Lesson 1Location-based services and GPS traces: accuracy trade-offs, frequency, battery considerations, and cleaning methodsExplores location-based services and GPS traces as fine-grained mobility data. Discusses accuracy, sampling frequency, battery impact, map-matching, and cleaning noisy trajectories for reliable tourism flow and POI visit analysis.
GPS accuracy, drift, and indoor limitationsSampling frequency and battery trade-offsMap-matching to roads and pedestrian pathsDetecting stops, trips, and POI visitsFiltering noise and outlier trajectoriesLesson 2Survey and intercept instruments: design of short in-app and on-site surveys, sampling strategies, frequency, and response biasFocuses on survey and intercept tools for tourism insights, from short in-app forms to on-site questionnaires. Explains questionnaire design, sampling strategies, timing, incentives, and how to reduce response bias and survey fatigue.
Defining survey objectives and key metricsQuestion wording, scales, and survey lengthOn-site, online, and in-app recruitmentSampling frames, quotas, and weightingNonresponse, recall, and social desirability biasLesson 3App telemetry and SDK data: location, session, POI visits, opt-in, sampling bias, and update cadenceDescribes app telemetry and SDK data used in tourism apps, including sessions, screens, and POI visits. Covers consent flows, opt-in rates, sampling strategies, update cadence, and how to avoid dark patterns and privacy risks.
Session, screen, and event instrumentationLocation and POI visit logging in appsConsent flows, opt-in, and transparencySampling, throttling, and data volume controlUpdate cadence and SDK governanceLesson 4Legal, privacy, and ethical constraints: GDPR-equivalent frameworks, anonymisation, differential privacy basics, and data retention policiesAddresses legal, privacy, and ethical aspects of tourism data. Reviews GDPR-like frameworks, lawful bases, anonymisation, differential privacy basics, retention limits, and ethical guidelines for responsible data-driven governance.
Lawful bases for processing tourism dataData minimization and purpose limitationAnonymization and pseudonymization methodsDifferential privacy concepts and use casesRetention schedules and deletion policiesLesson 5Mobile network and CDR-derived insights: what they reveal (origin, flows, dwell time), temporal resolution, access channels, and privacy/legal constraintsDetails mobile network and CDR-based tourism insights, such as origin markets, flows, and dwell times. Discusses spatial and temporal resolution, access models, aggregation, and strict privacy, consent, and regulatory requirements.
CDR structure, events, and aggregation levelsOrigin–destination matrices and visitor flowsDwell time estimation and stay classificationTemporal resolution and representativenessPrivacy, consent, and regulatory constraintsLesson 6Booking and reservation platforms data: occupancy, arrival/departure windows, booking lead times, and data sharing agreementsExamines data from booking platforms and channel managers, including occupancy, lead times, and stay patterns. Focuses on access options, data-sharing contracts, bias sources, and how to transform raw reservations into tourism intelligence.
Occupancy, ADR, and length-of-stay indicatorsArrival and departure windows by segmentBooking lead times and demand forecastingAPIs, exports, and channel manager feedsData sharing agreements and governanceLesson 7Open and administrative data: transport timetables, event permits, environmental datasets, and update schedulesExplores open and administrative datasets for tourism, including transport, events, and environment. Covers formats, update cycles, licensing, and how to assess reliability, completeness, and fitness for operational and strategic use.
Transport timetables and service calendarsEvent permits and cultural agenda datasetsEnvironmental and climate open data portalsLicensing, reuse rights, and attribution rulesUpdate frequency, versioning, and data qualityLesson 8Social media and UGC analytics: geo-tagged posts, sentiment, topic extraction, sampling bias, and API limitsCovers social media and UGC as tourism data, including geo-tagged posts, reviews, and photos. Addresses sentiment and topic extraction, platform APIs, sampling bias, and how to responsibly interpret signals for destination management.
Geo-tagged posts and place-based activityReview text, ratings, and photo metadataSentiment and emotion analysis techniquesTopic modeling and trend detectionSampling bias, bots, and API limitationsLesson 9Sensor and IoT data (counters, BLE, Wi-Fi probes): installation sites, calibration, maintenance, and near real-time retrievalCovers sensor and IoT data for smart destinations, such as counters, BLE beacons, and Wi-Fi probes. Discusses installation design, calibration, maintenance, edge processing, and near real-time data pipelines for operations.
People counters and camera-based systemsBLE beacons and Wi‑Fi probe collectionSite selection, coverage, and interferenceCalibration, testing, and maintenance plansStreaming, buffering, and real-time accessLesson 10Data linkage and provenance: identifiers, temporal alignment, aggregation levels, and techniques for combining heterogeneous sourcesExplains how to link heterogeneous tourism datasets while preserving provenance. Covers identifiers, temporal alignment, spatial aggregation, and methods to combine sources without overfitting, double counting, or privacy breaches.
Stable identifiers and pseudonymous keysTemporal alignment and time-window choicesSpatial aggregation and zoning decisionsRecord linkage and fusion techniquesProvenance tracking and audit trails
