scientific-lab-data-management

Automate lab data management across Benchling, DNAnexus, OMERO, and Protocols.io.

3|1|Updated Feb 11, 2026

Search Tags:#data-management #laboratory #benchling #omero #dnanexus #protocols.io #lab-integrations

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-lab-data-management

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-lab-data-management
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-lab-data-management
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-lab-data-management

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Lab data management across wet and dry workflows is fragmented across ELN, PaaS, imaging, and protocol sharing; this skill unifies these processes to streamline tracking, reproducibility, and collaboration.

Core Features & Use Cases

Integrated data lifecycle: ELN/DNA design/registry, cloud-genomics, imaging, and protocol sharing in a single pipeline.
Reproducible pipelines: standardized data models and artifact outputs support audit trails and collaboration.
Use Case: A team records experiments in Benchling, processes sequencing data in DNAnexus, stores images in OMERO, and shares protocols via Protocols.io, all orchestrated through this skill.

Quick Start

Configure and run a unified lab data management workflow across Benchling, DNAnexus, OMERO, and Protocols.io with a single command describing the involved artifacts and data flows.

Frequently Asked Questions about scientific-lab-data-management

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

FAQPage Schema

How do I automate lab data management across Benchling, DNAnexus, OMERO, and Protocols.io?▼

Lab data management across these platforms is automated by orchestrating ELN, cloud-genomics, imaging, and protocol sharing into a unified pipeline. The skill configures data flows and outputs structured metadata to streamline tracking and reproducibility across wet and dry workflows.

How does unified wet and dry lab data pipeline integration work?▼

Unified wet and dry lab data pipeline integration works by applying standardized data models across REST APIs. It connects experiment recording, sequence design, genomic processing, imaging, and protocol sharing to produce structured artifacts for audit trails and collaboration.

Do I need REST API access to use Benchling and DNAnexus integrations?▼

Yes, REST API access is required for each platform to use Benchling and DNAnexus integrations. The skill requires access to REST APIs for Benchling, DNAnexus, OMERO, and Protocols.io to automate data flows and output structured metadata.

What's the best way to build reproducible pipelines for laboratory data?▼

The best way to build reproducible pipelines for laboratory data is to standardize data models and artifact outputs across ELN, PaaS, imaging, and protocols platforms. This approach supports audit trails and ensures consistent data sharing across integrated workflows.

Can I use this approach to track experiments from protocol recording to genomic data analysis?▼

Yes, you can track experiments from protocol recording to genomic data analysis by unifying the data lifecycle. The skill integrates protocol sharing via Protocols.io, experiment recording in Benchling, and sequencing data processing in DNAnexus within a single orchestrated pipeline.

When do I need a unified data management workflow for laboratory pipelines?▼

You need a unified data management workflow for laboratory pipelines when your research data is fragmented across ELN, PaaS, imaging, and protocol sharing platforms. This approach streamlines tracking, reproducibility, and collaboration across wet and dry lab processes.