@inproceedings{4f2e84049dc843438808bdf23b86b31b,
title = "Handling uncertainty in geo-spatial data",
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.",
author = "Andreas Z{\"u}fle and Goce Trajcevski and Dieter Pfoser and Matthias Renz and Rice, {Matthew T.} and Timothy Leslie and Paul Delamater and Tobias Emrich",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 33rd IEEE International Conference on Data Engineering, ICDE 2017 ; Conference date: 19-04-2017 Through 22-04-2017",
year = "2017",
month = may,
day = "16",
doi = "10.1109/ICDE.2017.212",
language = "English (US)",
series = "Proceedings - International Conference on Data Engineering",
publisher = "IEEE Computer Society",
pages = "1467--1470",
booktitle = "Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017",
address = "United States",
}