph databases and knowledge graphs are rising in popularity as their potential to aid in technologies such as Large Language Models is being realised. Techmodal will be looking to collaborate further in this domain.

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