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Situation-Dependent Data Quality Analysis for Geospatial Data Using Semantic Technologies

  • Timo HomburgEmail author
  • Frank Boochs
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 339)

Abstract

In this paper we present a new way to evaluate geospatial data quality using Semantic technologies. In contrast to non-semantic approaches to evaluate data quality, Semantic technologies allow us to model situations in which geospatial data may be used and to apply costumized geospatial data quality models using reasoning algorithms on a broad scale. We explain how to model data quality using common vocabularies of ontologies in various contexts, apply data quality results using reasoning in a real-world application case using OpenStreetMap as our data source and highlight the results of our findings on the example of disaster management planning for rescue forces. We contribute to the Semantic Web community and the OpenStreetMap community by proposing a semantic framework to combine usecase dependent data quality assignments which can be used as reasoning rules and as data quality assurance tools for both communities respectively.

Keywords

Data quality GIS Reference data Machine learning OpenStreetMap 

Notes

Acknowledgements

This work was funded by the German Federal Ministry of Education and Research under project reference number 03FH032IX4.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Mainz University of Applied SciencesMainzGermany

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