Handling Uncertainty in Geo-Spatial Data
Handling Uncertainty in Geo-Spatial Data
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DOI：
10.1109/icde.2017.212
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发表时间：
2017-04
期刊：
影响因子：
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通讯作者：
Andreas Züfle;Goce Trajcevski;D. Pfoser;M. Renz;Matthew T. Rice;Timothy F. Leslie;P. Delamater;Tobias Emrich
中科院分区：
文献类型：
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作者：
Andreas Züfle;Goce Trajcevski;D. Pfoser;M. Renz;Matthew T. Rice;Timothy F. Leslie;P. Delamater;Tobias Emrich
任何包含空间和/或时间信息的数据集所面临的一个固有挑战是由于各种不精确来源而产生的不确定性。当从底层输入数据估计任何查询结果的可靠性（置信度）时，集成不确定性的影响是至关重要的。为了应对不确定性，地球科学和数据科学研究界分别提出了解决方案。这个跨学科的教程桥梁之间的差距差距两个社区通过提供在处理不确定的地理空间数据所涉及的不同挑战的全面概述，通过调查从两个研究社区的解决方案，并通过确定相似之处，协同作用和开放的研究问题。
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.