Investigative journalists and fact-checkers have found OpenStreetMap (OSM) to be an invaluable resource for their work due to its extensive coverage and intricate details of various locations, which play a crucial role in investigating news scenes. Despite its value, OSM's complexity presents considerable accessibility and usability challenges, especially for those without a technical background. To address this, we introduce 'Spot', a user-friendly natural language interface for querying OSM data. Spot utilizes a semantic mapping from natural language to OSM tags, leveraging artificially generated sentence queries and a T5 transformer. This approach enables Spot to extract relevant information from user-input sentences and display candidate locations matching the descriptions on a map. To foster collaboration and future advancement, all code and generated data is available as an open-source repository.
Cite
@article{arxiv.2311.08093,
title = {Spot: A Natural Language Interface for Geospatial Searches in OSM},
author = {Lynn Khellaf and Ipek Baris Schlicht and Julia Bayer and Ruben Bouwmeester and Tilman Miraß and Tilman Wagner},
journal= {arXiv preprint arXiv:2311.08093},
year = {2023}
}
Comments
To be published in the Proceedings of the OSM Science 2023