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Comparing points of view underlying databases

http://geonto.lri.fr http://recherche.ign.fr/labos/cogit. Comparing points of view underlying databases. Sébastien Mustière IGN / COGIT Lab. Institutional context. Research on database integration in a NMA Started in 1993 Reference topographic data / user thematic data

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Comparing points of view underlying databases

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  1. http://geonto.lri.fr http://recherche.ign.fr/labos/cogit Comparing points of view underlying databases Sébastien Mustière IGN / COGIT Lab

  2. Institutional context Research on database integration in a NMA Started in 1993 Reference topographic data / user thematic data French research project GeOnto on "Creation, Comparison and Use of Geographic Ontologies" 2008-2011 IGN / COGIT Lab (database integration) INRIA / Univ. Orsay (ontology alignment) CNRS / Univ. Toulouse (natural language processing for ontologies) Univ. Pau (natural language processing and spatial annotation of texts)

  3. Multiplicity of points of view • Need for understanding differences btw pieces of geographic information • For data integration, evaluation of fitness for use, generalisation…

  4. 16 Zimbabwe  14 12 10 Sudan  Tree Height (m) 8 Turkey  Tanzania Mozambique  Morocco  Ethiopia UnitedNations -FRA2000 New Zealand  6 Denmark  PNG  Luxembourg  Netherlands  SADC Namibia  Malaysia  Cambodia  Belgium UNESCO Jamaica  Australia  Somalia  Japan  4 Israel  UnitedStates Gambia  Switzerland  South Africa  Mexico  2 Kyrgyzstan Kenya  Portugal Estonia 0 0 10 20 30 40 50 60 70 80 90 Canopy Cover (%) Comparing schemas is not enough • Schemas define the organisation of data • Schemas do not (sufficiently) define semantics EXAMPLE Unique schema (e.g. INSPIRE schema) Data 1 Data 2 Different data (e.g. National data) from [Comber, Ficher et Wadsworth 2005]

  5. Point of view 1 Point of view 2 Specifications Specifications Global approach DB 1 DB 2 ???

  6. From specifications to taxonomies • Natural Language Processing to semi-automatically create ontologies from textual documents[Laurence 2006] • Done: 2 taxonomies (Fre/Eng) from 2 databases specifications, 700 concepts each • Under dvpt: more general tools • Under dvpt: taxonomy from old travelers books • Under dvpt: heavier ontologies (relations...)

  7. Modeling specifications • Formal model definition [Gesbert 2005] done • Use of some natural language processing tools for instantiating the model [Picard 2007] done “All permanentwatercourses are captured except aqueducts...”

  8. Using formal specifications and taxonomies • Portal for discovering databases [Horel 2007]to be ctd • Data matching [Olteanu 2008] done • Schema matching [Abadie 2009] under dvpt

  9. Ontology/Taxonomy fusion • Alignment (matching) and fusion Ongoing work

  10. Comparing ontologies • Open problem: A distance between ontologies • To answer to... • Same point of view but different vocabularies? • Different thematic areas? • Different levels of detail? • Fusion is pertinent?... • ...in the context of my “real” ontologies • Very light (even taxonomies, list of terms) • Very imperfect (automatically made) • Something specific for geographic ontologies?

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