Classics From IJGIS 2006
DOI: 10.1201/9781420006377.ch17
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Overcoming the Semantic and Other Barriers to GIS Interoperability

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Cited by 39 publications
(47 citation statements)
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“…Sometimes one can argue the structural interoperability by highlighting the schematic heterogeneity (different message types). In the interoperability literature [27], semantic heterogeneity can be divided into cognitive and naming heterogeneities, and naming heterogeneity sometimes can be further subdivided into syntactic (different symbols) and structural (different expressions) [29].…”
Section: Semantic Evaluation Of Service Chainsmentioning
confidence: 99%
See 1 more Smart Citation
“…Sometimes one can argue the structural interoperability by highlighting the schematic heterogeneity (different message types). In the interoperability literature [27], semantic heterogeneity can be divided into cognitive and naming heterogeneities, and naming heterogeneity sometimes can be further subdivided into syntactic (different symbols) and structural (different expressions) [29].…”
Section: Semantic Evaluation Of Service Chainsmentioning
confidence: 99%
“…The importance of semantics on accessing and integrating geospatial information has long been recognized [27][28][29]. There are two levels of interoperability in the services: syntactic interoperability and semantic interoperability [10].The former requires that there is a technical connection, i.e., that the data can be transferred between Web services.…”
Section: Semantic Evaluation Of Service Chainsmentioning
confidence: 99%
“…The paper discusses main challenges of service interoperability, especially semantic heterogeneity [12], from the practical viewpoint of GI service integration into legacy systems. This is still one of the major burdens to successful integration of services and data in general [13].…”
Section: Introductionmentioning
confidence: 99%
“…As a consequence, communities prefer to create their own specification by: reusing elements of other specifications, such as Ecological Metadata Language EML [11]; or rewriting a complete new specification by themselves, e.g., Hydrologic Markup Language HydroML [36]. This lack of interoperability has plagued many interdisciplinary collaboration efforts to date [4], [18], [19], [34], and is one of the main obstacles that need to be overcome when connecting various research communities, the government, and the public for a more seamless data and information realm. More specifically, the description of similar datasets using different vocabularies or using similar vocabularies for different data sets results into what is called Bsemantic heterogeneity'' [13], [20], [35].…”
Section: Introductionmentioning
confidence: 99%