Robotics and Humanoid FMEA Public Source Dataset
About this data
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.
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/purchases \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"dataset_id": "38fb601d-ac2e-421e-b87c-90d75ddf6783"}'