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Articles

A GML-based approach to automate spatial metadata updating

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Pages 231-250 | Received 15 Dec 2011, Accepted 20 Mar 2012, Published online: 07 Jun 2012
 

Abstract

With the huge amount of spatial data created and updated in short time frames and exchanged frequently over the Web, the demand for updating dataset and metadata in real time to provide users with the most up-to-date, precise, reliable, and complete metadata is increasing dramatically. So far, different metadata-updating approaches have been introduced to the spatial industry of which their issues and challenges have prohibited them from being adopted widely. Using the detached metadata data model and being limited to some dataset formats are some of these issues. To respond to this challenge, this article presents a new synchronization approach to automatically update the ISO 19115 core metadata elements which are affected by the (vector-based) dataset modification. Based on this approach, this article describes the major technical requirements considered necessary for the implementation phase, such as an integrated data model to couple dataset and metadata rooted in Geography Markup Language (GML) Application Schema, a mapping software application to support required Web Services, a user-friendly interface providing a visual modification facility, and an automatic metadata-updating process which is dataset format neutral. In order to prove the synchronization concept, the automatic synchronization approach has been prototyped and integrated with the GeoNetwork opensource environment. This article discusses the architecture designed for implementing the prototype system which contains three layers: storage, service (consisting of a synchronization service entitled ‘SYNC’), and application. The standards and open source technologies selected to develop the prototype system such as deegree, GeoNetwork, PostGIS, GML, Web Feature Service-Transaction, and CSW are then explained in more detail. Finally, the issues and challenges encountered during the implementation phase and the future direction are discussed in this article.

Acknowledgements

The authors wish to acknowledge the support of the Australian Research Council Linkage Project (LP0883933) on Automating and Integrating Spatial Data and Metadata Processes, its industry partners, and the members of the Centre for Spatial Data Infrastructures and Land Administration in the Department of Infrastructure Engineering, the University of Melbourne, in the preparation of this article and the associated research. However, the views expressed in this article are those of the authors and do not necessarily reflect those of these groups.

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