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Paul Smits, Anders Friis-Christensen European Commission, DG Joint Research Centre

Automatic Concept Space Generation in Support of Resource Discovery in Spatial Data Infrastructures. Paul Smits, Anders Friis-Christensen European Commission, DG Joint Research Centre Institute for Environment and Sustainability Spatial Data Infrastructures Unit TP 262, Ispra (VA), Italy.

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Paul Smits, Anders Friis-Christensen European Commission, DG Joint Research Centre

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  1. Automatic Concept SpaceGeneration in Support of Resource Discovery in Spatial Data Infrastructures Paul Smits, Anders Friis-Christensen European Commission, DG Joint Research Centre Institute for Environment and Sustainability Spatial Data Infrastructures Unit TP 262, Ispra (VA), Italy

  2. JRC’s Mission The mission of the JRC is to provide customer-driven scientific and technical support for the conception, development, implementation and monitoring of EU policies. As a service of the European Commission, the JRC functions as a reference centre of science and technology for the Union. Close to the policy-making process, it serves the common interest of the Member States, while being independent of special interests, whether private or national.

  3. Outline • Introduction • Objectives of the study • Approach • Results • Conclusions

  4. Introduction – components of a European SDI GI Policy GI standards Fundamental GI data sets Spatial Information Services

  5. Introduction INSPIRE requirements • metadata* • spatial data sets and spatial data services* • network services* • EU geo-portal • access and rights of use for Community institutions and bodies** • monitoring and reporting mechanisms** • process and procedures * technical: under JRC responsibility ** legal/procedural: under Eurostat responsibility

  6. Introduction • European interoperability framework for pan-European eGovernment services • Recommendations related to multilingualism, e.g., • For the Pan-European services provided via portals, the top-level EU portal interface should be fully multilingual, the second-level pages (introductory texts and the descriptions of links) should be offered in the official languages and the external links and related pages on the national websites should be available in at least one other language (for example English) in addition to the national language(s). http://europa.eu.int/idabc

  7. Introduction • Issues on Multilingualism identified by the INSPIRE DT on Network Services • only mentioned in the context of the interoperability of spatial data sets and services for key attributes and corresponding multilingual thesauri • Granularity: should the list of available languages be a service feature or at the data set or even at the feature attribute level ? • Metadata/Data: should only metadata be multilingual or datasets as well ? • Attributes label versus Attribute value: Should only attributes label be multilingual or should the attribute’ values be as well multilingual?

  8. Introduction

  9. Outline • Introduction • Objectives of the study • Approach • Results • Conclusions

  10. Objective of the study • Focus on discovery of resources • Answer question: • Is, from a technical point of view, a common ontology or thesaurus desirable and feasible for multi-lingual resource discovery in a European Spatial Data Infrastructure?

  11. Outline • Introduction • Objectives of the study • Approach • Results • Conclusions

  12. Approach • Implement and extend work of H. Chen, et al., "A Parallel Computing Approach to Creating Engineering Concept Spaces for Semantic Retrieval: The Illinois Digital Library Initiative Project," IEEE Transactions on Pattern Analysis and Machine Intelligence vol. 18 pp. 771-782, 1996. • Integrate thesauri, vocabularies and gazetteers in resource discovery • Experiments P. Smits, A. Friis-Christensen, Resource Discovery in a European Spatial Data Infrastructure. IEEE Transactions on Knowledge and Data Engineering (accepted for publication)

  13. Approach • What is a Concept Space? • Simply put: • An index of all concepts existing in a metadata repository • With numerical relationships defined between any two concepts • To be queried by associative retrieval

  14. Approach • Two-step approach • Creation of multi-lingual concept space • Associative retrieval based on a neural network H. Chen, B. Schatz, T. Ng, J. Martinez, A. Kirchhoff, C. Lin, A parallel computing approach to creating engineering concept spaces for semantic retrieval: the Illinois digital library initiative project. IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, August 1996, pp. 771-782.

  15. Approach • Creation of the multi-lingual concept space • Collection of resource descriptors • Object filtering and indexing • identify those concepts and terms that we already have in our human-created ontology which includes any thesauri and vocabulary • to filter out any irrelevant terms like stop words in order to improve performance • to store any remaining terms in the concept space

  16. Approach - Associative query • Initialize the associative retrieval • The neural network is initialized at query time by assigning initial membership values to the units of the neural network = concepts in the Concept Space • Terms in the concept space that match exactly a query term: 1 • Partial matches get membership value < 1 • Terms that do not match the query: 0

  17. Approach - Associative query • Initialize the associative retrieval Wij = 0 Query: “soil” Wij = 0.7 Soil, bodem 1 Sub-surface 0 information 0 Situation at t=0

  18. Approach - Associative query • Iterate though the neural network Wij = 0 Wij = 0 Wij = 0.7 Wij = 0.7 Soil, bodem Soil, bodem 1 1 Sub-surface Sub-surface 0 0.7 information information 0 0 Situation at t=0 Situation at t=1

  19. Approach - Associative query • Link membership values of concepts to resource descriptors Wij = 0 • Membership > threshold? • Use index to find resources that contain the concept • Order found resources in order of relevance, based on membership values Wij = 0.7 Soil, bodem 1 Sub-surface 0.7 information 0 Situation at t=1

  20. Outline • Introduction • Objectives of the study • Approach • Results • Conclusions

  21. Results • Creating the metadata repository

  22. Results

  23. Results

  24. Results • Query computationally expensive

  25. Outline • Introduction • Objectives of the study • Approach • Results • Conclusions

  26. Conclusions from the study • It will be impractical to rely only on one common ontology for resource discovery in a European SDI • The approach of using human-created ontologies in combination with automatic concept space generation and associative retrieval is a powerful means to the discovery of geospatial resources. • Proposed approach is useful and merits further investigation and development • The importance of structured information, using metadata standards, is underlined by our study and is also a basic assumption of our work.

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