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lamindb

Organize biological datasets with versioned, queryable artifacts and lineage tracking.

Updated May 24, 2026
Search Tags:#data lineage#FAIR data#workflow tracking#dataset curation#ontology annotation#laminDB
One-click install
npx skills add https://github.com/Estrella-231/Mathematical_modeling_tongmeng --skill lamindb-estrella-231
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lamindb
Source: https://github.com/Estrella-231/Mathematical_modeling_tongmeng/tree/main/.agents/skills/lamindb
Command: npx skills add https://github.com/Estrella-231/Mathematical_modeling_tongmeng --skill lamindb-estrella-231

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

LaminDB helps you manage biological datasets so they are discoverable and reusable, while preserving end-to-end provenance so results can be traced back to the exact data and computation that produced them.

Core Features & Use Cases

  • FAIR data management for biology: Turn datasets into versioned, queryable artifacts with typed metadata (features) and consistent annotations.
  • Data lineage and reproducibility: Track computational workflows, capture inputs/outputs, record parameters, and visualize lineage graphs.
  • Ontology-driven curation: Standardize annotations using biological ontologies (via Bionty), validate schemas, and enforce dataset structure.
  • Use Case: Curate scRNA-seq outputs from multiple batches by validating schema, standardizing cell-type labels through an ontology, saving the validated artifacts, and then querying across batches by tissue and condition.

Quick Start

Use the lamindb skill to curate and validate an annotated dataset by following the guidance in the references files, starting with schema design and then saving a validated artifact with linked ontology terms.

Frequently Asked Questions about lamindb

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track data lineage for scRNA-seq workflows across multiple batches?▼

Make biological data FAIR by turning datasets into versioned, queryable artifacts with typed metadata and consistent annotations. This approach ensures datasets remain discoverable and reusable while preserving end-to-end provenance for results tracing.

How do I standardize cell-type annotations using biological ontologies?▼

Standardize cell-type annotations by applying ontology-driven curation using biological ontologies via Bionty. This process validates schemas, enforces dataset structure, and standardizes labels to ensure consistent annotations across datasets.

Can I query biological datasets by tissue and condition after schema validation?▼

Query biological datasets by tissue and condition after validating schemas and saving validated artifacts with linked ontology terms. This feature-based querying allows you to select data across multiple batches based on specific metadata features.

Does LaminDB integrate with existing MLOps systems for dataset curation?▼

LaminDB integrates with workflow or MLOps systems to support dataset curation and deterministic lineage capture. It applies schema and ontology validation workflows using core concepts and curation APIs to manage biological datasets effectively.

What is the best way to validate dataset structure before saving biological artifacts?▼

Validate dataset structure by designing a schema first, then applying ontology-based annotation to enforce consistent structure before saving. This ensures artifacts are validated with linked ontology terms, maintaining data integrity and queryability.

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