Encoding and querying historic map content

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Slides courtesy of Simon Scheider. Presentation for our paper at AGILE 2014: Simon Scheider, Jim Jones, Alber Sanchez and Carsten Keßler (2014) Encoding and querying historic map content. In Joaquín Huerta, Sven Schade, Carlos Granell: Connecting a Digital Europe Through Location and Place. Springer Lecture Notes in Geoinformation and Cartography 2014: 251–273. DOI:10.1007/978-3-319-03611-3_15

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Encoding and querying historic map content

  1. 1. http://lodum.de Encoding and querying historic map content Simon Scheider*, Jim Jones*, Alber Sanchez*, Carsten Keßler§ *University of Münster, Institute for Geoinformatics, Münster §Hunter College, Department of Geography, NY
  2. 2. How can (we support) historians (in) find(ing) (answers in) maps? Question: “What was the type of landcover around Hildesheim in the 19th century?” 1) Manual search (through 20.000 maps?) 2) Text field search: - title: (“Gaußsche Landesaufnahme” “Berghe Ducatus”,...) - author: (Gerhard Mercator, ...) - year of production (1680, 1839, ...) -key words: (“topographic map”, “Flurkarte”) Sample from the map repository at ISTG (Institute for comparative urban history), Münster
  3. 3. How can (we support) historians (in) find(ing) (answers in) maps? Technical challenges: 1) Manual search (through 20.000 maps?) 2) Text field search: - title: (“Gaußsche Landesaufnahme” “Berghe Ducatius”,...) - author: (Gerhard Mercator, ...) - year of production (1680, 1839, ...) -key words: (“topographic map”, “Flurkarte”) Not scalable! Language? How to pick the „right“ terms? (which correspond to the answer?) How to pick the „right“ place/space? („the area around Hildesheim“) How to pick the right time? („19th century“) There are many languages in maps (Latin, ...)! Placenames are changing! Historic maps are distorted and lack CRS! Terms are ambiguous! There is too much content! There is nameless content (e.g. „landcover around Hildesheim“)!
  4. 4. How can (we support) historians (in) find(ing) (answers in) maps? More questions: “What was the extent of Prussia?” “Which territories were part of Prussia?” “Which Prussian territories were acquired by Friedrich-Wilhelm of Brandenburg, the great elector?“ Answer depends on time ... and ambiguity of names ... Prussia 1806 „Brandenburg“ (Prussia) 1688
  5. 5. How can (we support) historians (in) find(ing) (answers in) maps? A map answering detailed historical knowledge: “How many people did Napoleon’s army have when soldiers arrived in Smolensk during his 1812 campaign?“ “What were the lowest temperatures during Napoleon’s campaign?” “Which places did Napoleon’s army come across during the 1812 campaign?” Minard’s map about Napoleon’s invasion of Russia 1812:
  6. 6. How can (we support) historians (in) find(ing) (answers in) maps? Research topics we addressed in the paper: 1) How to precisely encode and query - semantic, - spatial and - temporal map contents? 2) How to deal with - wealth of content - language/naming ambiguity?
  7. 7. Linked spatio-temporal data for historic maps Linked spatio-temporal data enables 1. a simple und universal approach to describe semantic contents of (map) documents (namely, a graph) 2. complex content queries (beyond text search) using diverse languages 3. logical expressions and reasoning for approximate content descriptions/queries 4. linking to external resources (URI) ...and therefore: (re)-using resources and crowdsourcing 5. using spatial (OGC simple feature) and temporal references Map Berghe Ducatus Gerard Mercator is a creator coord x: …. y: …. mapsArea “1550”mapsTime Berg State is a Köln maps City “1512” birthDate is a
  8. 8. Formally encoding map contents Map contents can be treated as sets of assertions that can be extracted by looking at the map: In the Semantic Web, - nameless content - wealth of content can be addressed by intensionality: - logical quantification - blank nodes In linked data, this translates into a named graph:
  9. 9. Vocabularies we reused: -For map area as well as content space: GeoSPARQL ontology (prefix geo): OWLtime (prefix time): - For document properties:... Vocabularies for historic map contents Maps as documents (prefix maps) : http://geographicknowledge.de/vocab/maps
  10. 10. Vocabularies for historic map contents Content phenomena (prefix phen): http://geographicknowledge.de/vocab/historicmapsphen [.rdf/.jpg]: (reuse of any geographic/ historical ontology, such as: )
  11. 11. Encoding maps as linked data For example, the map about Hildesheim 1840: Document (graph) represents Content graph (describing the map as document) (describing content assertions)
  12. 12. Georeferencing and annotating historic maps http://data.uni-muenster.de/georeferencer/georef.html 1) Georeferencing map image: using control points (known locations in Open Street Map)
  13. 13. Georeferencing and annotating historic maps 2) Determine map window Automatic calculation of - map scale - map area
  14. 14. Georeferencing and annotating historic maps 3) Describe document: - time - creator - size - document URL …
  15. 15. Georeferencing and annotating historic maps 4) Describe contents Automatically suggested content based on map area, time window Reuse of external information recources (e.g. the state Berg at Dbpedia) Different historians can contribute to the same map
  16. 16. Publishing maps and their contents RESTful publication (accessible over http): - As RDF files or KML files - over SPARQL endpoint - Can be accessed over the Web for display or search Display with Google Earth:
  17. 17. Querying historic map contents Which maps contain information about ...
  18. 18. Querying historic map contents Which maps contain information about ...
  19. 19. Querying historic map contents Which maps contain information about ...
  20. 20. Conclusion • Historic map contents =: named RDF graphs! • ... allows the expression of map contents in a precise way as a set of (triple) assertions •... and the linking of maps as documents with their contents, reusing published vocabularies and external links (Dbpedia) • ... enables crowdsourcing of content descriptions • ... makes possible intensional descriptions (using blank nodes) in order to cope with the wealth of content, nameless content and content approximation • ... enables retrieval of maps that can answer historians‘ questions!
  21. 21. Future work • Tools that help encoding map contents for non-trained users (beyond georeferencer)? • Tools that allow non-trained users to formulate (visual) content based queries? >SPEX (spatio-temporal content explorer) (see https://github.com/lodum)
  22. 22. Dr. Simon Scheider Institut für Geoinformatik der Westfälischen Wilhelms-Universität Heisenbergstraße 2, 48149 Münster simon.scheider@uni-muenster.de Tel.: 0251 I 83-30088 Thanks for your attention!

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