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Presentation charvat cerba Presentation Transcript

  • 1. Ontology as Knowledge Base for Spatial Data Harmonization Otakar Cerba, Karel Charvat University of West Bohemia, Plzen, Czech Republic Help Service Remote Sensing, Benesov, Czech Republic26.06.2012 INSPIRE 2012 1
  • 2. Objectives  Spatial data harmonization – basics  Domain ontology – theory & essential principles  Harmonization ontology – components  Example of harmonization based on ontology  Conclusion26.06.2012 INSPIRE 2012 2
  • 3. Spatial data harmonization  Activity for elimination or reduction of heterogeneities of various properties of spatial data to support interoperability  The elimination of the aspects of spatial data heterogeneity cannot be based on a creation of some uniform rules and data models, because, there are too many subjects with individual requirements – formats, precision, reference systems, terminology...  The harmonization processes should be divided into small and simple substeps26.06.2012 INSPIRE 2012 3
  • 4. Conditions of successful harmonization  Theoretical knowledge (domain, geomatic, IT...)  Understandable user requirements  Cooperation of experts  Sequence of harmonization substeps  Multi-level data description26.06.2012 INSPIRE 2012 4
  • 5. Why to harmonize  To enable a sharing, combining and publishing of data  To re-use existing sources  To improve data quality  To use web services and other automatic tools (SaaS)  To keep data interoperability (its cool!) All reasons  To increase the number of stakeholders are strongly  To meet legislation requirements interconnect ed26.06.2012 INSPIRE 2012 5
  • 6. Ontology – Theory  To improve communication between all participating subjects (cartographers, users, IT experts, domain experts...) … exactly defined … clearly syntaxsemantically defined concepts ...formal and formalized explicit … precise list of … directly specification of terms expressed sharing conceptualization … suitable for re- … way how a human use understands the world26.06.2012 INSPIRE 2012 and how it expresses6
  • 7. Ontology – Fundamental components  Class (Concept) – particular parts of domain structured by is-a relation  Individual – particular parts of domain that cannot be divided  Property – detail description of specifics of classes or individuals; object & data type properties  Axiom – logical constructs between elements of ontology (e.g. closure axiom, cover axiom)  Annotation – metadata, description, explanation26.06.2012 INSPIRE 2012 7
  • 8. Ontology: Classes & Properties Classes Properties26.06.2012 INSPIRE 2012 8
  • 9. Role of ontology in harmonization process Heterogeneous Data Data Description Harmonization Harmonized Tool(s) Data Knowledge & Experience To formalize and Rules & process Ontology Methods extra26.06.2012 INSPIRE 2012 informatio 9 n
  • 10. Data description in ontology26.06.2012 INSPIRE 2012 10
  • 11. Proposal of harmonization substeps BeforeAfter reasoningreasoning26.06.2012 INSPIRE 2012 11
  • 12. Inferred Ontology – Data Description26.06.2012 INSPIRE 2012 12
  • 13. LU/LC Legend mapping ontology26.06.2012 INSPIRE 2012 13
  • 14. LU/LC Legend mapping ontology – parameters26.06.2012 INSPIRE 2012 14
  • 15. LU/LC Legend mapping ontology – example Reasoning Equivalent classes Inferred (new) information Asserted (original)26.06.2012 information INSPIRE 2012 15
  • 16. LU/LC Legend mapping ontology26.06.2012 INSPIRE 2012 16
  • 17. Harmonization in ETL tool Input file Replication Transformation Changing Outputs (CLC)26.06.2012 to more to new data INSPIRE 2012 attribute (PELCOM etc.) 17 outputs models values
  • 18. Results of LULC data harmonization PELCOMCLC26.06.2012 INSPIREPELCOM 2012 18 After manual final harmonization
  • 19. Conclusion  Harmonization is not only technical process but also semantic...  It is necessary to consider a suitability of data sets from the view of − Data completeness − Data quality (depend for purposes of result) − Semantics of the data sets and classification systems  Ontologies enable knowledge transfer and better communication (including information sharing)26.06.2012 INSPIRE 2012 19
  • 20. Thank you for your attention and questions cerba@kma.zcu.cz charvat@ccss.cz26.06.2012 INSPIRE 2012 20