MuseumSpark - Technical Summary MuseumSpark is an intelligent travel planning platform that transforms the Walker Art Center Reciprocal Program's museum membership roster into a data-rich, searchable resource for art enthusiasts across North America. The project curates and enriches data on 1,269 museums through a sophisticated multi-phase pipeline, enabling users to discover, prioritize, and plan visits based on artistic strength, collection focus (Impressionist/Modern/Contemporary), and travel logistics. Built with a modern React 19 + Vite frontend for browsing and filtering museums, the platform leverages a Python-based data enrichment architecture that aggregates information from Wikidata, Wikipedia, museum websites, and structured metadata sources, with validation enforced through JSON Schema and Pydantic models. The project follows a deliberate phase-based roadmap: currently completing Phase 1 (data foundation with 0.08% enrichment), transitioning to Phase 2 (expert scoring of collections), Phase 2.5–3 (AI-assisted content analysis using Claude/OpenAI), and Phase 4 (full interactive platform with FastAPI backend, user authentication, and trip planning). What distinguishes MuseumSpark is its data-first approach to travel planning, combining transparent progress tracking, rigorous quality assurance (including a "never replace known with null" policy), and planned AI integration for personalized itinerary generation—targeting art-focused travelers who want strategic, curated museum experiences rather than generic directories. The project demonstrates strong engineering discipline with modular pipeline stages, multi-language support (46.8% Python for data, 25.4% TypeScript for frontend), and clear separation of concerns between data transformation, validation, and user-facing presentation.