Architectural styles and the design of network-based software architectures
Architectural styles and the design of network-based software architectures
Resource Discovery in a European Spatial Data Infrastructure
IEEE Transactions on Knowledge and Data Engineering
Linked data on the web (LDOW2008)
Proceedings of the 17th international conference on World Wide Web
SKOS core: simple knowledge organisation for the web
DCMI '05 Proceedings of the 2005 international conference on Dublin Core and metadata applications: vocabularies in practice
Bottom-Up Gazetteers: Learning from the Implicit Semantics of Geotags
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
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Accurate and timely place-based information from multiple sources is essential for making informed social protection decisions and rapid interventions. Developing solutions to the challenges presented by multi-disciplanary data integration provides a rationale, and mechanisms, to realize the broader goals of Linked Data. The Spatial Identifier Reference Framework (SIRF) combines principles of indentifiers and Linked Data to link place names to related data. Unlike generic placename databases, SIRF uses semantic web technologies to describe relationships between sources of place names and exposes the provenance of identifiers to disambiuguate and explain them. This paper will describe how SIRF uses explicit information models of the spatial datasets from which it builds an index of spatial identifiers in use. Within the SIRF infrastructure the spatial identifiers are harvested from geospatial data sets and published as Web based identifiers (Uniform Resource Identifiers- URIs). These URIs may be used to access multiple forms of data and metadata for the identified feature, including accessing provenance metadata and direct links back to the source datasets. Formal models using the "Application Schema" profile defined by the ISO TC 211 General Feature Model drive a repeatable harvesting process and are directly published as part of the provenance metadata. Mappings between the source and common models, used to drive transformations of harvested data into the common index are also presented together with an explanation of their role. Modelled properties, linked to vocabulary mappings, also expposed by web services, to provide a complete Web-accessible provenance of both the source and the interpretation used.