research-article

Assessment of the accuracy of GeoNames gazetteer data

Author:

Dirk AhlersAuthors Info & Claims

GIR '13: Proceedings of the 7th Workshop on Geographic Information Retrieval

Pages 74 - 81

https://doi.org/10.1145/2533888.2533938

Published: 05 November 2013 Publication History

Abstract

Gazetteers are the basis of many geospatial applications and serve an important role to collect and make available knowledge about the physical world such as place names and their coordinates. GeoNames is one of the largest and most often used gazetteer and it is generally assumed to be of sufficient quality. In this paper, we examine the quality and accuracy of the data in more detail, triggered by some anomalies encountered during its use. We present a classification of inaccuracies ranging from grid patterns, imprecise coordinates, overlaps and repetitions as well as misclassifications and visualize these for a range of countries. We finally give an outlook into potential corrections.

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Cited By

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https://doi.org/10.1038/s40494-025-01598-x
Mao RGe MHan SLi WHe KZhu LCambria E(2025)A survey on pragmatic processing techniquesInformation Fusion10.1016/j.inffus.2024.102712114(102712)Online publication date: Feb-2025
https://doi.org/10.1016/j.inffus.2024.102712
Bartalesi VPratelli N(2024)Representing Geospatial Knowledge in NarrativesJournal on Computing and Cultural Heritage 10.1145/370391818:1(1-15)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3703918
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Index Terms

Assessment of the accuracy of GeoNames gazetteer data
1. Information systems
  1. Information retrieval

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cover image ACM Conferences

GIR '13: Proceedings of the 7th Workshop on Geographic Information Retrieval

November 2013

92 pages

ISBN:9781450322416

DOI:10.1145/2533888

Editors:
Chris Jones
Cardiff University
,
Ross Purves
University of Zurich

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 November 2013

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Seventh Framework Programme

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SIGSPATIAL'13

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SIGSPATIAL

SIGSPATIAL'13: 21st SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 5, 2013

Florida, Orlando

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Overall Acceptance Rate 46 of 61 submissions, 75%

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Cited By

Larsson ÅBornsäter BHacke M(2025)Developing practices for FAIR and linked data in Heritage Sciencenpj Heritage Science10.1038/s40494-025-01598-x13:1Online publication date: 1-Mar-2025
https://doi.org/10.1038/s40494-025-01598-x
Mao RGe MHan SLi WHe KZhu LCambria E(2025)A survey on pragmatic processing techniquesInformation Fusion10.1016/j.inffus.2024.102712114(102712)Online publication date: Feb-2025
https://doi.org/10.1016/j.inffus.2024.102712
Bartalesi VPratelli N(2024)Representing Geospatial Knowledge in NarrativesJournal on Computing and Cultural Heritage 10.1145/370391818:1(1-15)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3703918
Mai GHuang WSun JSong SMishra DLiu NGao SLiu TCong GHu YCundy CLi ZZhu RLao N(2024)On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/365307010:2(1-46)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3653070
Yao YLiu Y(2024)The Construction of a Mountain Vegetation Knowledge Graph Incorporating With Geographical Principles, Maps, and Remote Sensing ImagesIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2024.349345562(1-15)Online publication date: 2024
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Mao RHe KZhang XChen GNi JYang ZCambria E(2024)A survey on semantic processing techniquesInformation Fusion10.1016/j.inffus.2023.101988101(101988)Online publication date: Jan-2024
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Bui T(2023)Estimating Bounding Box for Point of Interest Using Social Media Geo-Tagged PhotosIEEE Access10.1109/ACCESS.2023.323901411(7837-7849)Online publication date: 2023
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Willinger DGötz FStieger S(2023)ecolo-zip: A global, rich and granular characterization of biogeophysical ecology for 1.5 million postal codesScientific Data10.1038/s41597-023-02579-010:1Online publication date: 29-Sep-2023
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