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Cited by 102Human Mobility and Location-Based AnalysisData Management and AlgorithmsComputational Physics and Python Applications

scikit-mobility : A Python Library for the Analysis, Generation, and Risk Assessment of Mobility Data

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Pappalardo, Luca, Simini, Filippo, Barlacchi, Gianni, Pellungrini, Roberto·2022·Journal of Statistical Software
DOI 10.18637/jss.v103.i04
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Abstract

The last decade has witnessed the emergence of massive mobility datasets, such as tracks generated by GPS devices, call detail records, and geo-tagged posts from social media platforms. These datasets have fostered a vast scientific production on various applications of mobility analysis, ranging from computational epidemiology to urban planning and transportation engineering. A strand of literature addresses data cleaning issues related to raw spatiotemporal trajectories, while the second line of research focuses on discovering the statistical

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Cited by

Sorted by citations

Authors
Pappalardo, L., Simini, F., Barlacchi, G., & Pellungrini, R.
Affiliations
  • Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" (IT)
  • Argonne National Laboratory (US)
  • Amazon (United States) (US)
  • University of Pisa (IT)
ORCID
Venue
Journal of Statistical Software
Publisher
Foundation for Open Access Statistic
Published
2022
Volume
103
Issue
4
ISSN
1548-7660 (ISSN-L)
DOI
10.18637/jss.v103.i04
OpenAlex
W2981033335
Cited by
102
References
4
Citations by year
2026: 14 · 2025: 26 · 2024: 20 · 2023: 12 · 2022: 9 · 2021: 10 · 2020: 11
FWCI
11.73
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Statistical Software (publishedVersion, cc-by)
  • ISTI Open Portal (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Scuola Normale Superiore di Pisa (submittedVersion, cc-by)
  • Greater South Information System
Funders
  • Horizon 2020 Framework Programme (780754, 871042)
  • Engineering and Physical Sciences Research Council (H2020, EP/P012906/1)
Topics
  • Social Sciences › Transportation › Human Mobility and Location-Based Analysis
  • Physical Sciences › Computer Science › Signal Processing › Data Management and Algorithms
  • Physical Sciences › Computer Science › Artificial Intelligence › Computational Physics and Python Applications
Keywords
mobility data, trajectory analysis, GPS tracks, call detail records, spatio-temporal trajectories, data cleaning, Python library

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