Datasets:
File size: 4,600 Bytes
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dataset_info:
features:
- name: file_name
dtype: string
- name: source_file
dtype: string
- name: question
dtype: string
- name: question_type
dtype: string
- name: question_id
dtype: int32
- name: answer
dtype: string
- name: answer_choices
list: string
- name: correct_choice_idx
dtype: int32
- name: image
dtype: image
- name: video
dtype: video
- name: media_type
dtype: string
splits:
- name: test
num_examples: 1040
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
license: mit
task_categories:
- visual-question-answering
language:
- en
size_categories:
- 1K<n<10K
tags:
- engineering
- simulation
- stratified-subset
---
# OpenSeeSimE-Fluid-Mini
A **stratified 1% subset** of [`cmudrc/OpenSeeSimE-Fluid`](https://huggingface.co/datasets/cmudrc/OpenSeeSimE-Fluid) for evaluating vision-language models at a reduced compute footprint while preserving the joint distribution of simulation type, question type, media type, and question id.
## Subset Provenance
- **Parent dataset**: [`cmudrc/OpenSeeSimE-Fluid`](https://huggingface.co/datasets/cmudrc/OpenSeeSimE-Fluid) (98,326 rows total)
- **Rows in this subset**: **1,040** (1.06% of parent)
- **Source classes**: `Bent Pipe`, `Converging Nozzle`, `Heat Exchanger`, `Heat Sink`, `Mixing Pipe`
- **Parquet shards**: 3 | **Storage**: ~11.61 GB
- **Sampling**: per-stratum shuffle with `numpy.random.default_rng(42)`, then take `ceil(n * fraction)` from each stratum. Any non-empty stratum contributes at least 1 row.
- **Strata**: `(source_file, question_type, media_type, question_id)` — all four jointly.
- **Nesting**: the 1% subset is a literal subset of the 10% subset (same shuffled prefix is taken for every fraction).
## Composition
### By `source_file`
| source_file | rows | pct |
|:------------------|-------:|------:|
| Heat Exchanger | 220 | 21.15 |
| Mixing Pipe | 220 | 21.15 |
| Bent Pipe | 204 | 19.62 |
| Converging Nozzle | 204 | 19.62 |
| Heat Sink | 192 | 18.46 |
### By `media_type`
| media_type | rows |
|:-------------|-------:|
| image | 520 |
| video | 520 |
### By `(source_file, question_type)`
| source_file | Binary | Multiple Choice | Spatial | Total |
|:------------------|---------:|------------------:|----------:|--------:|
| Bent Pipe | 82 | 82 | 40 | 204 |
| Converging Nozzle | 82 | 82 | 40 | 204 |
| Heat Exchanger | 88 | 88 | 44 | 220 |
| Heat Sink | 76 | 72 | 44 | 192 |
| Mixing Pipe | 88 | 88 | 44 | 220 |
## Feature Schema
Identical to the parent dataset. See [`cmudrc/OpenSeeSimE-Fluid`](https://huggingface.co/datasets/cmudrc/OpenSeeSimE-Fluid) for full documentation of simulation generation, ground-truth extraction, preprocessing, limitations, and intended use.
```python
{
'file_name': str, # Unique identifier
'source_file': str, # Base simulation model
'question': str, # Question text
'question_type': str, # 'Binary', 'Multiple Choice', 'Spatial'
'question_id': int, # Question identifier (1-20)
'answer': str, # Ground truth answer
'answer_choices': list[str], # Options
'correct_choice_idx': int, # Index of correct answer
'image': Image, # PIL Image (1920x1440) or null for video rows
'video': Video, # Video bytes or null for image rows
'media_type': str, # 'image' or 'video'
}
```
## Intended Use
- Benchmark evaluation of vision-language models on engineering simulation question answering at reduced compute cost
- Smoke-testing of evaluation pipelines before running the full benchmark
- Comparative studies where storage or bandwidth constraints matter
## License
MIT — same as parent. Free for academic and commercial use with attribution.
## Citation
```bibtex
@article{ezemba2024opensesime,
title={OpenSeeSimE: A Large-Scale Benchmark to Assess Vision-Language Model Question Answering Capabilities in Engineering Simulations},
author={Ezemba, Jessica and Pohl, Jason and Tucker, Conrad and McComb, Christopher},
year={2025}
}
```
## Contact
**Jessica Ezemba** — jezemba@andrew.cmu.edu
Department of Mechanical Engineering, Carnegie Mellon University
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