Modelling spatial structures

Franz-Benjamin Mocnik*, Andrew U. Frank

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

9 Citations (Scopus)


Data is spatial if it contains references to space.We can easily detect explicit references, for example coordinates, but we cannot detect whether data implicitly contains references to space, and whether it has properties of spatial data, if additional semantic information is missing. In this paper, we propose a graph model that meets typical properties of spatial data. We can, by the comparison of a graph representation of a data set to the graph model, decide whether the data set (implicitly or explicitly) has these typical properties of spatial data.

Original languageEnglish
Title of host publicationSpatial Information Theory
Subtitle of host publication12th International Conference, COSIT 2015, Santa Fe, NM, USA, October 12-16, 2015, Proceedings
EditorsScott Freundshuh, Sara Irina Fabrikant, Clare Davies, Scott Bell, Michela Bertolotto, Martin Raubal
Place of PublicationCham
Number of pages21
ISBN (Electronic)978-3-319-23374-1
ISBN (Print)978-3-319-23373-4
Publication statusPublished - 2015
Externally publishedYes
Event12th International Conference on Spatial Information Theory, COSIT 2015 - Santa Fe, United States
Duration: 12 Oct 201516 Oct 2015
Conference number: 12

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameTheoretical Computer Science and General Issues


Conference12th International Conference on Spatial Information Theory, COSIT 2015
Abbreviated titleCOSIT 2015
Country/TerritoryUnited States
CitySanta Fe


  • Graph model
  • Principle of least effort
  • Scale invariance
  • Space
  • Spatial data
  • Spatial information
  • Spatial network
  • Spatial structure
  • Time
  • Tobler’s law


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