Using qualitative spatial logic for validating crowd-sourced geospatial data

Du, Heshan; Nguyen, Hai Hoang; Alechina, Natasha; Logan, Brian; Jackson, Mike; Goodwin, John

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 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.

Citation

Du, H., Nguyen, H. H., Alechina, N., Logan, B., Jackson, M., & Goodwin, J. Using qualitative spatial logic for validating crowd-sourced geospatial data. Presented at Innovative Applications of Artificial Intelligence (IAAI-15)

• Conference Name: Innovative Applications of Artificial Intelligence (IAAI-15)
• End Date: Jan 29, 2015
• Publication Date: Jan 25, 2015
• Deposit Date: Sep 18, 2015
• Publicly Available Date: Sep 18, 2015
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/742661
• Publisher URL: http://www.aaai.org/ocs/index.php/IAAI/IAAI15/paper/view/9687
• Additional Information: Published in: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence and the Twenty-Seventh Innovative Applications of Artificial Intelligence Conference: 25-30 January 2015, Austin, Texas, USA. Palo Alto, Calif. : AAAI Press, 2015, ISBN: 9781577356981, pp. 3948-3953