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        <identifier>oai:drops-oai.dagstuhl.de:23835</identifier>
        <datestamp>2025-11-12T13:20:20Z</datestamp>
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          <dc:title>MODAP: A Multi-City Open Data &amp; Analytics Platform for Micromobility Research</dc:title>
          <dc:creator>McKenzie, Grant</dc:creator>
          <dc:subject>open data</dc:subject>
          <dc:subject>mobility</dc:subject>
          <dc:subject>geovisualization</dc:subject>
          <dc:subject>micromobility</dc:subject>
          <dc:description>Over the past decade, micromobility services, particularly electric vehicles for personal short-distance trips, have experienced significant growth. Major cities around the world now host extensive fleets of vehicles available for short-term public rental. While previous research has examined usage patterns within and between a few select cities, large, open, and publicly accessible data sets for analyzing mobility across multiple cities are extremely limited. I have collected, curated, and aggregated over twenty million e-scooter and e-bicycle trips across five major cities and are openly releasing aggregated data for use by mobility and sustainable transport researchers, urban planners, and policymakers. To accompany these data, I developed MODAP (Micromobility Open Data &amp; Analytics Platform), a geovisual analytics tool that empowers researchers to explore the temporal and regional patterns of e-mobility trips within our open data set and download the data for offline analysis. My objective is to foster further research into city-scale mobility patterns and to equip researchers, community members, and policymakers with the necessary tools to conduct this work.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Grant McKenzie</dc:contributor>
          <dc:date>2025</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)</dc:relation>
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          <dc:identifier>doi:10.4230/LIPIcs.GIScience.2025.6</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-238353</dc:identifier>
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          <dc:language>eng</dc:language>
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