# OntoGSN: An Ontology-Based Framework for Semantic Management and Extension of Assurance Cases

arXiv: https://arxiv.org/abs/2506.11023 · HTML: https://mlsanity.com/paper/2506.11023/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 55 references that are in the map.
- First posted on arXiv 20 May 2025.

## Builds on (most cited first, 4 of 4)

- [Safety case template for frontier AI: A cyber inability argument](https://mlsanity.com/paper/2411.08088/) (2024)
- [Security Assurance Cases -- State of the Art of an Emerging Approach](https://mlsanity.com/paper/2003.14151/) (2020)
- [Assessing Confidence with Assurance 2.0](https://mlsanity.com/paper/2205.04522/) (2022)
- [Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs](https://mlsanity.com/paper/2410.05304/) (2024)

## Abstract (arXiv)

Assurance cases (ACs) are a common artifact for building and maintaining confidence in system properties such as safety or robustness. Constructing an AC can be challenging, although existing tools provide support in static, document-centric applications and methods for dynamic contexts (e.g., autonomous driving) are emerging. Unfortunately, managing ACs remains a challenge, since maintaining the embedded knowledge in the face of changes requires substantial effort, in the process deterring developers - or worse, producing poorly managed cases that instill false confidence. To address this, we present OntoGSN: an ontology and supporting middleware for managing ACs in the Goal Structuring Notation (GSN) standard. OntoGSN offers a knowledge representation and a queryable graph that can be automatically populated, evaluated, and updated. Our contributions include: a 1:1 formalization of the GSN Community Standard v3 in an OWL ontology with SWRL rules; a helper ontology and parser for integration with a widely used AC tool; a repository and documentation of design decisions for OntoGSN maintenance; a SPARQL query library with automation patterns; and a prototypical interface. The ontology strictly adheres to the standard's text and has been evaluated according to FAIR principles, the OOPS framework, competency questions, and community feedback. The development of other middleware elements is guided by the community needs and subject to ongoing evaluations. To demonstrate the utility of our contributions, we illustrate dynamic AC management in an example involving assurance of adversarial robustness in large language models.