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Georeferencing of Search Results based on Annoted Data and Geographic Information Systems

Georeferencing of Search Results based on Annoted Data and Geographic Information Systems. by Giw Aalam MPI, Department 5, Databases and Information Systems. Motivation(1). „Whatever occurs, occurs in space and time.“ (Wegener 2000)

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Georeferencing of Search Results based on Annoted Data and Geographic Information Systems

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  1. Georeferencing of Search Results based on Annoted Data and Geographic Information Systems by Giw Aalam MPI, Department 5, Databases and Information Systems

  2. Motivation(1) • „Whatever occurs, occurs in space and time.“ (Wegener 2000) • Navigation • Path of a hurricane • Market surveys • Environmental dynamics • Increasing market for geospatial information

  3. Motivation(2) • Most georeferencing we encounter daily is in form of placenames: • ~70% of text documents contain placename references (MetaCarta Inc. 2005) • 49,69% out of 5Mio. libraray catalog records of the University of California contain >1 place related subject headings (Petras 2004) Time and space reference potentially important to access documents and knowledge

  4. Motivation(3) • Most text oriented search engines heavily depend on recognizing weighted keywords • Cannot find relevant results for queries like „tropical fruit“ and „Bodensee“; e.g. an article about apricots from Mainau isle • Requires appropiate knowledge base (Thesauri/Ontology, Gazzetters/geospatial information)

  5. Objective • Show potentials & problems of the usage of geodata / georeferenced data in the framework of information retrieval • Develop a prototype for a search engine, based on widespread available data and tools (Wikipedia, GoogleEarth)

  6. Georeferencing(1) • Translation between informal and formal representations of geographic locations • Informal reference e.g. used in discourse („Saarbrücken“, „the musicstore on Marktstraße“, …) • Formal representations are basis for mathematical calculations like distance, direction and spatial relationships in general (52° 31' N, 13° 25' O )

  7. Georeferencing(2)

  8. Annotation(1) • Congruent, common understanding of geographic references important for consistent annotation • What should be annotated? • What is relevant? • What aspects of geodata should be described? • How? • Context specific versus cross-context

  9. Annotation(2) • XML-based formats play an increasing role in the framework of GIS (Geographic Information Systems) for annotation/description and data exchange • Structured • Extensible; XML Schema comprises a binding determination of an information model expressed in a document-instance • Possible to work with heterogeneous data

  10. Annotation(3) • GML (Geography Markup Language) • Defined by the OGC (Open Geospatial Consortium) as a „standard“ format for modeling and exchange of spatial information • expected to be released as an international standard in 2007

  11. Annotation(5) • KML (Keyhole Markup Language) • Delevoped by Keyhole Corp. for the „EarthViewer“-Tool • Keyhole has been taken over by Google Inc. in 2004 • KML now used in connection with GoogleEarth • Visualisation of georeferenced data • Description of geometric figures, pictures and locations • Define view/perspective Examples later…

  12. Infrastructure(1) 3-level architecture as considered by EU-initiative INSPIRE (Infrastructure for Spatial Information in Europe)

  13. Infrastructure(2) • Bottom level: (meta-)data sources • „Machinable“; read & interpret • Medium level: (value-added) services • Independent from specific databases • Top-Level: user-applications (GIS, browser, specialized services,…)  Requirement for common interfaces!

  14. Visualisation(1) • Context-specific representation / visualisation of results could effectively support the process of Data-Mining • Geospatial coherence often deducible by use of adequate visualisation • Conformance between mental model and cognitive style often better than in a simple table-view.

  15. Visualisation(2) Example: Identification of a pump on „Broad Street“ as source of cholera epidemic; Dr. John Snow, 1854, London

  16. References(1) • Wegener M, Fotheringham A., 2000, Spatial models and GIS: New Potential and New Models, London, Taylor & Francis • Petras V., 2004, Statistical Analysis of Geographic and Language Clues in the MARC Record. Technical report for the „Going Places in the Catalog: Improved Geographical Access“ project, University of California, http://metadata.sims.berkeley.edu/papers/Marcplaces.pdf • MetaCarta Inc. 2005, MetaCarta corporate brochure, http://metacarta.com/docs/Corporate_Brochure_06_05.pdf

  17. References(2) • „INSPIRE Architecture and Standards Position Paper“, INSPIRE (Infrastructure for Spatial Information in Europe), European Commission, Joint Research Centre, 2002 http://inspire.jrc.it/reports/position_papers/inspire_ast_pp_v4_3_en.pdf • Düren U., „XML, GML, NAS“, Landesvermessungsanstalt NRW http://www.landesvermessungsamt.nrw.de/neues/veranstaltungen/seminare/images/Vortraege_LDS_Kurs_40004_06/Dueren_LVermA_NRW/LDS_40004_XML_GML_NAS.pdf • W. Riekert, P. Treffler, 2000, „Georeferenzierung als Mittel zur Erschließung von Fachinformationen in Internet und Intranet“, 14. Int. Symposium Informatik im Umweltschutz http://v.hdm-Stuttgart.de/~riekert/vortraege/00ui.pdf

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