ArticlePloS one2021
ODT FLOW: Extracting, analyzing, and sharing multi-source multi-scale human mobility.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed.
- Outfitting the quest for spatial spread of infections: A review of mobility datasets for population health modelling.Infectious Disease Modelling · 2026Review
- Analyzing post-COVID-19 demographic and mobility changes in Andalusia using mobile phone data.Scientific reports · 2024Article
- Human mobility and the infectious disease transmission: A systematic review.Geo-spatial information science = Diqui kongjian xinxi kexue xuebao · 2024Article
- Article
- Impacts on Human Movement in Australian Cities Related to the COVID-19 Pandemic.Tropical medicine and infectious disease · 2023Article
- Does Distance Still Matter? Moderating Effects of Distance Measures on the Relationship Between Pandemic Severity and Bilateral Tourism Demand.Journal of travel research · 2023Article
- Article
- Social media mining under the COVID-19 context: Progress, challenges, and opportunities.International journal of applied earth observation and geoinformation : ITC journal · 2022Article
- Exploring the spatial disparity of home-dwelling time patterns in the USA during the COVID-19 pandemic via Bayesian inference.Transactions in GIS : TG · 2022Article
- Population Mobility and Aging Accelerate the Transmission of Coronavirus Disease 2019 in the Deep South: A County-Level Longitudinal Analysis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2022Article
- Spatial social network research: a bibliometric analysis.Computational urban science · 2022Review
- Article
- Emerging geo-data sources to reveal human mobility dynamics during COVID-19 pandemic: opportunities and challenges.Computational urban science · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
In response to the soaring needs of human mobility data, especially during disaster events such as the COVID-19 pandemic, and the associated big data challenges, we develop a scalable online platform for extracting, analyzing, and sharing multi-source multi-scale human mobility flows. Within the platform, an origin-destination-time (ODT) data model is proposed to work with scalable query engines to handle heterogenous mobility data in large volumes with extensive spatial coverage, which allows for efficient extraction, query, and aggregation of billion-level origin-destination (OD) flows in parallel at the server-side. An interactive spatial web portal, ODT Flow Explorer, is developed to allow users to explore multi-source mobility datasets with user-defined spatiotemporal scales. To promote reproducibility and replicability, we further develop ODT Flow REST APIs that provide researchers with the flexibility to access the data programmatically via workflows, codes, and programs. Demonstrations are provided to illustrate the potential of the APIs integrating with scientific workflows and with the Jupyter Notebook environment. We believe the platform coupled with the derived multi-scale mobility data can assist human mobility monitoring and analysis during disaster events such as the ongoing COVID-19 pandemic and benefit both scientific communities and the general public in understanding human mobility dynamics.
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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.