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Part 1: Document Description
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Citation |
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Title: |
04_OD Flow Explorer Case Studies |
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Identification Number: |
doi:10.7910/DVN/GL3HAB |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2021-03-16 |
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Version: |
4 |
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Bibliographic Citation: |
Li, Zhenlong; Hu, Tao; Ning, Huan; Huang, Xiao; Ye, Xinyue, 2021, "04_OD Flow Explorer Case Studies", https://doi.org/10.7910/DVN/GL3HAB, Harvard Dataverse, V4, UNF:6:yU0ynDI/tA3SR8wQdEUIWg== [fileUNF] |
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Citation |
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Title: |
04_OD Flow Explorer Case Studies |
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Identification Number: |
doi:10.7910/DVN/GL3HAB |
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Authoring Entity: |
Li, Zhenlong (University of South Carolina) |
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Hu, Tao (Harvard University) |
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Ning, Huan (University of South Carolina) |
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Huang, Xiao (University of Arkansas) |
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Ye, Xinyue (TEXAS A&M UNIVERSITY) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Li, Zhenlong |
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Access Authority: |
Hu, Tao |
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Depositor: |
China, Data Lab |
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Date of Deposit: |
2021-03-15 |
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Study Scope |
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Keywords: |
Computer and Information Science, Earth and Environmental Sciences, Social Sciences |
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Abstract: |
The Geoinformation and Big Data Research Laboratory (GIBD) at the University of South Carolina developed the OD Flow Explorer (http://gis.cas.sc.edu/GeoAnalytics/od.html), which provides free human mobility data derived by global wide Geotagged Tweets and the US Safegraph data. To make the data analysis reproducible, replicable, and expandable, we created three case studies based on workflow to visualize data in dynamic maps, and analyze human mobilities' impact on COVID-19 disease transmission in the US and Europe. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
CC0 Waiver |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Bibliographic Citation: |
Zhenlong Li, Xiao Huang, Tao Hu, Huan Ning, Xinyue Ye, and Xiaoming Li. (2021) ODT FLOW: A Scalable Platform for Extracting, Analyzing, and Sharing Multi-source Multi-scale Human Mobility Flows. Preprint. https://www.researchgate.net/publication/350342301_ODT_FLOW_A_Scalable_Platform_for_Extracting_Analyzing_and_Sharing_Multi-source_Multi-scale_Human_Mobility_Flows |
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File Description--f4459569 |
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File: US_State_Hasc.tab |
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Notes: |
UNF:6:yU0ynDI/tA3SR8wQdEUIWg== |
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List of Variables: | |
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Variables |
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f4459569 Location: |
Variable Format: character Notes: UNF:6:3eX04+CgQM2uoaF4tsp9ow== |
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f4459569 Location: |
Variable Format: character Notes: UNF:6:tJBvyDOS01OgSfZfx+JnTQ== |
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f4459569 Location: |
Variable Format: character Notes: UNF:6:T31MSdF870SPJ2T7FkEAfA== |
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f4459569 Location: |
Summary Statistics: StDev 15.832827649303493; Min. 1.0; Mean 28.960784313725497; Valid 51.0; Max. 56.0; Variable Format: numeric Notes: UNF:6:lkyU2WJThwrmOIGUsSWXSw== |
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Label: |
API with Jupyter Notebook Case study 1.tar |
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Notes: |
application/x-tar |
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Label: |
API with Jupyter Notebook Case study 2.tar |
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Notes: |
application/x-tar |
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Label: |
API with Jupyter Notebook Case study 3.tar |
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Notes: |
application/x-tar |
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Label: |
case-study-1_dynamic_map.knwf |
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Text: |
Dynamic map visualization developed by the workflow tool KNIME |
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Notes: |
application/octet-stream |
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Label: |
case-study-2_NY_correlation_analysis.knwf |
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Text: |
Correlation analysis between human mobility and covid-19 cases developed by the workflow tool KNIME |
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Notes: |
application/octet-stream |
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Label: |
case-study-3_Italy_correlation_analysis.knwf |
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Notes: |
application/octet-stream |
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Label: |
ODT Flow REST APIs_Doc_v0.8.pdf |
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Text: |
This is the detailed description of REST APIs and examples for accessing ODT Flow data. |
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Notes: |
application/pdf |
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Label: |
USA_State_5.json |
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Text: |
It is applied in case study 1. |
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Notes: |
application/json |