# SAP Signavio Academic Models: A Large Process Model Dataset

arXiv: https://arxiv.org/abs/2208.12223 · HTML: https://mlsanity.com/paper/2208.12223/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Aug 2022.

## Built on by (most cited first, 11 of 11)

- [Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks](https://mlsanity.com/paper/2407.02310/) (2024)
- [DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models](https://mlsanity.com/paper/2406.15781/) (2024)
- [xSemAD: Explainable Semantic Anomaly Detection in Event Logs Using Sequence-to-Sequence Models](https://mlsanity.com/paper/2406.19763/) (2024)
- [Towards a Benchmark for Large Language Models for Business Process Management Tasks](https://mlsanity.com/paper/2410.03255/) (2024)
- [Automated Business Process Analysis: An LLM-Based Approach to Value Assessment](https://mlsanity.com/paper/2504.06600/) (2025)
- [On the Potential of Large Language Models to Solve Semantics-Aware Process Mining Tasks](https://mlsanity.com/paper/2504.21074/) (2025)
- [LLMs that Understand Processes: Instruction-tuning for Semantics-Aware Process Mining](https://mlsanity.com/paper/2508.16270/) (2025)
- [Evaluating the Process Modeling Abilities of Large Language Models -- Preliminary Foundations and Results](https://mlsanity.com/paper/2503.13520/) (2025)
- [On LLM-Assisted Generation of Smart Contracts from Business Processes](https://mlsanity.com/paper/2507.23087/) (2025)
- [Detecting Undesired Process Behavior by Means of Retrieval Augmented Generation](https://mlsanity.com/paper/2505.22041/) (2025)
- [Beyond Control-Flow: Integrating the Resource Perspective into Multi-Collaborative Process Modeling from Text](https://mlsanity.com/paper/2605.24546/) (2026)

## Abstract (arXiv)

In this paper, we introduce the SAP Signavio Academic Models (SAP-SAM) dataset, a collection of hundreds of thousands of business models, mainly process models in BPMN notation. The model collection is a subset of the models that were created over the course of roughly a decade on academic.signavio.com, a free-of-charge software-as-a-service platform that researchers, teachers, and students can use to create business (process) models. We provide a preliminary analysis of the model collection, as well as recommendations on how to work with it. In addition, we discuss potential use cases and limitations of the model collection from academic and industry perspectives.