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Challenges and Prospects of Uncertainties in Spatial Big Data Analytics

Bibliographic Data

ID3208032
AuthorsWenzhong Shi (0000-0002-3886-7027, Hong Kong Polytechnic University), Anshu Zhang (0000-0001-7158-8292, Hong Kong Polytechnic University), Xiaolin Zhou (0000-0002-4115-5071, Hong Kong Polytechnic University), Min Zhang (0000-0003-4273-6836, Wuhan University)
Year2018
Volume108
Issue6
Pages1513-1520
Publication date2018-11-02
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueAnnals of the American Association of Geographers (JOURNAL)
Journal identifiersISSN: 2469-4452 • E-ISSN: 2469-4460
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/24694452.2017.1421898
OpenAlexW2793105082
LanguageEN
Citations received3
References cited17

Knowledge extraction from spatial big data (SBD) with advanced analytics has become a major trend in research and industry. Meanwhile, the increasingly complex SBD and its analytics face proliferating challenges posed by uncertainties in them. Linked to various characteristics of SBD, the uncertainties emerge and propagate in each stage of SBD analytics. To avoid unreliable knowledge and losses resulting from the uncertainties and to ensure the value of authentic knowledge, this article proposes uncertainty-based SBD analytics. Uncertainty-based SBD analytics strive to understand, control, and alleviate uncertainties and their propagation in each stage of geographic knowledge extraction. Key topics involved in uncertainty-based SBD analytics include, for example, place-based heuristics for learning urban structure and place-based analytics on broader knowledge extraction tasks; dealing with the biases and inferencing the semantics in cell phone tracking data; quality assessment of unstructured spatial user-generated contents and the rectification of location shifts and time elapses between humans' activities and corresponding online contents they generate; and uncertainty handling in sophisticated black-box analytics with SBD such as deep learning. Challenges and the latest advances in each of these topics are presented, and further research for addressing these challenges is suggested in this article

Analytics · Big data · Data Analysis · Data mining · Data science · Heuristics · Knowledge extraction · Visual analytics · Visualization · Computer Science · Geographic Information Systems Studies · Human Mobility and Location-Based Analysis · Traffic Prediction and Management Techniques

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Unique citing works3
Citations per year0,5
Citation span2020 - 2025 (6)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 3

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