A Semantic Modelling A Semantic Modelling Approach to Biological Approach to Biological Parameter Parameter Interoperability Interoperability Roy Lowry & Laura Bird British Oceanographic Data Centre Pieter Haaring RIKZ, Rijkswaterstaat, The Netherlands Ocean Biodiversity Ocean Biodiversity Informatics Informatics
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A Semantic Modelling Approach to Biological Parameter Interoperability
Ocean Biodiversity Informatics. A Semantic Modelling Approach to Biological Parameter Interoperability. Roy Lowry & Laura Bird British Oceanographic Data Centre Pieter Haaring RIKZ, Rijkswaterstaat, The Netherlands. Presentation Overview. The nature of the problem - PowerPoint PPT Presentation
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A Semantic Modelling Approach A Semantic Modelling Approach to Biological Parameter to Biological Parameter
InteroperabilityInteroperability
Roy Lowry & Laura BirdBritish Oceanographic Data Centre
Pieter HaaringRIKZ, Rijkswaterstaat, The Netherlands
• The nature of the problem• Dictionaries and data models• The starting position• Manual mapping• Automation through semantic matching• From dictionary to semantic model• Mapping semantic models• Semantic model applications• Conclusions and lessons learned
The Nature of the ProblemThe Nature of the Problem
• BODC and Rijkswaterstaat both have marine databases holding a wide range of physical, chemical and biological parameters
• Both were to be included pan-European metadatabases (EDIOS and SEA-SEARCH CDI) using a common discovery vocabulary
• BODC set up the vocabulary and obviously included a mapping to the BODC Parameter Dictionary
• Problem arose of how to provide a similar mapping for the Rijkswaterstaat
• If the Rijkswaterstaat data markup vocabulary could be mapped to the BODC Parameter Dictionary then the BODC discovery vocabulary mapping could be used
Dictionary to Semantic ModelDictionary to Semantic Model
• Semantic model developed from DONAR Semantic model developed from DONAR with an increased semantic element with an increased semantic element count to overcome shoe-horningcount to overcome shoe-horning
• Principle that semantic elements may be Principle that semantic elements may be combined automatically to produce text combined automatically to produce text descriptions maintaineddescriptions maintained
• Currently implemented as three sub-Currently implemented as three sub-modelsmodels
• Element superset will ultimately be Element superset will ultimately be created as a single modelcreated as a single model
Semantic Model ApplicationsSemantic Model Applications
• Semantic modelling is a lowest common denominator approach to metadata
• This is what makes it good for mapping
• The approach also offers the basis for user-controlled data discovery and interoperability User chooses the semantic element subset User data selection interaction based on the
subset vocabulary Automated interoperability requires more