MetaData Retrieval (MDR) is a software module for the enrichment of geo-referenced maps with metadata. Metadata are annotations on spatial locations that are taken from the Volunteered Graphical Information projects like OpenStreetMap and GeoNames. The MDR user acts with a user-friendly GUI, a Query By Example in which the user specifies in a multi-dimensional data model the spatial objects for which new information are searched for. The request is translated into SQL queries for the database and in web service requests for OpenStreetMap and GeoNames. Downloaded annotations are checked and compared with the history for duplicate elimination. Annotations are presented to the user in the context of an interactive, geo-referenced map and in a hierarchical, ontological structure, that is a facility for indexing and browsing. On demand, an annotation is stored in the system history. Finally, the user can filter the annotations that characterize a specified area by a statistical filter that compares the annotation frequency with the neighborhood.

MetaData Retrieval: A Software Prototype for the Annotation of Maps with Social Metadata

MEO, Rosa;ROGLIA, ELENA;
2011-01-01

Abstract

MetaData Retrieval (MDR) is a software module for the enrichment of geo-referenced maps with metadata. Metadata are annotations on spatial locations that are taken from the Volunteered Graphical Information projects like OpenStreetMap and GeoNames. The MDR user acts with a user-friendly GUI, a Query By Example in which the user specifies in a multi-dimensional data model the spatial objects for which new information are searched for. The request is translated into SQL queries for the database and in web service requests for OpenStreetMap and GeoNames. Downloaded annotations are checked and compared with the history for duplicate elimination. Annotations are presented to the user in the context of an interactive, geo-referenced map and in a hierarchical, ontological structure, that is a facility for indexing and browsing. On demand, an annotation is stored in the system history. Finally, the user can filter the annotations that characterize a specified area by a statistical filter that compares the annotation frequency with the neighborhood.
2011
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)
Athens
5-9 September, 2011
Proceedings of the 26th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Springer-Verlag
LNCS vol. 6913
III
642
645
9783642238079
http://www.ecmlpkdd2011.org/
spatial data; annotation; metadata; social network
Meo, Rosa; Roglia, Elena; Ponassi, E.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/131196
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