Datasets:

pritamdeka
/

BPMN-VLM

dataset_info:
  features:
    - name: image
      dtype: image
    - name: bpmn
      dtype: string
    - name: image_filename
      dtype: string
    - name: bpmn_filename
      dtype: string
    - name: split
      dtype: string
  splits:
    - name: train
      num_bytes: 43277266
      num_examples: 101
    - name: validation
      num_bytes: 110828879
      num_examples: 50
    - name: test
      num_bytes: 104260192
      num_examples: 51
  download_size: 220317996
  dataset_size: 258366337
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
task_categories:
  - image-to-text
  - image-text-to-text
pretty_name: BPMN Diagram ↔ BPMN XML Paired Dataset
size_categories:
  - 1K<n<10K

🏗️ BPMN Diagram → BPMN XML Paired Dataset

Structured Extraction from Business Process Diagrams using Vision-Language Models

This dataset contains Business Process Model and Notation (BPMN) diagrams paired with their corresponding .bpmn XML ground truth files.
The dataset is designed for training, evaluation, and benchmarking multimodal models that perform structured extraction from diagrams, including OCR-enhanced pipelines and vision-language models (VLMs).

📦 Dataset Contents

Each example includes:

Field	Description
`image`	BPMN diagram image (PNG/JPEG), uploaded directly to HF
`bpmn`	Text content of the corresponding `.bpmn` XML file
`image_filename`	Original image filename
`bpmn_filename`	Original BPMN filename
`split`	One of: `train`, `validation`, `test`

Folder structure used during creation:

dataset/
├── train/
│   ├── images/
│   ├── bpmn/
├── validation/
│   ├── images/
│   ├── bpmn/
├── test/
    ├── images/
    ├── bpmn/

🖼️ Example Image

Ground Truth BPMN (excerpt)

<bpmn:definitions xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xmlns:bpmn="http://www.omg.org/spec/BPMN/20100524/MODEL"
    xmlns:bpmndi="http://www.omg.org/spec/BPMN/20100524/DI"
    xmlns:dc="http://www.omg.org/spec/DD/20100524/DC"
    id="Definitions_1"
    targetNamespace="http://bpmn.io/schema/bpmn">

  <bpmn:process id="Process_1" isExecutable="false">

    <bpmn:startEvent id="StartEvent_1">
      <bpmn:outgoing>Flow_0abcd12</bpmn:outgoing>
    </bpmn:startEvent>

    <bpmn:task id="Task_1" name="Receive Order">
      <bpmn:incoming>Flow_0abcd12</bpmn:incoming>
      <bpmn:outgoing>Flow_0efgh34</bpmn:outgoing>
    </bpmn:task>

    <bpmn:exclusiveGateway id="Gateway_1">
      <bpmn:incoming>Flow_0efgh34</bpmn:incoming>
      <bpmn:outgoing>Flow_0ijkl56</bpmn:outgoing>
      <bpmn:outgoing>Flow_0mnop78</bpmn:outgoing>
    </bpmn:exclusiveGateway>

    <bpmn:task id="Task_2" name="Validate Order">
      <bpmn:incoming>Flow_0ijkl56</bpmn:incoming>
      <bpmn:outgoing>Flow_0qrst90</bpmn:outgoing>
    </bpmn:task>

      ...

 </bpmndi:BPMNDiagram>
</bpmn:definitions>

🔧 Usage

from datasets import load_dataset

ds = load_dataset("pritamdeka/BPMN-VLM")

example = ds["train"][0]

image = example["image"]               # PIL image object
bpmn_text = example["bpmn"]           # XML content as string
image_name = example["image_filename"]
bpmn_name = example["bpmn_filename"]

🎯 Applications

This dataset is suitable for:

BPMN diagram understanding and parsing
OCR + VLM multimodal pipelines
Structured JSON extraction
Diagram-to-XML reconstruction
Fine-tuning Pixtral, Qwen2.5-VL, LLaMA 3.2 Vision, Aya Vision, Gemma3 and other VLMs
Evaluation against ground truth .bpmn files

Ideal for research in:

Vision-language reasoning
Diagram understanding
Business process modelling automation

📜 Citation

If you use this dataset, please cite:

@misc{deka2025structuredextractionbusinessprocess,
      title={Structured Extraction from Business Process Diagrams Using Vision-Language Models}, 
      author={Pritam Deka and Barry Devereux},
      year={2025},
      eprint={2511.22448},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2511.22448}, 
}

📄 License

This dataset is released under CC BY-NC 4.0 —
It can be used for research and non-commercial purposes with attribution.

🙏 Acknowledgements

Developed at the Advanced Research Centre (ARC), Queen’s University Belfast, as part of research into multimodal structured extraction from business process diagrams.

📬 Contact

For questions, contact:
Pritam Deka — p.deka@qub.ac.uk