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Data-Driven Design

Integrate GIS, sensor, and climate data into architectural design workflows.

Updated Apr 14, 2026
Search Tags:#sensors#data-driven#api-integration#gis#occupancy#space-syntax#climate-analysis
One-click install
npx skills add https://github.com/gerald-ica/opencode-config-snapshot --skill data-driven-design
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Data-Driven Design
Source: https://github.com/gerald-ica/opencode-config-snapshot/tree/main/opencode/skills/data-driven-design
Command: npx skills add https://github.com/gerald-ica/opencode-config-snapshot --skill data-driven-design

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps architects and urban designers replace intuition with evidence by integrating GIS context, sensor streams, occupancy analytics, space syntax, climate data, and API sources into a coherent design workflow.

Core Features & Use Cases

  • GIS integration for contextual site analysis: combine location, topography, land use, and infrastructure data to inform zoning, massing, and program decisions.
  • Sensor data and occupancy analytics pipelines: ingest, clean, and analyze indoor environmental quality, occupancy, and usage patterns to drive HVAC, daylight, and space planning.
  • Space syntax and urban data analytics: quantify connectivity, accessibility, movement, and urban vitality to optimize circulation and public realm design.
  • Climate data processing and API data sources: incorporate EPW weather data, microclimate indicators, and API feeds for performance benchmarks and resilience planning.

Quick Start

Load your GIS context and sensor data, then run a data-driven design iteration to inform early spatial decisions.

Frequently Asked Questions about Data-Driven Design

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

FAQPage Schema
How do I combine GIS data and sensor streams for evidence-based architectural design?▼

Combining GIS data and sensor streams for evidence-based design involves integrating location, topography, occupancy analytics, and indoor environmental quality into a coherent workflow. This guides zoning, massing, and space planning decisions using reproducible data pipelines.

What is space syntax and how does it inform urban circulation design?▼

Space syntax is an analytical method that quantifies urban connectivity, accessibility, and movement patterns. It informs circulation design by optimizing the public realm and urban vitality based on data-driven spatial analytics.

Can I use EPW weather data and API feeds for climate adaptation planning?▼

Yes, you can use EPW weather data and API feeds for climate adaptation planning. Processing microclimate indicators and external data sources provides performance benchmarks to drive resilience strategies and climate-informed design decisions.

How to start a data-driven site analysis using occupancy analytics and GIS context?▼

To start data-driven site analysis, load your GIS context and sensor data, then run a design iteration. Ingesting and cleaning occupancy analytics reveals usage patterns that inform early spatial decisions and programming.

Does this approach support open standards for reproducible data workflows?▼

Yes, this approach supports open standards for reproducible data workflows. It ensures provenance and modular data processing by integrating API sources, sensor streams, and climate data using references provided in the skill content.

What is the best way to integrate indoor environmental quality sensors with space planning?▼

The best way to integrate indoor environmental quality sensors with space planning is through occupancy analytics pipelines. Ingesting and analyzing these sensor streams drives HVAC, daylight, and spatial programming decisions.

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