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                <identifier>oai:data.mendeley.com/knxmkcsg9m.1</identifier>
                <datestamp>2026-04-14T15:01:40Z</datestamp>
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            <metadata><oai_dc:dc xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
    <dc:creator>Mansourihanis, Omid</dc:creator>
    <dc:title>Cincinnati Metro Transit Network Vulnerability Analysis</dc:title>
    <dc:publisher>Mendeley Data</dc:publisher>
    <dc:description>This dataset supports a graph-theoretic vulnerability analysis of the Southwest Ohio Regional Transit Authority (SORTA) Cincinnati Metro weekday bus network. The study constructs a directed weighted graph from publicly available GTFS schedule data, computes composite vulnerability scores using Principal Component Analysis (PCA) across four centrality metrics, simulates four Cincinnati-specific disruption scenarios, and overlays results with U.S. Census equity data.

Network: 3,532 connected stops | 4,048 directed edges | 50 routes | 6,435 weekday trips | service_id: 2603-QG &amp; BH-Weekday-010

Key findings:
- Most vulnerable stop: Government Square Area F (PCA score = 100.0, betweenness = 0.230)
- Government Square hub shutdown (6 stops): 0.17% network disruption — network is resilient to single-hub closure
- Ohio River flood scenario (235 stops, FEMA Zone AE): 6.82% disruption, 241 stops isolated — most severe scenario
- Downtown power outage (96 stops, 0.5-mile radius): 2.89% disruption, 102 stops isolated
- Spearman ρ = 0.18 (p &lt; 0.001) between vulnerability score and neighborhood poverty rate

Dataset contents:
- SORTA_Stops_Vulnerability_Scores.csv: Main dataset (3,532 stops) with PCA vulnerability scores, four centrality metrics (betweenness, closeness, degree, trip frequency), Census equity variables (median income, poverty rate, car-free household rate, transit dependency, equity impact score), and binary scenario flags for all four disruption scenarios.
- Disruption_Scenarios_Summary.csv: Quantified outcomes for four scenarios (stops removed, reachability, disruption %, isolated stops).
- Sequential_Removal_Simulation.csv: Network reachability R(G&apos;) across 15 sequential stop removals (reachability curve data for Figure 5).
- Network_Statistics_Summary.csv: Scalar network metrics reported in the paper.
- Cincinnati_Neighborhoods_Demographics.csv: Demographic profile of 20 neighborhoods.
- Shapefiles (EPSG:4326): SORTA_Stops (point), Cincinnati_Neighborhoods (polygon), FEMA_FloodZone_AE (polygon).
- Figures 2–5 at 300 DPI.
- Complete analysis pipeline as a Google Colab-compatible Jupyter notebook.

Primary data sources (not redistributed): SORTA GTFS (go-metro.com/about/developer-data), U.S. Census ACS 5-Year 2018–2022 (api.census.gov), FEMA NFHL (msc.fema.gov). All public domain / freely available.</dc:description>
    <dc:subject>Transport</dc:subject>
    <dc:subject>Urban Planning</dc:subject>
    <dc:subject>Equity</dc:subject>
    <dc:subject>Bus Transportation</dc:subject>
    <dc:type>Dataset</dc:type>
    <dc:identifier>doi:10.17632/knxmkcsg9m.1</dc:identifier>
    <dc:identifier>oai:data.mendeley.com/knxmkcsg9m.1</dc:identifier>
    <dc:rights>Creative Commons Attribution 4.0 International</dc:rights>
    <dc:rights>http://creativecommons.org/licenses/by/4.0</dc:rights>
    <dc:relation>https://data.mendeley.com/datasets/knxmkcsg9m</dc:relation>
    <dc:date>2026-04-14T15:01:40Z</dc:date>
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