Dataset and Computational Outputs for: An Adaptive Computational GIS Framework for Tourism Hotspot Discovery in Data-Scarce Contexts—Sudan Geo-Tagged Flickr Metadata as a Case Study

This repository contains the processed research data, computational outputs, and supporting materials associated with the study titled “An Adaptive Computational GIS Framework for Tourism Hotspot Discovery in Data-Scarce Contexts: Sudan Geo-Tagged Flickr Metadata as a Case Study.” The study investigates the use of geo-tagged Flickr metadata for identifying spatial and temporal patterns of digital tourism visibility in Sudan during the pre-war baseline period from 2002 to 2019. The original data were collected through the Flickr API using a custom PHP–MySQL data acquisition system and were subsequently cleaned, filtered, analysed, and validated using Python, Google Colab, GIS software, OpenStreetMap, and Wikidata resources. The deposited materials may include processed and anonymised data tables, DBSCAN clustering outputs, tourism hotspot summaries, spatial validation results, statistical outputs, maps, figures, analysis scripts, and documentation describing the variables and computational workflow. The repository is intended to support research transparency, reproducibility, and the reuse of the proposed Computational GIS framework in other data-scarce geographic and tourism contexts. Personally identifiable user information and copyrighted Flickr images are not included. Users of these materials should cite both this Zenodo record and the associated scientific publication when available.