Robotics and Humanoid FMEA Public Source Dataset
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Not documented — confirm reuse terms with the seller
- Source / creator
- Not documented
- Collection method
- Supplier description: Public-source dataset for the Robotics Companies FMEAs bounty. Includes 18 robot, humanoid, HRC, personal-care robot, collaborative robot, autonomous robot, failure mode and effects analysis, and FMEA-methodology sources with URLs, source type, year, robot platform/domain, directness label, access status, relevance score, evidence locator, evidence note, and notes. This is AI-assisted public research with manual review labels. It is a compiled source index and review dataset: it does not redistribute papers, claim access to private proprietary company FMEAs, or include fabricated safety documents. Original source rights remain with their publishers; buyers get the compiled metadata, links, labels, and review notes.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
Sample structure score: 99.7 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (CSV) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 110 of 110 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 29.7 / 30 | 109 of 110 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| title | 0 / 10 | string | 0 / 10 |
| url | 0 / 10 | string | 0 / 10 |
| source_type | 0 / 10 | string | 0 / 10 |
| year | 0 / 10 | number | 1 / 10 |
| robot_platform_or_domain | 0 / 10 | string | 0 / 10 |
| directness | 0 / 10 | string | 0 / 10 |
| access_status | 0 / 10 | string | 0 / 10 |
| relevance_score | 0 / 10 | number | 0 / 10 |
| evidence_locator | 0 / 10 | string | 0 / 10 |
| evidence_note | 0 / 10 | string | 0 / 10 |
| notes | 0 / 10 | string | 0 / 10 |
About this data
Curated index of 18 public-source FMEA references for robotics, humanoids, collaborative, and autonomous platforms. Includes URLs, source type, relevance scores, and manual review labels. Compiled metadata and links only; does not redistribute original papers or proprietary documents.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py 38fb601d-ac2e-421e-b87c-90d75ddf6783 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| title | string | Public source title or dataset entry name. |
| url | url | Public URL for the source so buyers can verify and inspect the evidence. |
| source_type | string | Source category such as paper, standard, article, or public technical resource. |
| year | integer | Publication or source year when available. |
| robot_platform_or_domain | string | Robot platform, safety domain, or application area connected to the source. |
| directness | string | How directly the source relates to robotics FMEA or humanoid robot safety analysis. |
| access_status | string | Public access note, including whether the source is a PDF, article, abstract, or variable-access page. |
| relevance_score | integer | Manual relevance score from 1 to 5 for the robotics FMEA bounty fit. |
| evidence_locator | string | Where in the source the relevant FMEA, safety, or risk-analysis evidence appears. |
| evidence_note | string | Short manually reviewed evidence note explaining why the source was included. |
| notes | string | Additional buyer-facing context, caveats, or review guidance. |
Sample Data
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Robotics and Humanoid FMEA Pub" })
// Found: 38fb601d-ac2e-421e-b87c-90d75ddf6783
buy_now({ dataset_id: "38fb601d-ac2e-421e-b87c-90d75ddf6783" }) // uses your saved card# Authenticate with your API key:
curl https://api.databazaar.io/datasets/38fb601d-ac2e-421e-b87c-90d75ddf6783 \
-H "Authorization: Bearer YOUR_API_KEY"
# Purchase:
curl -X POST https://api.databazaar.io/datasets/38fb601d-ac2e-421e-b87c-90d75ddf6783/buy \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"dataset_id": "38fb601d-ac2e-421e-b87c-90d75ddf6783"}'