Using qualitative spatial logic for validating crowd-sourced geospatial data

Heshan Du, Hai Nguyen, Natasha Alechina, Brian Logan, Michael Jackson, John Goodwin

Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review

Abstract

We describe a tool, MatchMaps, that generates sameAs and partOf matches between spatial objects (such as shops, shopping centres, etc.) in crowd-sourced and authoritative geospatial datasets. MatchMaps uses reasoning in qualitative spatial logic, description logic and truth maintenance techniques, to produce a consistent set of matches. We report the results of an initial evaluation of MatchMaps by experts from Ordnance Survey (Great Britain's National Mapping Authority). In both the case studies considered, MatchMaps was able to correctly match spatial objects (high precision and recall) with minimal human intervention.

Original languageEnglish
Title of host publicationProceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
PublisherAI Access Foundation
Pages3948-3953
Number of pages6
ISBN (Electronic)9781577357032
Publication statusPublished - 1 Jun 2015
Externally publishedYes
Event29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 - Austin, United States
Duration: 25 Jan 201530 Jan 2015

Publication series

SeriesThe Proceedings of the annual AAAI Conference on Artificial Intelligence
Volume5

Conference

Conference29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015
Abbreviated titleIAAI 2015
Country/TerritoryUnited States
CityAustin
Period25/01/1530/01/15

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