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research-data-acquisition

Implement WPF research data acquisition workflows with provider-backed import, preview, validation, and lineage.

Updated Mar 23, 2026
Search Tags:#validation#wpf#backfill#research data#lineage#provider import#dataset cleanup
One-click install
npx skills add https://github.com/rodoHasArrived/Meridian-main --skill research-data-acquisition
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-data-acquisition
Source: https://github.com/rodoHasArrived/Meridian-main/tree/main/.codex/skills/research-data-acquisition
Command: npx skills add https://github.com/rodoHasArrived/Meridian-main --skill research-data-acquisition

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Meridian desktop research acquisition workflows need to import, preview, validate, and hand off provider-backed data without duplicating models, losing lineage, or freezing the UI.

Core Features & Use Cases

  • Provider-backed acquisition with bounded preview: supports date range, granularity, and preview sizing while avoiding full materialization for large datasets.
  • Validation, lineage, and dataset lifecycle: persists provenance, freshness/schema, validation results, and cleanup/retry/cancel behavior through existing catalog/storage/lineage seams.
  • WPF-oriented orchestration and handoffs: keeps orchestration in services and operator projection in view models, handing preview/inspector UI to specialized grid components.

Quick Start

Use the research-data-acquisition skill to add a WPF research acquisition flow that imports a provider dataset, shows a bounded preview, validates results, and records lineage for handoff to the preview/inspector UI.

Frequently Asked Questions about research-data-acquisition

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

FAQPage Schema
How does dataset lineage work during provider-backed data acquisition?▼

Dataset validation in research data acquisition persists provenance, freshness, and schema validation results through existing catalog and storage seams, capturing cleanup, retry, and cancel behavior.

Can I preview large provider datasets without fully materializing them in a WPF research acquisition flow?▼

Provider data acquisition handles partial data and provider failure by persisting validation metadata and applying retry, cancel, and dataset cleanup behaviors, with evidence-backed tests covering these edge cases.

How do I catalog and hand off validated research datasets after provider import?▼

Bounded preview supports date range, granularity, and preview sizing constraints during provider import, avoiding full materialization for large datasets while handing off preview UI to specialized grid components.

Do I need separate services for backfill and dataset cleanup in WPF research data workflows?▼

After provider import and validation, you hand off datasets through existing catalog and lineage seams, ensuring provenance and validation metadata persist for the preview and inspector UI.

What tests should I add for WPF research data acquisition and validation?▼

Research data acquisition workflows inventory provider, backfill, ETL, catalog, and storage seams within services, keeping orchestration out of UI projections to handle dataset cleanup and lifecycle events.

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