Enhancing data privacy with semantic trajectories: a raster-based framework for GPS stop/move management

Wang, Y. and McArthur, D. (2018) Enhancing data privacy with semantic trajectories: a raster-based framework for GPS stop/move management. Transactions in GIS, 22(4), pp. 975-990. (doi: 10.1111/tgis.12334)

[img]
Preview
Text (Cover Sheet)
157980Cover.pdf - Other

178kB
[img]
Preview
Text
157980.pdf - Accepted Version

4MB

Abstract

Tracking facilities on smartphones generate enormous amounts of GPS trajectories, which provide new opportunities to study movement patterns and improve transportation planning. Converting GPS trajectories into semantically meaningful trips is attracting increasing research effort with respect to the development of algorithms, frameworks, and software tools. There are, however, few works focused on designing new semantic enrichment functionalities taking privacy into account. This article presents a raster‐based framework which not only detects significant stop locations, segments GPS records into stop/move structures, and brings semantic insights to trips, but also provides possibilities to anonymize users’ movements and sensitive stay/move locations into raster cells/regions so that a multi‐level data sharing structure is achieved for a variety of data sharing purposes.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Mcarthur, Dr David and Wang, Dr Yang
Authors: Wang, Y., and McArthur, D.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Transactions in GIS
Publisher:Wiley
ISSN:1361-1682
ISSN (Online):1467-9671
Published Online:11 April 2018
Copyright Holders:Copyright © 2018 John Wiley & Sons Ltd
First Published:First published in Transactions in GIS 22(4): 975-990
Publisher Policy:Reproduced in accordance with the copyright policy of the publisher

University Staff: Request a correction | Enlighten Editors: Update this record