@datadrivenconstruction

unit-price-database-manager provides construction estimating workflows: price crud, vendor quote tracking, location factor adjustment, historical trending, csv import/export, and basic validation. implementation is code-forward, lacking task orchestration or integration details.

ifc-to-excel wraps the IfcExporter CLI to convert industry foundation classes files into structured excel workbooks with element data, quantities, and properties. includes python bindings for batch processing and summary analytics.

standards-compliance-checker validates construction data against iso 19650, ifc, cobie, uniformat, masterformat, and omniclass via pattern matching and enumerated values. batch processing and custom rule injection supported.

historical-cost-analyzer provides methods for benchmarking construction costs, normalizing by location and year, identifying cost drivers, and detecting overrun patterns. it includes dataclasses for cost benchmarks, escalation analysis, and cost drivers, with a python class wrapping pandas and scipy operations.

data-model-designer provides python code for constructing entity-relationship models in construction projects, generating sql schemas and json representations. lacks procedural guidance for actual usage and minimal edge case handling.

auto-estimate-generator maps bim quantities to pricing rules and produces cost estimates with element-type breakdowns. includes rule matching logic, unmapped item tracking, and excel export but lacks explicit error handling and trigger definitions.

rvt-to-ifc converts revit models to industry foundation classes with support for ifc2x3, ifc4, and ifc4.3 schemas. includes python sdk for batch processing, preset management, and basic output validation.

ifc-data-extraction provides code examples for parsing bim models with ifcopenshell, extracting elements, quantities, materials, and spatial relationships. lacks procedural guidance, trigger conditions, and error handling strategy.

open-data-integrator provides python classes and connectors to fetch construction data from weather, material prices, labor rates, and permits. it includes caching and basic enrichment logic but lacks concrete trigger definitions and actionable integration guidance.

image-to-data extracts structured information from construction photos and documents via ocr, object detection, and progress measurement. the implementation is code-heavy but lacks actionable workflow guidance and error handling.

Extract quantities from IFC/Revit models for quantity takeoff. Uses DDC converters to get element counts, areas, volumes, lengths with grouping and reporting.

Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.

Convert DGN files (v7-v8) to Excel databases. Extract elements, levels, and properties from infrastructure CAD files.

Automated cost estimation from BIM models using DDC CWICR database with 55,719 work items. AI classification + vector search for accurate pricing.

Extract, clean, and organize legacy construction data from archives. Migrate historical project data, cost records, and schedules into modern formats.

Analyze ERP system integration for construction data flows. Map and optimize data flows between ERP modules

Parse and validate JSON data from construction APIs, IoT sensors, and BIM exports. Transform nested JSON to flat DataFrames.

Map construction data to standard ontologies. Create semantic mappings between different data schemas

Convert CAD/BIM files to structured data. Extract element data from Revit, IFC, DWG, DGN files.

Track data origin, transformations, and flow through construction systems. Essential for audit trails, compliance, and debugging data issues.

Build validation rules for construction data. Create RegEx and logic-based validation for BIM elements, cost codes, and schedule data.