Spot: A Natural Language Interface for Geospatial Searches in OSM
Lynn Khellaf Ipek Baris Schlicht Julia Bayer Ruben Bouwmeester Tilman Miraß Tilman Wagner
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.