Handling Uncertainty in Geo-Spatial Data

Züfle, Andreas; Trajcevski, Goce; Pfoser, Dieter; Renz, Matthias; Rice, Matthew T.; Leslie, Timothy; Delamater, Paul and Emrich, Tobias (2017): Handling Uncertainty in Geo-Spatial Data. 2017 IEEE 33rd International Conference on Data Engineering (ICDE), San Diego, CA, 19-22 April 2017. Institute of Electrical and Electronics Engineers (ed.) , In: CDE 2017 : 2017 IEEE 33rd International Conference on Data Engineering : 19-22 April 2017, San Diego, California, USA : proceedings, Piscataway, NJ: IEEE. pp. 1467-1470

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.

• Item Type: Conference or Workshop Item (Paper)
• Faculties: Mathematics, Computer Science and Statistics > Computer Science
• Subjects: 000 Computer science, information and general works > 004 Data processing computer science
• Place of Publication: Piscataway, NJ
• Annotation: ISBN 978-1-5090-6543-1
• Language: English