skip to main content
10.1145/3340964.3340976acmotherconferencesArticle/Chapter ViewAbstractPublication PagessstdConference Proceedingsconference-collections
research-article

Exposing Points of Interest as Linked Geospatial Data

Published: 19 August 2019 Publication History

Abstract

Point of Interest (POI) data is widely used in many modern applications and services related to navigation, tourism, social networking, logistics, and many more. In this paper, we propose a comprehensive and vendor-agnostic data model to represent multi-faceted and enriched POI profiles. Harnessing the versatility of Linked Data technologies, this semantically rich ontology accommodates and extends existing POI formats for assembling and managing POI data from heterogeneous sources. Furthermore, we have developed the open-source software TripleGeo, which can effectively transform POI data from diverse sources and formats (geographical files, databases, and semi-structured data) to their RDF representations and vice versa. Thus, it is possible to import POI data from various existing systems and products, transfer and address the data integration challenges in the Linked Data domain, and export back the results. Our empirical study confirms the validity and efficiency of this framework for a variety of real-world POI assets and formats, underscoring its robustness to cope with scalable data volumes.

References

[1]
S. Athanasiou, G. Giannopoulos, D. Graux, N. Karagiannakis, J. Lehmann, A. C. Ngonga Ngomo, K. Patroumpas, M. A. Sherif, and D. Skoutas. Big POI Data Integration with Linked Data Technologies. In EDBT, pp. 477--488, 2019.
[2]
S. Athanasiou, M. Alexakis, G. Giannopoulos, N. Karagiannakis, Y. Kouvaras, P. Mitropoulos, K. Patroumpas, and D. Skoutas. SLIPO: Large-Scale Data Integration for Points of Interest. In EDBT, pp. 574--577, 2019.
[3]
K. Bereta and M. Koubarakis. Ontop of Geospatial Databases. In ISWC, pp. 37--52, 2016.
[4]
A. Dimou, M. van der Sande, P. Colpaert, R. Verborgh, E. Mannens, and R. van de Walle. RML: A Generic Language for Integrated RDF Mappings of Heterogeneous Data. In LDOW, 2014.
[5]
A. Dimou, D. Kontokostas, M. Freudenberg, R. Verborgh, J. Lehmann, E. Mannens, S. Hellmann, and R. Van de Walle. Assessing and Refining Mappings to RDF to Improve Dataset Quality. In ISWC, pp. 133--149, 2015.
[6]
F. Hamdi, N. Abadie, B. Bucher, and A. Feliachi. GeomRDF: A Geodata Converter with a Fine-Grained Structured Representation of Geometry in the Web. In GeoLD, 2014.
[7]
K. Kyzirakos, I. Vlachopoulos, D. Savva, S. Manegold and M. Koubarakis. GeoTriples: a Tool for Publishing Geospatial Data as RDF Graphs Using R2RML Mappings. In Terra Cognita, 2014.
[8]
K. Kyzirakos, D. Savva, I. Vlachopoulos, A. Vasileiou, N. Karalis, M. Koubarakis, and S. Manegold. GeoTriples: Transforming Geospatial Data into RDF Graphs Using R2RML and RML Mappings. Journal of Web Semantics, 52-53: 16--32, 2018.
[9]
K. Patroumpas, M. Alexakis, G. Giannopoulos, and S. Athanasiou. TripleGeo: an ETL Tool for Transforming Geospatial Data into RDF Triples. In LWDM, 2014.
[10]
K. Patroumpas, N. Georgomanolis, T. Stratiotis, M. Alexakis, S. Athanasiou. Exposing INSPIRE on the Semantic Web. Journal of Web Semantics, 35: 53--62, 2015.
[11]
M. Rodriguez-Muro and M. Rezk. Efficient SPARQL-to-SQL with R2RML mappings. Journal of Web Semantics, 33: 141--169, 2015.
[12]
J. Unbehauen, S. Hellmann, S. Auer, and C. Stadler. Knowledge Extraction from Structured Sources. In Search Computing, pp. 34--52, 2012.
[13]
L.M. Vilches-Blázquez, B. Villazón-Terrazas, V. Saquicela, A. de León, O. Corcho, and A. Gómez-Pérez. GeoLinked Data and INSPIRE through an Application Case. In ACM SIGSPATIAL, pp. 446--449, 2010.
[14]
J. Yu, Z. Zhang, and M. Sarwat. Spatial Data Management in Apache Spark: the GeoSpark Perspective and Beyond. GeoInformatica. 2018.

Cited By

View all
  • (2024)Semantic Data Integration and Querying: A Survey and ChallengesACM Computing Surveys10.1145/365331756:8(1-35)Online publication date: 26-Apr-2024
  • (2024)Large-scale Generation of Transit Maps from OpenStreetMap DataThe Cartographic Journal10.1080/00087041.2024.232576160:4(342-366)Online publication date: 2-Jul-2024
  • (2024)Construct and Query A Fine-Grained Geospatial Knowledge GraphData Science and Engineering10.1007/s41019-023-00237-49:2(152-176)Online publication date: 22-Jan-2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
SSTD '19: Proceedings of the 16th International Symposium on Spatial and Temporal Databases
August 2019
245 pages
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 the author(s) 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].

In-Cooperation

  • TU Wien: TU Wien

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 August 2019

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. POI
  2. RDF
  3. linked geospatial data
  4. ontology
  5. transformation

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

SSTD '19

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)16
  • Downloads (Last 6 weeks)1
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Semantic Data Integration and Querying: A Survey and ChallengesACM Computing Surveys10.1145/365331756:8(1-35)Online publication date: 26-Apr-2024
  • (2024)Large-scale Generation of Transit Maps from OpenStreetMap DataThe Cartographic Journal10.1080/00087041.2024.232576160:4(342-366)Online publication date: 2-Jul-2024
  • (2024)Construct and Query A Fine-Grained Geospatial Knowledge GraphData Science and Engineering10.1007/s41019-023-00237-49:2(152-176)Online publication date: 22-Jan-2024
  • (2023)POI Verilerinin Semantik Tanımlarının Oluşturulması ve GörselleştirilmesiGenerating Semantic Definitions and Visualization of POI DataTurkish Journal of Remote Sensing and GIS10.48123/rsgis.1254438(213-230)Online publication date: 26-May-2023
  • (2023)WISK: A Workload-aware Learned Index for Spatial Keyword QueriesProceedings of the ACM on Management of Data10.1145/35893321:2(1-27)Online publication date: 20-Jun-2023
  • (2023)Construct Fine-Grained Geospatial Knowledge GraphDatabase Systems for Advanced Applications. DASFAA 2023 International Workshops10.1007/978-3-031-35415-1_19(267-282)Online publication date: 28-Sep-2023
  • (2023)Geospatial Data ScienceundefinedOnline publication date: 9-Jun-2023
  • (2022)Automatic generation of sailing holiday itineraries using vessel density data and semantic technologiesInformation Technology & Tourism10.1007/s40558-022-00224-x24:2(265-298)Online publication date: 15-Mar-2022
  • (2022)Enhanced-Sweep: Communication Cost Efficient Top-K Best Region SearchArabian Journal for Science and Engineering10.1007/s13369-022-07084-x48:2(2121-2132)Online publication date: 12-Aug-2022
  • (2022)Towards the FAIRification of Meteorological Data: A Meteorological Semantic ModelMetadata and Semantic Research10.1007/978-3-030-98876-0_7(81-93)Online publication date: 1-Apr-2022
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media