FISETIO: A FIne-grained, Structured and Enriched Tourism Dataset for Indoor and Outdoor attractions

Published: 21 June 2019| Version 1 | DOI: 10.17632/t7bfhtzhxg.1
Amir Khatibi,
Ana Couto,
Jussara Almeida,
M.A. Gonçalves


This data in brief paper introduces our publicly available datasets in the area of tourism demand prediction for future experiments and comparisons. Most previous works in the area of tourism demand forecasting are based on coarse- grained analysis (level of countries or regions) and there are very few works and datasets available for fine-grained tourism analysis as well (level of attractions and points of interest). In this article, we present our fine-grained datasets for two types of attractions – (I) indoor attractions (27 Museums and Galleries in U.K.) and (II) outdoor attractions (76 U.S. National Parks) enriched with official number of visits, social media reviews and environmental data for each of them. In addition, the complete analysis of prediction results, methodology and exploited models, features’ performance analysis, anomalies, etc, are available in our original paper



Tourism, Climate Data, Social Media Analytics