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Die Konstruktion von Dienstleistungskarten mit Open Data am Beispiel des lokalen Bedarfs an Kinderbetreuung in Berlin
[The construction of service maps with open data: the case of local need for child care in Berlin]

Author

Listed:
  • Ulrich Rendtel

    (Freie Universität Berlin)

  • Milo Ruhanen

Abstract

Zusammenfassung Durch Dichteschätzer können georeferenzierte Daten effektiv zur Darstellung des Zusammenhangs von Konzentrationsgebieten bestimmter Bevölkerungsgruppen und dem jeweiligen Betreuungsbedarf genutzt werden. Im Gegensatz zu der klassischen Darstellung über Choroplethenkarten bieten Kerndichteschätzer für eine kleinräumige Analyse große Vorteile. Diese vermeiden Sprünge an den Gebietsgrenzen, sie sind flächentreu und bieten die Möglichkeit Konzentrationsgebiete leicht zu erkennen. Allerdings liefern Open Data nur aggregierte Informationen zu einem Flächenstück. In diesem Aufsatz zeigen wir, wie durch die Anwendung der Methode der simulierten Geokoordinaten von Groß et al. (2017) auch mit Open Data Dichteschätzer erstellt werden können. Dies geschieht hier anhand von vier Beispielen aus dem Bereich der Kinderbetreuung in Berlin. Zum Vergleich benutzen wir die bisher übliche Darstellungsweise über Choroplethenkarten. Im Ergebnis erkennt man auf den Dichtekarten eine angemessene regionale Verteilung von Kitas und Grundschulen, während die Versorgung mit Kinderarztpraxen deutliche Mängel aufweist. Diese Sachverhalte sind anhand der Choroplethenkarten nicht ersichtlich.

Suggested Citation

  • Ulrich Rendtel & Milo Ruhanen, 2018. "Die Konstruktion von Dienstleistungskarten mit Open Data am Beispiel des lokalen Bedarfs an Kinderbetreuung in Berlin [The construction of service maps with open data: the case of local need for ch," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 271-284, December.
  • Handle: RePEc:spr:astaws:v:12:y:2018:i:3:d:10.1007_s11943-018-0235-y
    DOI: 10.1007/s11943-018-0235-y
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    References listed on IDEAS

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    1. Marcus Groß & Ulrich Rendtel & Timo Schmid & Sebastian Schmon & Nikos Tzavidis, 2017. "Estimating the density of ethnic minorities and aged people in Berlin: multivariate kernel density estimation applied to sensitive georeferenced administrative data protected via measurement error," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 161-183, January.
    2. Groß, Marcus & Rendtel, Ulrich & Schmid, Timo & Tzavidis, Nikos, 2018. "Switching between different area systems via simulated geocoordinates: A case study for student residents in Berlin," Discussion Papers 2018/2, Free University Berlin, School of Business & Economics.
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    Cited by:

    1. Groß Marcus & Kreutzmann Ann-Kristin & Rendtel Ulrich & Schmid Timo & Tzavidis Nikos, 2020. "Switching Between Different Non-Hierachical Administrative Areas via Simulated Geo-Coordinates: A Case Study for Student Residents in Berlin," Journal of Official Statistics, Sciendo, vol. 36(2), pages 297-314, June.
    2. Groß, Marcus & Rendtel, Ulrich & Schmid, Timo & Bömermann, Hartmut & Erfurth, Kerstin, 2018. "Simulated geo-coordinates as a tool for map-based regional analysis," Discussion Papers 2018/3, Free University Berlin, School of Business & Economics.
    3. Groß Marcus & Kreutzmann Ann-Kristin & Rendtel Ulrich & Schmid Timo & Tzavidis Nikos, 2020. "Switching Between Different Non-Hierachical Administrative Areas via Simulated Geo-Coordinates: A Case Study for Student Residents in Berlin," Journal of Official Statistics, Sciendo, vol. 36(2), pages 297-314, June.
    4. Timo Schmid & Markus Zwick, 2018. "Vorwort der Herausgeber," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 12(3), pages 189-193, December.
    5. Sebastian Dräger & Johannes Kopp & Ralf Münnich & Simon Schmaus, 2022. "Die zukünftige Entwicklung der Grundschulversorgung im Kontext ausgewählter Wanderungsszenarien [The future development of primary school demand in the context of selected migration scenarios]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 16(1), pages 51-77, March.

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