README.md

---
license: cc-by-nc-nd-4.0
task_categories:
  - robotics
  - other
tags:
  - manipulation
  - egocentric
  - imu
  - factory
  - shoe-manufacturing
  - bimanual
size_categories:
  - n<1K
pretty_name: "Daneel Data — Real-world factory manipulation"
extra_gated_prompt: "Access is provided for evaluation only. Please do not redistribute this sample dataset."
extra_gated_fields:
  "Company / Lab": text
  "Work email": text
  "Role": text
  "What are you building?": text
  "Intended use": text
  "I agree not to redistribute this sample dataset": checkbox
extra_gated_button_content: "Request access"
---

# Daneel Data — Real-world factory manipulation

![Daneel Data sample — 9-grid preview](thumbnail.jpg)

A private evaluation sample of real-world, egocentric factory-floor manipulation
recordings captured during shoe production. Provided to qualified teams
evaluating the full Daneel Data corpus for robotics foundation-model training.

This is not an open-source release. Access is granted by request, for
evaluation purposes only.

## What's included

- **25 unique 3-minute clips**, organized into **3 task packs** (57 pack-copies total)
- **22 workers**, **19 task subcategories** across **19 production stages**
- **Egocentric video** paired with **synchronized wrist + head motion sensing**, pre-aligned to the camera frame timeline
- **Task metadata** with plain-language task descriptions
- **Step-level annotations** encoded via the task-pack / category / subtask directory hierarchy

## Task organization

The same set of clips is presented through three lenses:

1. **Capability Task Packs** — grouped by manipulation capability: contact-rich adhesive application; fine bimanual alignment & attachment; machine-assisted operations; inspection / visual checking / rework.
2. **Sole Attachment Workflow** — end-to-end coverage of one critical sub-process: `body_bottom_glue → sole_glue → sole_attachment → final_press → sole_inspection_rework`.
3. **Full Production Line** — all 19 stages of shoe assembly, suitable for studying production-stage transitions and long-horizon dependencies.

## Package layout

```
daneel-data-sample/
├── README.md
├── LICENSE                         (CC BY-NC-ND 4.0)
├── thumbnail.jpg
└── <task_pack>/<category>/[<subtask>/]
    ├── intrinsics.json             (camera intrinsics + axis conventions, same across all clips)
    └── <clip_id>.tar               (one clip per archive)
```

Each `.tar` archive contains, for one clip:
- Egocentric video (~3 min)
- Synchronized per-frame motion vector (CSV — one row per video frame)
- Compact JSON metadata: `clip_id`, `subject`, `task` (name + plain-language description), `duration_s`

## Loading

```python
import csv, json, tarfile, io

clip_id = "factory_001_worker_016_001"
with tarfile.open(f"{clip_id}.tar") as tf:
    meta = json.load(tf.extractfile(f"{clip_id}/metadata.json"))
    rows = list(csv.DictReader(io.TextIOWrapper(
        tf.extractfile(f"{clip_id}/per_frame_imu.csv"), encoding="utf-8")))
    tf.extract(f"{clip_id}/{clip_id}.mp4", path=".")
```

## License

[**CC BY-NC-ND 4.0**](https://creativecommons.org/licenses/by-nc-nd/4.0/). Inspection and citation for evaluation purposes are permitted. Redistribution and commercial use are not.

## Commercial use & full corpus access

The full Daneel Data corpus, and commercial licensing of any subset, are available on request.

- Website: **https://www.daneeldata.com**
- Inquiries (commercial / partnership / dataset access): see website

## Citation

```
@misc{daneeldata2026sample,
  title  = {{Daneel Data}: Real-world factory manipulation data for robotics foundation models},
  author = {{Daneel Data}},
  year   = {2026},
  url    = {https://www.daneeldata.com},
  note   = {Sample package, v1}
}
```