We extract tourist attractions, seasonal festivals, regional accommodations, and travel itineraries from VisitKorea. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Attractions objects from visitkorea.or.kr. All fields typed and schema-versioned.
"attraction_id": "VK_ATT_94821", "name": "Gyeongbokgung Palace", "region": "Seoul", "category": "Historical Sites", "operating_hours": "09:00 - 18:00", "admission_fee": 3000, "latitude": 37.579617, "longitude": 126.977041
| # | attraction_id | name | region | category | address | phone |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Festivals objects from visitkorea.or.kr. All fields typed and schema-versioned.
"festival_id": "VK_FES_1029", "name": "Jinju Namgang Yudeung Festival", "start_date": "2026-10-01", "end_date": "2026-10-15", "location": "Jinju-si, Gyeongsangnam-do", "fee": "Free (some programs charged)", "website": "yudeung.com"
| # | festival_id | name | theme | start_date | end_date | location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Accommodations objects from visitkorea.or.kr. All fields typed and schema-versioned.
"accommodation_id": "VK_ACC_5512", "name": "Shilla Stay Gwanghwamun", "type": "Hotel", "region": "Seoul", "check_in": "15:00", "check_out": "12:00", "parking": true, "amenities": "['Wi-Fi', 'Fitness Center', 'Restaurant']"
| # | accommodation_id | name | type | region | address | rooms |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Restaurants objects from visitkorea.or.kr. All fields typed and schema-versioned.
"restaurant_id": "VK_RES_8834", "name": "Myeongdong Kyoja", "cuisine": "Korean", "signature_dish": "Kalguksu", "operating_hours": "10:30 - 21:00", "closed_days": "Seollal and Chuseok", "parking": false
| # | restaurant_id | name | cuisine | signature_dish | address | operating_hours |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Itineraries objects from visitkorea.or.kr. All fields typed and schema-versioned.
"itinerary_id": "VK_ITI_442", "title": "3 Days in Busan: Coastal Wonders", "duration": "3 Days", "region": "Busan", "theme": "Nature & Healing", "stops": 12, "transport_mode": "Public Transit", "estimated_cost": 150000
| # | itinerary_id | title | duration | theme | region | stops |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our VisitKorea pipeline captures deep regional data, translating complex site taxonomy and dynamic map elements into structured warehouse records.
Extract operating hours, admission fees, closed days, and detailed historical descriptions for thousands of cultural and natural sites.
Capture start dates, end dates, program schedules, and location coordinates for regional festivals across all provinces.
Extract Hanok stays, hotels, and guesthouse data including amenities, room counts, and official booking links.
Parse embedded map data to extract precise latitude and longitude coordinates for points of interest.
Capture structured data on wheelchair access, braille guides, and accessible restrooms for trip planning applications.
Extract content across English, Japanese, Chinese, and Korean site versions, maintaining ID parity across languages.
Scrape multi-day travel routes, including sequential stops, transit modes, and estimated travel times.
Extract restaurant profiles, signature dishes, menu translations, and operating hours for certified local eateries.
Run pipelines monthly or quarterly to capture new festival dates and seasonal attraction changes without full re-crawls.
Brief in. Clean data out.
Specify desired regions, categories (e.g., festivals, heritage sites), or language versions. We design the schema.
We configure crawlers to navigate VisitKorea's nested category menus and dynamic map interfaces.
Schema validation, coordinate accuracy checks, and null-rate monitoring before deployment.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage.
Government tourism portals often rely on complex legacy architectures and heavy client-side rendering. We handle the extraction logic.
VisitKorea embeds location data within JavaScript map initialisation blocks rather than standard HTML attributes. Our Playwright instances execute the page scripts to intercept and extract clean latitude and longitude values.
Tourism data is buried under multiple layers of region, sub-region, and theme filters. We map the entire category tree and maintain stateful crawls to ensure zero data loss during pagination.
The site structure often differs slightly between the Korean and English versions. We use internal content IDs to normalise records, allowing you to query the same attraction across different language datasets.
Festival URLs frequently change or expire after the event concludes. We track historical URLs and implement change detection to flag events as completed rather than throwing 404 errors in your dataset.
Government servers employ strict rate limiting. We optimise request concurrency and rotate Korean datacenter IPs to maintain steady extraction velocity without triggering firewall blocks.
OTA platforms ingest attraction and festival data to populate destination guides and cross-sell local experiences.
LLM startups use structured points-of-interest and itinerary data to train and ground their travel recommendation models.
Navigation providers integrate tourist coordinates and accessibility data to improve local routing for foreign visitors.
Consultancies track the growth of regional festivals and accommodation density to evaluate tourism investment opportunities.
MICE industry professionals monitor local cultural events to align corporate retreats with regional festivals.
Researchers analyse tourism distribution and seasonal attraction availability to study regional economic impact.
"VisitKorea holds the definitive dataset for South Korean tourism, but extracting multilingual itineraries and geodata at scale requires dedicated infrastructure."
Extracting data from government tourism portals involves navigating complex taxonomy structures, dynamic map integrations, and frequent seasonal updates. DataFlirt manages the extraction pipeline so your engineering team can focus on product development rather than maintaining fragile scripts.
Everything supported by our visitkorea.or.kr scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy and Redis handle complex pagination across nested regional categories, ensuring complete coverage of the VisitKorea taxonomy without duplicate requests.
Playwright clusters execute JavaScript to render map components and interactive itinerary timelines, capturing data hidden from standard HTTP requests.
Airflow triggers validation checks post-crawl, verifying coordinate boundaries and null rates for critical fields like admission fees and operating hours.
Data delivered to where your team already works — no new tooling required.
About visitkorea.or.kr scraping, legality, and pipeline operations.
Ask us directly →Yes. We can target specific language versions of VisitKorea (English, Korean, Japanese, Chinese) or extract them concurrently. We use internal reference IDs to link the same attraction across different languages.
For core attractions and cultural sites, a quarterly refresh is typically sufficient. For seasonal festivals, event schedules, and temporary exhibitions, we recommend monthly or bi-weekly pipelines.
Yes. We parse the embedded map scripts on attraction and accommodation pages to extract precise latitude and longitude values, delivering them as standard float fields in your database.
Yes. We use Playwright to execute the client-side JavaScript required to load sequential itinerary stops and transit routes, capturing the structured data behind the visual map.
Our minimum engagement covers a full extraction of a specific category (e.g., all attractions or all accommodations) for a single language. Contact us for precise scoping based on your data volume.
Yes. We provide a sample run covering a specific region (e.g., Jeju or Busan) to allow your team to validate our schema and coordinate accuracy before committing to a full pipeline.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a complete dump of national heritage sites or a recurring feed of seasonal festivals — we scope, build, and operate the pipeline. Tell us what you need.
