Lars Harrie
Professor
Expert System to Enhance the Functionality of Clearinghouse Services
Author
Summary, in English
Abstract in Undetermined
Spatial data clearinghouses are one of the key features of a spatial data infrastructure (SDI). However, recent research indicates that few national clearinghouses function well, as the spatial data resources available cannot be satisfactorily accessed or optimally used. To improve the functionality, we propose that clearinghouses to be complemented with expert systems and semantic matching. The expert system facilitates automatic determination of candidate datasets and the conversion of the available data to the required data. A schema translator is also used to find similar data that might be used in other disciplines or other datasets by semantic matching. In order to accomplish this, we have developed a method of identifying available data and methods for data conversion. The methodology is implemented using standardized map services. Practical tests show that the discovery of available data in the clearinghouse satisfying users' requirements is substantially increased, which is an important step forward in building future SDIs. (C) 2010 Elsevier Ltd. All rights reserved.
Spatial data clearinghouses are one of the key features of a spatial data infrastructure (SDI). However, recent research indicates that few national clearinghouses function well, as the spatial data resources available cannot be satisfactorily accessed or optimally used. To improve the functionality, we propose that clearinghouses to be complemented with expert systems and semantic matching. The expert system facilitates automatic determination of candidate datasets and the conversion of the available data to the required data. A schema translator is also used to find similar data that might be used in other disciplines or other datasets by semantic matching. In order to accomplish this, we have developed a method of identifying available data and methods for data conversion. The methodology is implemented using standardized map services. Practical tests show that the discovery of available data in the clearinghouse satisfying users' requirements is substantially increased, which is an important step forward in building future SDIs. (C) 2010 Elsevier Ltd. All rights reserved.
Department/s
- Dept of Physical Geography and Ecosystem Science
- Centre for Geographical Information Systems (GIS Centre)
- eSSENCE: The e-Science Collaboration
Publishing year
2011
Language
English
Pages
159-172
Publication/Series
Computers, Environment and Urban Systems
Volume
35
Issue
2
Links
Document type
Journal article
Publisher
Elsevier
Topic
- Physical Geography
Keywords
- Web Service Composition
- Geospatial Web Services
- spatial data infrastructure (SDI)
- Expert system
Status
Published
ISBN/ISSN/Other
- ISSN: 0198-9715