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Generating a Pseudo Resident Registration Register by Using Open Data

GEOProcessing 2022: The Fourteenth International Conference on Advanced Geographic Information Systems, Applications, and Services. Bd. 2022. Porto, Portugal. 2022 S. 53 - 57

Erscheinungsjahr: 2022

ISBN/ISSN: 978-1-61208-983-6/2308-393X

Publikationstyp: Zeitschriftenaufsatz (Konferenzbeitrag)

Sprache: Englisch

GeprüftBibliothek

Inhaltszusammenfassung


The paper offers a possibility for a (partial) reconstruction of a resident registration dataset combining and linking open (geo-) data with respect to data protection regulations. Here, a method is proposed that simulates a building-level georeferenced resident registration register as a pseudo-derivative. Understood as a potential supplement for research projects, the increasing relevance and discussion of datasets for analyzing individual dynamics on a small scale is taken up with easy-to-...The paper offers a possibility for a (partial) reconstruction of a resident registration dataset combining and linking open (geo-) data with respect to data protection regulations. Here, a method is proposed that simulates a building-level georeferenced resident registration register as a pseudo-derivative. Understood as a potential supplement for research projects, the increasing relevance and discussion of datasets for analyzing individual dynamics on a small scale is taken up with easy-to-generate datasets without facing data protection issues. Complete reconstruction and disaggregation are not possible due to anonymization techniques and data available, but further improvements are conceivable with the latest census and additional open data. This procedure thus reflects trends of Urban-Geo to expand and better visualize small-scale demographic analyses, and also highlights the potential value of opening up register data to science.» weiterlesen» einklappen

  • Resident registration register
  • disaggregation
  • censusdata
  • open data
  • register-based researc
  • census data
  • register-based research

Autoren


Visca, Dominik (Autor)
Neis, Pascal (Autor)

Klassifikation


DFG Fachgebiet:
Informatik

DDC Sachgruppe:
Informatik

Verbundene Forschungsprojekte


Verknüpfte Personen



Max Hoppe