Using qualitative spatial logic for validating crowd-sourced geospatial data

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, t...

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Main Authors: Du, Heshan, Nguyen, Hai Hoang, Alechina, Natasha, Logan, Brian, Jackson, Mike, Goodwin, John
Format: Conference or Workshop Item
Published: 2015
Online Access:https://eprints.nottingham.ac.uk/30166/
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author Du, Heshan
Nguyen, Hai Hoang
Alechina, Natasha
Logan, Brian
Jackson, Mike
Goodwin, John
author_facet Du, Heshan
Nguyen, Hai Hoang
Alechina, Natasha
Logan, Brian
Jackson, Mike
Goodwin, John
author_sort Du, Heshan
building Nottingham Research Data Repository
collection Online Access
description 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 eval- uation 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.
first_indexed 2025-11-14T19:08:11Z
format Conference or Workshop Item
id nottingham-30166
institution University of Nottingham Malaysia Campus
institution_category Local University
last_indexed 2025-11-14T19:08:11Z
publishDate 2015
recordtype eprints
repository_type Digital Repository
spelling nottingham-301662020-05-04T17:00:16Z https://eprints.nottingham.ac.uk/30166/ Using qualitative spatial logic for validating crowd-sourced geospatial data Du, Heshan Nguyen, Hai Hoang Alechina, Natasha Logan, Brian Jackson, Mike Goodwin, John 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 eval- uation 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. 2015-01-25 Conference or Workshop Item PeerReviewed Du, Heshan, Nguyen, Hai Hoang, Alechina, Natasha, Logan, Brian, Jackson, Mike and Goodwin, John (2015) Using qualitative spatial logic for validating crowd-sourced geospatial data. In: Innovative Applications of Artificial Intelligence (IAAI-15), 25-29 Jan 2015, Austin, Texas, USA. http://www.aaai.org/ocs/index.php/IAAI/IAAI15/paper/view/9687
spellingShingle Du, Heshan
Nguyen, Hai Hoang
Alechina, Natasha
Logan, Brian
Jackson, Mike
Goodwin, John
Using qualitative spatial logic for validating crowd-sourced geospatial data
title Using qualitative spatial logic for validating crowd-sourced geospatial data
title_full Using qualitative spatial logic for validating crowd-sourced geospatial data
title_fullStr Using qualitative spatial logic for validating crowd-sourced geospatial data
title_full_unstemmed Using qualitative spatial logic for validating crowd-sourced geospatial data
title_short Using qualitative spatial logic for validating crowd-sourced geospatial data
title_sort using qualitative spatial logic for validating crowd-sourced geospatial data
url https://eprints.nottingham.ac.uk/30166/
https://eprints.nottingham.ac.uk/30166/