Geographic Information System Interoperability in Local Community Environment

The basic architecture of GeoNis framework is shown on Figure 2 [6,14] Generic architecture of GeoNis recognizes several different components that have important role in geoinformation discovering and retrieving process:

  • GIC – in each node of GeoNis framework there exist GIS application and corresponding (spatial and non-spatial) data sources. Data in these local data sources are accessible according to user privileges.
  • Wrapper/translator - component that translates information flow between information source and GeoNis system.
  • Semantic mediators - requests for specific data set are forward through.
  • Shared GIS server (Catalog Server) - maintains metadata and all shared/common geographic data as addition to domain oriented GIS applications.
According to GeoNis architecture every GIC environment can have several translators. There can be one translator for every information source in GIC environment. Ginis OLE DB data provider is an example of translator implementation [4]. This approach (unified methods for data access) allows simply chaining of translators. Also we can easily add new information sources without influence on other GIC environments. In order to do this we have to provide semantic mapping only for the GIC environment with new information source. In this way we have simplified the problem of semantic heterogeneity.

The total number of geo-data providers in local community environment is indeterminable and unlimited. This implies the need for a flexible approach that can deal with the existing and the future geo-data providers in interoperable systems. A standard model for spatial data is the first step to approach the solution for schematic and syntactic heterogeneity. The Open GIS Consortium (OGC) specification aims to solve the problem of heterogeneity at the spatial data modeling level. Because of that, GeoNis uses OpenGIS standard as common data model to represent geo-data at mediator level. Data models of local information sources are translated in common model using wrappers.

Semantic heterogeneity of the data sources in GeoNis is resolved using a hybrid ontology approach and methodology (and software support) for semantic mismatches resolving between terminologies. GeoNis solution to the problem of semantic heterogeneity is to formally specify the meaning of the terminology of each GIC using local ontology and to define a translation between each GIC terminologies (local ontologies) and an intermediate terminology (in top-level ontology) [15]. This methodology uses the ontology mappings between each community terminologies and a top-level ontology or the common data model, represented by IF-THEN rules.

GeoNis formal ontology consists of definitions of terms, and it includes concepts with associated attributes, relationships and constraints defined between the concepts and entities that are instances of concepts. In our system architecture it is assumed that the ontology is shared, and there exists commitment by the clients about data, which will be shared. Intent of our formal ontology is for sharing, merging, and querying data, but not for reading and efficient processing.

Conclusion
Interoperability in general, and especially semantic interoperability, will lead to dramatic organizational changes in GI community. Integration of diverse information sources has many advantages:

  • Quality improvement of data due to the availability of complete datasets.
  • Improvement of existing analysis and application of the new analysis.
  • Cost reduction resulting from the multiple use of existing information sources.
  • Avoidance of redundant data and conflicts that can arise from redundancy.
The GeoNis is a generalized framework, in which both schematic and syntactic heterogeneity is resolved by mediation and common data model. This framework is aimed to resolve interoperability problem in local, municipality environment. Our solution uses a mediator-based architecture for interoperability in local community environment, OpenGIS Simple Feature as the common model, and local ontologies for resolving semantic heterogeneity of data sources. The principles behind the ontology/mediation framework described in this paper are extensibility, relative autonomy of infrastructure nodes, and universal access to heterogeneous data sources from a variety of portals.

GeoNis uses widely accepted OpenGIS standard for geo-data modeling and representation on the mediator level. Changes in the OpenGIS standard have impact only on translators, not on information sources. GeoNis also enables adding legacy data sources in interoperability process. The only condition is the translator realization (implementation).

Significance of our work is based on usefulness of GeoNis tools and components for realization of interoperable geo-spatial and other (such as B2, see [16]) information nodes in local community organizations.

References

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