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AOSM2022: Integration of Text and Geospatial Search for Hydrographic Datasets Using the Lucene Search Library
Section 1: Publication
Authorship or Presenters
Matthew Yang, Siwen Yang, Jimmy Lin
Integration of Text and Geospatial Search for Hydrographic Datasets Using the Lucene Search Library
Hydrology and Terrestrial Ecosystems
10-minute oral presentation
Matthew Yang, Siwen Yang, Jimmy Lin (2022). Integration of Text and Geospatial Search for Hydrographic Datasets Using the Lucene Search Library. Proceedings of the GWF Annual Open Science Meeting, May 16-18, 2022.
AOSM2022 core Computer Science
Section 2: Abstract
Plain Language Summary
We present a hybrid text and geospatial search application for hydrographic datasets built on the open-source Lucene search library. Our goal is to demonstrate that it is possible to build custom GIS applications by integrating existing open-source components and data sources, which contrasts with existing approaches based on monolithic platforms such as ArcGIS and QGIS.
Lucene provides rich index structures and search capabilities for both free text and geometries; the former has already been integrated and exposed via our group's Anserini and Pyserini IR toolkits. In this work, we extend these toolkits to include geospatial capabilities as well. Combining knowledge extracted from Wikidata with the HydroSHEDS dataset, our application enables text and geospatial search of rivers around the world.
Section 3: Miscellany
University of Waterloo
First Author: Matthew Yang, University of Waterloo
Additional Authors: Siwen Yang, University of Waterloo; Jimmy Lin, University of Waterloo
Section 4: Download
T-2022-04-24-n12kgTcDbOEK4haplm5pSyw Conference Publication 1.0