Reference Information Specifications for Europe RISE Results & Lessons Learnt
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Transcript of Reference Information Specifications for Europe RISE Results & Lessons Learnt
Reference Information Specifications for Europe
RISE Results & Lessons Learnt
Wyn Cudlip (QinetiQ)
www.eu-rise.org
RISE Results, Porto, 5th July, 2007. V1.0 Page 2
Issues
• How to satisfy INSPIRE and other EU Directives on data
sharing and re-use without completely re-engineering
the information databases.
• Also applies to cross-border and other cross-sector data
harmonisation issues.
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RISE Project goals
• Define Methodology & Guidelines Document• for the creation of geospatial Data Product Specifications (DPS), consistent with
international and industrial standards.
• Test the Methodology • by creating test harmonised DPS for Hydrography, LandCover and Elevation; as
example input datasets to diffuse nutrient leakage modelling for the Water Framework Directive (WFD).
• Test the harmonised Data Product Specifications (hDPS) • in an on-line “Test Environment” with data from test areas (in Sweden & Norway).
• Demonstrate the automatic creation of harmonised Data Products
• from existing databases using schema translation
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RISE consortium
EuroGeographics
Lantmäteriet
BKG
Public Institutions -Source data providers
QinetiQ
OGC-Europe
IndustryTechnology
“HarmonisationAdvisory Committee & Planning Board”
“WFD & GMES”“Key stakeholders”
Users and applications2 yr FP6 Project; started Sept. 05.
Working relationship with MOTIIVE.
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Approach
Requirements Use Cases
Conceptual schema (UML)
Testing
Prototype
Application schema (GML) Cost
benefit
Exploitation guidelines
RISEMethodology
Data Product Specification
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Key Steps in the development of “harmonised” Data Product Specification
• Analyse Use Cases• To define requirements
• Develop Conceptual Schema (in UML)• Including Feature Type Catalogue and Data Dictionary update
• Develop GML Application Schema• this can be automated
• e.g., UGAS, UML to GML conversion tool
• Define harmonised Data Product Specification
• Data Products created from existing data
• Goal: to create “on the fly” with suitable server software
Use CaseDevelopment
Use CaseDevelopment
Requirementsand Feature Types
Identification
Requirementsand Feature Types
Identification
Data Dictionary Update
Data Dictionary Update
DPS and App SchemaDevelopment
DPS and App SchemaDevelopment
Implementation,testing and validation
Implementation,testing and validation
Use CaseDevelopment
Use CaseDevelopment
Requirementsand Feature Types
Identification
Requirementsand Feature Types
Identification
Data Dictionary Update
Data Dictionary Update
DPS and App SchemaDevelopment
DPS and App SchemaDevelopment
Implementation,testing and validation
Implementation,testing and validation
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RequirementsRequirementsRequirementsAs-is analysis
Gap analysis
Use CaseDevelopment
Use CaseDevelopment
Use CaseDevelopment
Use CaseDevelopment
Requirementsand Feature Types
Identification
Requirementsand Feature Types
Identification
Requirementsand Feature Types
Identification
Requirementsand Feature Types
Identification
App SchemaDevelopmentApp SchemaDevelopmentApp SchemaDevelopment
Data ProductSpecificationDevelopment
Implementation,testing and validation
Implementation,testing and validation
Implementation,testing and validation
Implementation,testing and
validation(using WFS)
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Key assumptions
Mandatory:• Overview• Specification scopes• Data product identification• Data content and structure• Reference systems• Data quality• Data product delivery• Metadata
Optional:• Data capture• Data maintenance• Portrayal• Additional information
• A Data Specification is based on a data product specification (DPS) according to ISO 19131. Such a DPS includes the following sections:
• RISE harmonisation is concerned with more than just data content and structure.
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1.2 Reference model
1. INSPIRE Information Model
1.7 Object referencing modelling
1.6 Coordinate refe-rencing and units model
1.1 INSPIRE Principles
2. Operational components/registers
3. Guidelines & Best Practice
2.2 Terminology
1.3 Application Schemas
2.1 Identifier Management
2.4 Dictionaries
1.8 Data translation model/guidelines
2.3 Feature catalogues 2.5 Conformance
1.4 ISO 19100 Profile
1.5 Multi-lingual text andcultural adaptibility
3.1 Metadata
3.2 Maintenance
3.3 Quality
3.4 Data Transfer
3.5 Derived re-porting & multiple representations
1.9 Portrayal model 3.6 Consistency between data
3.7 Data capturing
Data Harmonisation Components – Overview
(developed by INSPIRE Drafting Team „Data Specifications“ in collaboration with RISE; RISE
will focus on the methodology, the DT will focus on generic aspects of the conceptual model)
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Relevant ISO Standards
• UML ISO 19103• Conceptual Schema ISO 19107/8/9• Application Schema ISO 19109• Feature Type ISO 19109• Data Dictionary ISO 19126• Data Product Specification ISO 19131• Quality ISO 19113/5• Metadata ISO 19115• Multi Lingual ISO 19139• Portrayal ISO 19117• GML ISIO 19136• Translating WFS ISO 19142+43
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RISE Deliverables
RequirementsRequirementsRequirementsRequirements
Use Use CasesCasesUse Use
CasesCases
MethodologyMethodology
Conceptual Conceptual SchemaSchema
Conceptual Conceptual SchemaSchema
TestingTestingTestingTesting
PrototypePrototypePrototypePrototype
GMLGMLApplicationApplication
SchemaSchema
GMLGMLApplicationApplication
SchemaSchemaCost Benefit Cost Benefit
AnalysisAnalysisCost Benefit Cost Benefit
AnalysisAnalysis
Exploitation Exploitation GuidelinesGuidelines
Exploitation Exploitation GuidelinesGuidelines
Data Data SpecificationSpecification
Data Data SpecificationSpecification
ArchitectureArchitectureArchitectureArchitecture
Data Harmonisation Requirements ReportData Harmonisation Requirements ReportData Harmonisation Requirements ReportData Harmonisation Requirements Report
Use Case DescriptionsUse Case DescriptionsUse Case DescriptionsUse Case Descriptions
Exploitation GuidelinesExploitation GuidelinesExploitation GuidelinesExploitation Guidelines
Services Architecture OutlineServices Architecture OutlineServices Architecture OutlineServices Architecture Outline
Cost Benefit ReportCost Benefit ReportCost Benefit ReportCost Benefit Report
Test Environment ReportTest Environment ReportTest Environment ReportTest Environment Report
GML Application SchemaGML Application SchemaGML Application SchemaGML Application Schema
Data Product SpecificationData Product SpecificationData Product SpecificationData Product Specification
Conceptual Schema in UMLConceptual Schema in UMLConceptual Schema in UMLConceptual Schema in UML
Methodology & Guidelines for Use Case & Schema DevelopmentMethodology & Guidelines for Use Case & Schema DevelopmentMethodology & Guidelines for Use Case & Schema DevelopmentMethodology & Guidelines for Use Case & Schema Development
Drafts available now; final versions in September 2007
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Methodology & Guidelines Document
• V1.0 available. http://www.eu-rise.org/
• Used by the INSPIRE Drafting Team on Data
Specifications for their “Guidelines” Document.
• Used by the MOTIIVE Harmonisation Project
• Revised version due in September 2007.
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USE Case Architecture
HydrographyLandcover Clearcuts DEM
Source Data
(WFS/WCS)
Use Case Actors:
Data Providers
LAN, WAN, WWW
HydrographyAttributes
WFS/WCS
LAN, WAN, WWW
Processing Services
Use Case Actors:
Data Integrators
Use Case Actors:Users
harmoniseddata products
modelling
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Testing
• Three Themes
• Hydrography (i.e. catchment area polygons; river and lake segments)
• Landcover (i.e. RISE defined scheme (aggregated CORINE type)
• Elevation (i.e. uniform grid of Digital Elervation Model (DEM)
• Two Test Areas
• Vindan (East Sweden)
• Enningsdalsalven
(Swedish Norwegian Borders)
Vindan
Enningsdalsalven
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UML Diagram
ElevationLandcover
Hydrography(riverbasin and river/lake network)
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Schema Translation
• Schema translation definitions created with the use of Matching Tables.
• These have to be generated by domain experts.
Example of schema translation with Snowflake’s “Go Publisher”.
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RISE Test Environment• Demonstrate the creation of harmonised data products
• “on-the fly” from existing data sets
• Allow evaluation of the data products (and hence the specifications)
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Conclusion
• RISE has produced a Methodology & Guidelines document for the creation of harmonised Data Product Specifications.
• Several other documents have also been produced including a number related to schema development.
• A RISE Test Environment has shown how hDP can be produced “on the fly” from existing information through schema translation.
• Some types of “missing information” can be created automatically without any database intervention. In practice, the degree of automation will depend on how much information is missing from the input existing datasets.
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Lessons Learnt
• Harmonisation must be driven by real requirements• need to avoid lowest common denominator effect.
• or compromises which satisfy nobody.
• Hence importance of Use Cases
• Interface standards need further development• E.g. for access control, handling time series
• Enhancement to WCS, improved integration with SOAP etc.
• Software tools require further development• E.g. Improved integration of Clients, WMS, WFS and WCS
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Issues for discussion
• How to maintain project results after the end of the Project?
• How best to influence Standards Bodies?• E.g. Specify requirements; support testbeds?
• Commercial versus Open-Source Software?