Semantic Graphs to Reflect the Evolution of Geographic Divisions
C. Bernard (),
C. Plumejeaud-Perreau (),
M. Villanova-Oliver (),
J. Gensel () and
H. Dao ()
Additional contact information
C. Bernard: Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG
C. Plumejeaud-Perreau: LIttoral ENvironnement et Sociétés (LIENSs) - UMR
M. Villanova-Oliver: Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG
J. Gensel: Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG
H. Dao: University of Geneva, Department of Geography and Environment Geneva
Chapter Chapter 6 in Handbook of Big Geospatial Data, 2021, pp 135-159 from Springer
Abstract:
Abstract Nowadays, the volume of data coming from the public sector is growing rapidly on the Open Data Web. Most of these data come from governmental agencies such as Statistical and Mapping Agencies. Together, these public institutions publish territorial statistics that are of utmost importance for policy-makers to conduct various analyses of their jurisdiction, in time and space, and observe its evolution over time. However, through times, all over the world, the geographic divisions that serve as a reference for recording territorial statistical values, are subject to change: their name, their belonging or their boundaries change for political or administrative reasons and at several subdivision levels (e.g., regions, districts, sub-districts). These changes lead to breaks in time-series and are source of both misinterpretations, and statistical biases when not properly documented. In this chapter, we investigate solutions relying on the Semantic Web technologies for the description of the evolution of geographic divisions over time. We investigate how these technologies may enhance the understanding of the territorial dynamics over time, providing statisticians, researchers, citizens with well-documented descriptions of territorial changes to conduct various analyses of the territories.
Date: 2021
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-55462-0_6
Ordering information: This item can be ordered from
http://www.springer.com/9783030554620
DOI: 10.1007/978-3-030-55462-0_6
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().