Datensatz:

OPTIMAP: A Dataset for Open Public Transport Infrastructure and Mobility Accessibility Profiles

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Datum der Erstveröffentlichung

2025

Autor:innen

Schmidt, Manuel

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DOI (Link zu den Daten)
https://doi.org/10.5281/zenodo.14772647
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Publikationsstatus
Published

Zusammenfassung

This dataset provides a comprehensive assessment of public transport connectivity across Germany by analyzing both walking distances to the nearest public transport stops as well as the quality of public transport connections for daily usage scenarios with housing-level-granularity on a country-wide scale. The data was generated through a novel approach that integrates multiple open data sources, simulation models, and visual analytics techniques, enabling researchers, policymakers, and urban planners to identify gaps and opportunities for transit network improvements.

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Fachgebiet (DDC)
004 Informatik

Schlagwörter

Public transport, visual analytics, Urban mobility

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Publikation
Beitrag zu einem Konferenzband
Interactive Public Transport Infrastructure Analysis through Mobility Profiles : Making the Mobility Transition Transparent
(2024) Metz, Yannick; Ackermann, Dennis; Keim, Daniel A.; Fischer, Maximilian T.
Erschienen in: 2024 IEEE Visualization in Data Science, VDS 2024, Proceedings. Piscataway, NJ: IEEE, 2024, S. 6-14. ISBN 979-8-3315-2843-0. Verfügbar unter: doi: 10.1109/vds63897.2024.00006
Link zu zugehöriger Publikation
https://doi.org/10.1109/VDS63897.2024.00006
Link zu zugehörigem Datensatz

Zitieren

ISO 690FISCHER, Maximilian T., Daniel FÜRST, Yannick METZ, Manuel SCHMIDT, Julius RAUSCHER, Daniel A. KEIM, 2025. OPTIMAP: A Dataset for Open Public Transport Infrastructure and Mobility Accessibility Profiles
BibTex
RDF
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    <dcterms:abstract>This dataset provides a comprehensive assessment of public transport connectivity across Germany by analyzing both walking distances to the nearest public transport stops as well as the quality of public transport connections for daily usage scenarios with housing-level-granularity on a country-wide scale. The data was generated through a novel approach that integrates multiple open data sources, simulation models, and visual analytics techniques, enabling researchers, policymakers, and urban planners to identify gaps and opportunities for transit network improvements.</dcterms:abstract>
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