Handling uncertainty in geo-spatial data

Andreas Züfle, Goce Trajcevski, Dieter Pfoser, Matthias Renz, Matthew T. Rice, Timothy Leslie, Paul Delamater, Tobias Emrich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

An inherent challenge arising in any dataset containing information of space and/or time is uncertainty due to various sources of imprecision. Integrating the impact of the uncertainty is a paramount when estimating the reliability (confidence) of any query result from the underlying input data. To deal with uncertainty, solutions have been proposed independently in the geo-science and the data-science research community. This interdisciplinary tutorial bridges the gap between the two communities by providing a comprehensive overview of the different challenges involved in dealing with uncertain geo-spatial data, by surveying solutions from both research communities, and by identifying similarities, synergies and open research problems.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017
PublisherIEEE Computer Society
Pages1467-1470
Number of pages4
ISBN (Electronic)9781509065431
DOIs
StatePublished - May 16 2017
Event33rd IEEE International Conference on Data Engineering, ICDE 2017 - San Diego, United States
Duration: Apr 19 2017Apr 22 2017

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627

Other

Other33rd IEEE International Conference on Data Engineering, ICDE 2017
CountryUnited States
CitySan Diego
Period4/19/174/22/17

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems

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