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An ontology-based algorithm for managing the evolution of multi-level territorial partitions

Authors:

Camille Bernard,

Christine Plumejeaud-Perreau,

Marlène Villanova-Oliver,

Jérôme Gensel,

Hy DaoAuthors Info & Claims

SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Pages 456 - 459

https://doi.org/10.1145/3274895.3274944

Published: 06 November 2018 Publication History

Abstract

Through times, regions all over the world are very often subject to change (their names, their belonging, their composition, and their geometries). In this paper, we present a Semantic Matching Algorithm for automatically detecting, describing and publishing in the Linked Open Data Web, rich descriptions of changes occurring in multi-level territorial partitions (e.g., partitions made of major regions, regions and districts levels). We adopt a Linked Data (LD) approach for the semantic descriptions of the changes they undergo, relying on two existing generic ontologies, TSN-Ontology and TSN-Change Ontology. The created RDF graphs draw the lineage of each region over time (horizontal reading of the graphs), as well as the propagation of a change event through the partition levels (vertical reading).

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Camille Bernard, Marlène Villanova-Oliver, Jérôme Gensel, and Hy Dao. 2018. Modeling Changes in Territorial Partitions Over Time: Ontologies TSN and TSN-change. In Proceedings of the 33rd Annual ACM Symposium on Applied Computing (SAC '18). ACM, 866--875.

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Cited By

Shbita BKnoblock CDuan WChiang YUhl JLeyk S(2023)Building spatio-temporal knowledge graphs from vectorized topographic historical mapsSemantic Web10.3233/SW-22291814:3(527-549)Online publication date: 5-Apr-2023
https://doi.org/10.3233/SW-222918
Mai GHu YGao SCai LMartins BScholz JGao JJanowicz K(2022) Symbolic and subsymbolic GeoAI : Geospatial knowledge graphs and spatially explicit machine learning Transactions in GIS10.1111/tgis.1301226:8(3118-3124)Online publication date: 18-Dec-2022
https://doi.org/10.1111/tgis.13012
Bernard CVillanova‐Oliver MGensel J(2022)Theseus: A framework for managing knowledge graphs about geographical divisions and their evolutionTransactions in GIS10.1111/tgis.1298826:8(3202-3224)Online publication date: 23-Sep-2022
https://doi.org/10.1111/tgis.12988
Show More Cited By

Index Terms

An ontology-based algorithm for managing the evolution of multi-level territorial partitions
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
  2. World Wide Web
    1. Web data description languages

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Information & Contributors

Information

Published In

cover image ACM Conferences

SIGSPATIAL '18: Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 2018

655 pages

ISBN:9781450358897

DOI:10.1145/3274895

General Chairs:
Farnoush Banaei-Kashani
University of Colorado, Denver
,
Erik Hoel
Esri
,
Program Chairs:
Ralf Hartmut Güting
FernUniversität in Hagen, Germany
,
Roberto Tamassia
Brown University
,
Li Xiong
Emory University

Copyright © 2018 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2018

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SIGSPATIAL '18

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SIGSPATIAL

SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 6 - 9, 2018

Washington, Seattle

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SIGSPATIAL '18 Paper Acceptance Rate 30 of 150 submissions, 20%;

Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

Shbita BKnoblock CDuan WChiang YUhl JLeyk S(2023)Building spatio-temporal knowledge graphs from vectorized topographic historical mapsSemantic Web10.3233/SW-22291814:3(527-549)Online publication date: 5-Apr-2023
https://doi.org/10.3233/SW-222918
Mai GHu YGao SCai LMartins BScholz JGao JJanowicz K(2022) Symbolic and subsymbolic GeoAI : Geospatial knowledge graphs and spatially explicit machine learning Transactions in GIS10.1111/tgis.1301226:8(3118-3124)Online publication date: 18-Dec-2022
https://doi.org/10.1111/tgis.13012
Bernard CVillanova‐Oliver MGensel J(2022)Theseus: A framework for managing knowledge graphs about geographical divisions and their evolutionTransactions in GIS10.1111/tgis.1298826:8(3202-3224)Online publication date: 23-Sep-2022
https://doi.org/10.1111/tgis.12988
Bernard CPlumejeaud-Perreau CVillanova-Oliver MGensel JDao H(2020)Semantic Graphs to Reflect the Evolution of Geographic DivisionsHandbook of Big Geospatial Data10.1007/978-3-030-55462-0_6(135-159)Online publication date: 17-Dec-2020
https://doi.org/10.1007/978-3-030-55462-0_6
Shbita BKnoblock CDuan WChiang YUhl JLeyk S(2020)Building Linked Spatio-Temporal Data from Vectorized Historical MapsThe Semantic Web10.1007/978-3-030-49461-2_24(409-426)Online publication date: 27-May-2020
https://doi.org/10.1007/978-3-030-49461-2_24

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