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Encoding and Querying Historic Map Content

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Connecting a Digital Europe Through Location and Place

Part of the book series: Lecture Notes in Geoinformation and Cartography ((LNGC))

Abstract

Libraries have large collections of map documents with rich spatio-temporal information encoded in the visual representation of the map. Currently, historic map content is covered by the provided metadata only to a very limited degree, and thus is not available in a machine-readable form. A formal representation would support querying for and reasoning over detailed semantic contents of maps, instead of only map documents. From a historian’s perspective, this would support search for map resources which contain information that answers very specific questions, such as maps that show the cities of Prussia in 1830, without manually searching through maps. A particular challenge lies in the wealth and ambiguity of map content for queries. In this chapter, we propose an approach to describe map contents more explicitly. We suggest ways to formally encode historic map content in an approximate intensional manner which still allows useful queries. We discuss tools for georeferencing and enriching historic map descriptions by external sources, such as DBpedia. We demonstrate the use of this approach by content queries on map examples.

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Notes

  1. 1.

    http://www.loc.gov/rr/geogmap/guides.html

  2. 2.

    http://www.uni-muenster.de/Staedtegeschichte/portal/datenbanken

  3. 3.

    http://www.fas.harvard.edu/~chgis/

  4. 4.

    The International Committee for Museum Documentation’s conceptual reference model for cultural heritage documentation, see http://cidoc.ics.forth.gr.

  5. 5.

    http://gaia.gge.unb.ca/eg/HistoricalMap.owl

  6. 6.

    http://www.w3.org/RDF/

  7. 7.

    Throughout the chapter, we use the Turtle syntax to write down triples; see http://www.w3.org/TeamSubmission/turtle/.

  8. 8.

    http://dbpedia.org

  9. 9.

    http://www.w3.org/1999/02/22-rdf-syntax-ns

  10. 10.

    http://en.wikipedia.org/wiki/Named_graph

  11. 11.

    http://www.ontotext.com/owlim

  12. 12.

    http://www.w3.org/TR/rdf-sparql-query/

  13. 13.

    In order to stay historically correct, one would need to say that Silesia was part of Prussia only after its conquest in 1763. This would require to introduce time-indexed partOf relations. Similarly, wasAcquiredby reflects some event. However, as a matter of fact, such kind of information is actually not contained in the map, and thus should not be represented by the content graph. Moreover, representing such time-indexed relationships presents a challenge of its own (Trame et al. 2013) which goes beyond the scope of this chapter.

  14. 14.

    http://www.w3.org/TR/owl-ref/

  15. 15.

    Available at http://geographicknowledge.de/vocab/historicmapsphen [.rdf/.jpg], denoted by prefix phen.

  16. 16.

    In fact, our classes cover the classes of geographic kinds suggested by Smith and Mark (2001), which was based on an empirical study. We furthermore imported the ontology for Linking Open Descriptions of Events (LODE) http://linkedevents.org/ontology/.

  17. 17.

    With this predicate, we express that phenomena are visually connected in the map image, without making any further implications.

  18. 18.

    http://ontologydesignpatterns.org/wiki/Submissions:Time_indexed_person_role

  19. 19.

    Available at http://www.opengis.net/ont/geosparql/1.0, prefix geo.

  20. 20.

    A serialization of geometry based on OGC’s simple feature standard.

  21. 21.

    Alternatively, one may add corresponding blank nodes by some SPARQL construct.

  22. 22.

    Available at http://www.w3.org/2006/time; prefix time.

  23. 23.

    Available at http://geographicknowledge.de/vocab/maps [.rdf/.jpg], prefix maps.

  24. 24.

    http://purl.org/ontology/bibo/

  25. 25.

    http://purl.org/dc/terms/

  26. 26.

    http://dbpedia.org

  27. 27.

    https://github.com/lodum/georef

  28. 28.

    https://github.com/NYPL/map-vectorizer

  29. 29.

    OWLIM-Lite 4.0 with OWL-Horst reasoner (optimized) and OpenRDF workbench version 2.7.7. The endpoint is available at http://data.uni-muenster.de:8080/openrdf-sesame/repositories/mapcontents.

  30. 30.

    Note: Due the fact that the temperature uses a literal dbp-de:Reaumur-Skala, the SPARQL function MIN does not work without additional effort.

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Acknowledgments

This work has been funded by the German Research Foundation (DFG) through the Linked Data for eScience Services (LIFE) project (KU 1368/11-1). We also would like to thank our project partners, the Münster University Library (ULB) and the Institute for comparative urban history (ISTG) for their constant support of this work.

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Authors and Affiliations

  1. Institute for Geoinformatics, University of Münster, Münster, Germany

    Simon Scheider, Jim Jones & Alber Sánchez

  2. CARSI, Department of Geography, Hunter College, City University of New York, New York, USA

    Carsten Keßler

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  1. Simon Scheider
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  2. Jim Jones
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  4. Carsten Keßler
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Correspondence to Carsten Keßler .

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Editors and Affiliations

  1. University Jaume I of Castellón, Castellón, Spain

    Joaquín Huerta

  2. European Commission - Joint Research Centre, Italy

    Sven Schade

  3. European Commission - Joint Research Centre, Ispra, Italy

    Carlos Granell

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Scheider, S., Jones, J., Sánchez, A., Keßler, C. (2014). Encoding and Querying Historic Map Content. In: Huerta, J., Schade, S., Granell, C. (eds) Connecting a Digital Europe Through Location and Place. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-03611-3_15

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