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A visual analytics design for studying rhythm patterns from human daily movement data
Author(s) -
Wei Zeng,
ChiWing Fu,
Stéfan Müller Arisona,
Simon Schubiger,
Remo Burkhard,
KwanLiu Ma
Publication year - 2017
Publication title -
visual informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.495
H-Index - 11
eISSN - 2543-2656
pISSN - 2468-502X
DOI - 10.1016/j.visinf.2017.07.001
Subject(s) - visual analytics , variety (cybernetics) , analytics , context (archaeology) , data science , movement (music) , computer science , space (punctuation) , human–computer interaction , visualization , geography , artificial intelligence , philosophy , archaeology , operating system , aesthetics
Human’s daily movements exhibit high regularity in a space–time context that typically forms circadian rhythms. Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners, transportation analysts, to business strategists. In this paper, we present an interactive visual analytics design for understanding and utilizing data collected from tracking human’s movements. The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time. Case studies using real-world human movement data, including massive urban public transportation data in Singapore and the MIT reality mining dataset, and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system

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