Databases Reference
In-Depth Information
Tabl e 2.
Seven exemplary research questions in the field of geo-semantics
What Kinds of Geospatial Classes Should be Distinguished?
How to Refer to Geospatial Phenomena?
How to Perform Geo-Reasoning & Querying over the Semantic Web?
How to Discover Events and how to Account for Geographic Change?
How to Handle Places and Moving Object Trajectories?
How to Compare, Align, and Translate Geospatial Classes?
How to Process, Publish and Retrieve Geodata?
can be thought of as the analogy to datum transformation, similarity measures
the proximity between classes in a semantic space as an analogy to distance in
space (and time). Geo-ontology alignment is concerned with the combination
of multiple ontologies to foster data reuse and integration. The fact that most
types of geographic information analysis, e.g. kernel methods, interpolation, or
point pattern analysis, are based on spatial auto-correlation and distance in
space, shows why semantic similarity is regarded crucial for making ontologies
and geo-semantics first class citizens of geographic information systems. The no-
tion of similarity also plays a key role in many cognitive approaches. Semantic
similarity and analogy reasoning also enable new types of interaction paradigms
and user interfaces which may ease browsing and navigating through (unfamil-
iar) geo-data and ontologies [45]. On the downside, similarity is highly sensitive
to context. Therefore, researchers have analyzed the influence of contextual in-
formation and proposed different techniques to account for such effects [55].
How to Process, Publish and Retrieve Geodata?
Standardized means for publishing, querying, retrieving, and accessing geodata
via Web services are provided by Spatial Data Infrastructures (SDI) as part of
the framework developed by the Open Geospatial Consortium (OGC). These
SDIs also support a variety of notification and processing services and, thereby,
go beyond simple data stores. Data and processing services can be combined
to model complex scientific workflows and be integrated as core elements in
cyberinfrastructures. To ensure a meaningful combination of services, however,
relies on formal specifications of the service inputs, outputs, side effects, and
parameters. Therefore, semantic markups for Web services have been actively
researched for years [71,27,93]. Examples of SDI specific proposals include the
work of Lemmens et al. [63], Vaccari et al. [96], and Lutz [67].
SDI services use their own markup languages (e.g., the Geographic Markup
language GML) and protocols, which differ considerably from the Semantic Web
technology stack. This prevents interoperability and makes a combination of the
Semantic Web and the Geo-Web challenging. Consequently, researchers have
proposed and implemented different approaches for a semantic enablement of
the Geo-Web. Janowicz et al. [46], for instance, specified transparent and bi-
directional proxies which enable users of both infrastructures to share data and
