Demonstrating spindra: A geographic knowledge graph management system

Yuhan Sun, Jia Yu, Mohamed Elsayed

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations


Knowledge Graphs are widely used to store facts about real-world entities and events. With the ubiquity of spatial data, vertexes or edges in knowledge graphs can possess spatial location attributes side by side with other non-spatial attributes. For instance, as of June 2018 the Wikidata knowledge graph contains 48; 547; 142 data items (i.e., vertexes) to date and ≈13% of them have spatial location attributes. The co-existence of the graph and spatial data in the same geographic knowledge graph allows users to search the graph with local intent. Many location-based services such as UberEats, GrubHub, and Yelp already employ similar knowledge graphs to enhance the location search experience for their end-users. In this paper, we demonstrate a system, namely Spindra, that provides efficient management of geographic knowledge graphs. We demonstrate the system using an interactive map-based web interface that allows users to issue location-aware search queries over the WikiData knowledge graph. The Front end will then visualize the returned geographic knowledge to the user using OpenStreetMaps.

Original languageEnglish (US)
Title of host publicationProceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9781538674741
StatePublished - Apr 1 2019
Event35th IEEE International Conference on Data Engineering, ICDE 2019 - Macau, China
Duration: Apr 8 2019Apr 11 2019

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Conference35th IEEE International Conference on Data Engineering, ICDE 2019


  • Graph search
  • Index
  • Knowledge graph
  • Spatial data

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems


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