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Semantic schema for geonames

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Presentation made at INSPIRE 2013, in the Semantics session, by Feroz Farazi, of University of Trento. …

Presentation made at INSPIRE 2013, in the Semantics session, by Feroz Farazi, of University of Trento.
The research leading to these results has received funding from the CUbRIK Collaborative Project, partially funded by the European Commission's 7th Framework ICT
Programme for Research and Technological Development under the Grant agreement no. 287704.

Published in: Technology, Education

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  • 1. A SEMANTIC SCHEMA FOR GEONAMES Enzo Maltese Feroz Farazi
  • 2. Index • Introduction • GeoNames • DERA Methodology • Faceted Ontology • Semantic Schema • Result • Conclusion INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 3. Introduction • With the proliferation of the Web, dataset publishing is also getting a momentum • With Linked Open Data (LOD) initiative • Old datasets are published in machine readable format • Many new datasets are made available on the Web • As part of LOD initiative essentially we observe that datasets are there with increased • Machine readability • Availability • Ease of finding through links INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 4. Introduction • However, in the LOD initiative more emphasis is given on the quantity of the data than its quality • In this work we proposed a semantic schema that can help improve the quality while enforcing it on the data • Our approach is domain independent • We performed a detailed case study using GeoNames INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 5. GeoNames • GeoNames is a geo-spatial database consists of various locations of all countries • It includes geographical data • Place names in various languages • Latitude • Longitude • Altitude • Class • Latitude and longitude coordinates are stored according to the WGS84 INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 6. GeoNames • It currently contains around 8 million geographic names for around 7 million unique places • The places are classified into 9 broader categories called feature classes • They are further divided into 667 classes, most of them have a natural language description • The data is available free of charge, can be used under a creative commons attribution license INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 7. DERA Methodology • A methodology for developing ontology • It allows building domain specific ontologies • However, it can be used to construct ontology for any domain • In DERA, a domain consists of three components namely entity class, relation and attribute. D=<E, R,A> • E is a tuple <C, e>, where C represents set of concepts and e represents set of entities INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 8. DERA Methodology • Methodology: • Step 1: Identification of the relevant terms • Step 2: Analysis • Step 3: Synthesis • Step 4: Standardization • Following the above steps leads to the creation of a set of facets INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 9. Faceted Ontology • Facet is a hierarchy of homogeneous concepts describing an aspect of the domain (e.g., space), where each term in the hierarchy denotes an atomic concept • A facet is a distinctive property of a set of concepts that can help in differentiating one group from another • Faceted ontology is an ontology in which concepts are organized into facets • S. R. Ranganathan was the first to introduce the faceted approach • GeoWordNet is an example of a faceted ontology consists of facets such as body of water, geological formation and administrative division INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 10. Faceted Ontology Body of water •Flowing body of water •Stream •Brook •River •Still body of water •Pond •Lake Populated place •City •Town •Village Landform •Natural depression •Oceanic depression •Oceanic valley •Oceanic trough •Continental depression •Trough •Valley •Natural elevation •Oceanic elevation •Seamount •Submarine hill •Continental elevation •Hill •Mountain INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 11. Semantic Schema • The usage of a geospatial ontology does not solve all the problems • In fact, GeoNames lacks sufficient constraints on the domain and range of the attributes • Moreover, it lacks corresponding mechanisms to enforce them which can guarantee for an adequate quality of the data • We define a semantic schema as a set of constrains on the domain and range of • the attributes (e.g. population) • the relations (e.g. capital) INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 12. Semantic Schema • Such constraints should prevent the attribute population to have a negative value • While it is fine for cities to have such attribute, this should be prevented for streams • The schema is semantic-aware because • the domain of attributes and relations and • the range of relations are always a class and its more specific classes taken from the geospatial ontology • For instance, if we specify that the domain of the attribute population is populated place INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 13. Semantic Schema • We assume it to apply also to city, town and village (more specific classes in the ontology) • The purpose of the schema is expressly to define what is legal in terms of • attributes • relations • corresponding values • Enforcing the schema corresponds to verifying the consistency of the dataset w.r.t. such constraints INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 14. Semantic Schema Attribute Name Definition Domain (main class) Range Population the people who inhabit a territory or State Populated Place Long > 0 Altitude elevation above sea level Location but Undersea Float in [-423, 8848] Area the extent of a 2- dimensional surface enclosed within a boundary Location Float > 0 Capital A seat of government Geo-political entity Populated Place INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 15. Semantic Schema • The range of altitude was set by referring to the altitude of • the Dead Sea (the lowest) • the Mount Everest (the highest) INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 16. Result • In GeoNames the Dead Sea is represented with negative altitude set to −405 m. • Surprisingly, GeoNames contains other 45 locations with same altitude of the Dead Sea • two other locations are reported to be even lower than the Dead Sea (Nahal Amazyahu and `Arvat Sedom) • The domain of population includes several unexpected classes such as airport, stream and garden • We removed population from corresponding entities in the ontology INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 17. Result • We found several entities with elevation set to -9999 that is used in GeoNames to encode an unknown value • We removed elevation from corresponding entities in the ontology • In the range of capital, 3 entities are encoded as cities (e.g. Jerusalem) while all the others as capitals • This is not wrong, but at least this is not homogeneous • We represented them homogeneously INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 18. Conclusion • We have stressed the need for an integrated approach to effectively support semantic interoperability between different geospatial applications • The proposed solution • Consists in the usage of a geospatial faceted ontology providing the terminology of the geospatial domain and • A semantic schema that, by establishing precise constraints on the domain and range of the attributes and the relations, guarantees a higher level of data quality INSPIRE Conference – June 25th 2013 Feroz Farazi – University of Trento
  • 19. Thank you Questions?

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