ArticleScientific data2024
YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Contagion-preserving compression for multiscale epidemic modeling.Science advances · 2026Article
- Outfitting the quest for spatial spread of infections: A review of mobility datasets for population health modelling.Infectious Disease Modelling · 2026Review
- Urban vibrancy: An analogy of biodiversity, retail diversity, and activity-based urban diversity measures.PNAS nexus · 2026Article
- WorldMove, a global open data for human mobility.Scientific data · 2026Article
- Programmable optoelectronic Ising machine for optimization of real-world problems.Light, science & applications · 2026Article
- Anonymised human location data in England for urban mobility research.Scientific data · 2025Article
- How can we make GPS tracking studies more open, reproducible, and collaborative? A vision for the OpenGPS platform.Data in brief · 2025Article
- Revealing urban area from mobile positioning data.Scientific reports · 2024Article
- YJMob100K: City-scale and longitudinal dataset of anonymized human mobility trajectories.Scientific data · 2024Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Modeling and predicting human mobility trajectories in urban areas is an essential task for various applications including transportation modeling, disaster management, and urban planning. The recent availability of large-scale human movement data collected from mobile devices has enabled the development of complex human mobility prediction models. However, human mobility prediction methods are often trained and tested on different datasets, due to the lack of open-source large-scale human mobility datasets amid privacy concerns, posing a challenge towards conducting transparent performance comparisons between methods. To this end, we created an open-source, anonymized, metropolitan scale, and longitudinal (75 days) dataset of 100,000 individuals' human mobility trajectories, using mobile phone location data provided by Yahoo Japan Corporation (currently renamed to LY Corporation), named YJMob100K. The location pings are spatially and temporally discretized, and the metropolitan area is undisclosed to protect users' privacy. The 90-day period is composed of 75 days of business-as-usual and 15 days during an emergency, to test human mobility predictability during both normal and anomalous situations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.