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Representing and Utilizing Changing Historical Places as an Ontology Time Series

  • Eero HyvönenEmail author
  • Jouni Tuominen
  • Tomi Kauppinen
  • Jari Väätäinen
Chapter
First Online:
Part of the Semantic Web and Beyond book series (ADSW, volume 12)

Abstract

Place names and their geographical coverage change in time. This causes problems when retrieving information content related to different times. Geo-content is usually indexed using place names of the time of indexing (e.g. a photo of the 1968 upraise of Czechoslovakia indexed then) or of the time that the content has been used or created (e.g. a spear used in the Punic Wars in 146 b.c. in Carthago but indexed at a later time using place names of that time). Finally, end-users may query content in terms of contemporary place names (e.g. Check Republic or Slovakia) or overlapping historic names of different times (e.g. Roman Empire). This chapter presents an ontology-based approach to this problem. The idea is to represent and maintain a time series of spatial ontologies in terms of easily manageable local spatio-temporal changes from which the actual time series ontology can be generated automatically with semantic enrichment. This ontology can then be used for indexing and for mapping spatio-temporal regions and their names onto each other. As a proof-of-concept, the system has been applied to modeling the history municipalities of Finland in 1865–2010. We present the model, a tool for maintaining the change history in a user-friendly way, transformation of the place change history into an ontology time series with semantic enrichment, and publication of the ontology as a ready to use ontology services on the web with AJAX, Web Service, and REST interfaces. The system has been applied in the semantic cultural heritage portal CultureSampo for semantic search and recommendation, as well as an external service for indexing cultural heritage content, and for query expansion search in a legacy cultural heritage database system.

Keywords

Geographic Information System Query Term Query Expansion Topological Relation Ontology Service 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

This work is part of the National Semantic Web Ontology project in Finland19 (FinnONTO, 2003–2012), funded mainly by the National Technology and Innovation Agency (Tekes) and a consortium of 38 organizations, and the Cultural Foundation of Finland.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Eero Hyvönen
    • 1
    Email author
  • Jouni Tuominen
  • Tomi Kauppinen
  • Jari Väätäinen
  1. 1.Aalto UniversityAaltoFinland

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