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Managing Data
Interoperability with FME
         Tony Kent
        Applications Engineer
               IMGS
IMGS
We deliver innovative spatial solutions
For the desktop, web and mobile
Built on our partner’s technology




Designed to meet the challenges of Government,
Mapping Agencies, and Utility & Communications
Customers
Safe Software
   Powering the flow of spatial data with
   FME




Enabling people to use their spatial data where, when and how they want to

            Most Used Spatial Interoperable Solution in Ireland



                                                        3
Why Spatial ETL?
Significant proliferation of different spatial data
formats and types
  Hundreds of formats, with more added each year
  Multiple types of data stored in multiple systems
  Unique data model requirements for each application




                                          4
Why Spatial ETL?

Traditional approaches to data translation
and data model manipulation are not viable
  Complex, inefficient and time-consuming




                                            5
Why Spatial ETL?
Increasing pressure for access to spatial data
  More users, beyond traditional GIS users
  Expectations of real-time custom data views, 24x7




                                          6
FME Capabilities
 The only complete spatial ETL solution

                     Translate spatial data from one
                      format to another

                     Transform spatial data into the
                      precise data model you need

                     Integrate different data types
                      into a single data model

                     Distribute spatial data to users
                     where, when and how they need it


                                          7
FME Desktop
Flexible and powerful spatial ETL toolset
Translate, transform and integrate data in hundreds of
formats
Graphical authoring environment

                                   Step 1 - Extract
                                   Select and add the source
                                   dataset(s)
                                   Step 2 - Transform
                                   Add transformers to manipulate
                                   the data as it moves from source
                                   to destination

                                   Step 3 – Load
                                   Load the transformed data into a
                                   destination format and source




                                            8
FME Workbench
Use simple
point and click
to easily define
spatial data
flows to
translate,
transform and
integrate your
data




                       9
Examples
Automating Ordnance Survey data updates
   Pushing NTF data to multiple GIS platforms
   Stripping out unnecessary data
   Adding custom styling and symbology – CAD
   E.g. Eircom, ESB, Fingal County Council


Publishing data to internal public portals
   Bulk and transactional updates
   Fire wall Friendly – use selected port
   Completely automated
   E.g. Dublin City Council
Open Data Challenge
You want to meet Open data requirements, but
your data is organized rather differently




                     ?
What FME does …




     ?
     Build data bridges
        to your SDI
SDI Harmonization
        Core Concepts
Harmonization: implied requirement for building
an SDI
Disparate sources must be mapped to a common
destination data model
Core to the harmonization workflow is a process
called schema mapping.
Delivered by services based on open standards
Harmonization Principles
Typical stages:
1. Evaluation
2. Assembly
3. Transformation
4. Validation
5. Publication


Based on the Spatial ETL concept (Extract,
Transform and Load), as applied to INSPIRE SDI’s
Evaluation
Assess destination schema and data
requirements
Assess source datasets and schema
Consider fundamental differences in
representation, resolution
Closely inspect actual representative
datasets
Data Assembly
  Assess the diversity of source data types:
      vector, raster, CAD, GIS, database, text, XML,
      web, 3D, sensor and non-spatial
  Review format and semantic translation
  needs
  Decide how to perform necessary joins
      ID joins, spatial relates, nearest neighbor, one to
      many relationships

Goal is to build a data structure that corresponds with your
published standard
Metadata – Data about data
Describes data structures
  tables
  geometry types
  data types
  fields

Describes data content
  coordinate system
  extent
  modification date
  quality, ownership, etc.
Metadata - Purpose
Key FME Metadata Capabilities
 Reading

 Writing

 Updating

 Harvesting

 Validating

 Integration with web services
CSW: Catalog Service for the Web

 Deegree

 GeoNetwork

 OpenGIS

 TerraCatalog
Data Transformation - Schema

Reshape source data
 to match required
 destination schema
Schema mapping
   feature type
   attribute name
   new attribute
   creation
   code lists
   conditional value
   mappings
Schema Mapping in FME

 Feature Type Mapping in FME Workbench




 Attribute Mapping in FME Workbench
FME Data Model Restructuring:
  Attribute Names & Values
  Value Mapping
FME SchemaMapper:
INSPIRE geographic names



                           FME Workspace




                           Name mapping




                           Name &
                           value mapping
Transformation: Geometry
Non-spatial to spatial
Geometry extraction (spatial to GML)
Representation transform: CAD drawing lines with labels to
GIS polygonal features with attributes
Coordinate System Reprojection (ED50 to ETRF89)
Simple to complex geometry
   Source point and polygon data to multiple geometric
   representations (city as point / area, river as line / area)
Generalization and interpolation
   Highly granular national and regional datasets often require thinning
   to be usable on pan-European scales
Validation
  Schema validation i.e. INSPIRE (xsds)
  Data integrity
     Unique IDs
     Geometric integrity (closed polygons)
     Null values (nullable?)
     Valid values: ranges and domain codes
     Data gaps
     Bounds
     Network integrity
  Custom validity rules specific to domain
  Validation automation via FME Server upload

Ensure data quality throughout the data transformation process
Publication
Produce INSPIRE compliant GML
Provide discovery, view or download
services, for WxS, GML and other desired
formats
Publish with FME Server or integrate with
your geo web server of choice:
Spatial Data Services
Publication with FME Server
Publish workspace to FME Server
   Store the workspace in a central repository
Make your FME workspaces available to others –over
the web




Register the workspace with one or more services   (Data
Streaming, Data Download, etc.)




                                                           28
FME Tools for INSPIRE
Format translation
Schema mapping
String and list manipulation
Data validation
Database load and extract
XML,GML,WFS: reading, validation,
publication
Web services: WFS, WMS,
integration with others
Metadata support
Enterprise services with FME Server
Other ETL Software Options

 Intergraph GeoMedia Fusion

 GeoKettle – Open Source

 Snowflake Software

 Spatial Data Integrator – Open Source
Summary
FME can provide all the tools to help build support your
data sharing needs:
   Integrate your data sources

   Manage your meta data catalogues

   Transform your data to standard schemas

   Publish the data in the required formats
Thank You



For more information:
  Email: ckirk@imgs.ie or tkent@imgs.ie
  Twitter: @Ciarankirk
  Web:     www.imgs.ie

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Managing data interoperability with FME

  • 1. Managing Data Interoperability with FME Tony Kent Applications Engineer IMGS
  • 2. IMGS We deliver innovative spatial solutions For the desktop, web and mobile Built on our partner’s technology Designed to meet the challenges of Government, Mapping Agencies, and Utility & Communications Customers
  • 3. Safe Software Powering the flow of spatial data with FME Enabling people to use their spatial data where, when and how they want to Most Used Spatial Interoperable Solution in Ireland 3
  • 4. Why Spatial ETL? Significant proliferation of different spatial data formats and types Hundreds of formats, with more added each year Multiple types of data stored in multiple systems Unique data model requirements for each application 4
  • 5. Why Spatial ETL? Traditional approaches to data translation and data model manipulation are not viable Complex, inefficient and time-consuming 5
  • 6. Why Spatial ETL? Increasing pressure for access to spatial data More users, beyond traditional GIS users Expectations of real-time custom data views, 24x7 6
  • 7. FME Capabilities  The only complete spatial ETL solution  Translate spatial data from one format to another  Transform spatial data into the precise data model you need  Integrate different data types into a single data model  Distribute spatial data to users where, when and how they need it 7
  • 8. FME Desktop Flexible and powerful spatial ETL toolset Translate, transform and integrate data in hundreds of formats Graphical authoring environment Step 1 - Extract Select and add the source dataset(s) Step 2 - Transform Add transformers to manipulate the data as it moves from source to destination Step 3 – Load Load the transformed data into a destination format and source 8
  • 9. FME Workbench Use simple point and click to easily define spatial data flows to translate, transform and integrate your data 9
  • 10. Examples Automating Ordnance Survey data updates Pushing NTF data to multiple GIS platforms Stripping out unnecessary data Adding custom styling and symbology – CAD E.g. Eircom, ESB, Fingal County Council Publishing data to internal public portals Bulk and transactional updates Fire wall Friendly – use selected port Completely automated E.g. Dublin City Council
  • 11. Open Data Challenge You want to meet Open data requirements, but your data is organized rather differently ?
  • 12. What FME does … ? Build data bridges to your SDI
  • 13. SDI Harmonization Core Concepts Harmonization: implied requirement for building an SDI Disparate sources must be mapped to a common destination data model Core to the harmonization workflow is a process called schema mapping. Delivered by services based on open standards
  • 14. Harmonization Principles Typical stages: 1. Evaluation 2. Assembly 3. Transformation 4. Validation 5. Publication Based on the Spatial ETL concept (Extract, Transform and Load), as applied to INSPIRE SDI’s
  • 15. Evaluation Assess destination schema and data requirements Assess source datasets and schema Consider fundamental differences in representation, resolution Closely inspect actual representative datasets
  • 16. Data Assembly Assess the diversity of source data types: vector, raster, CAD, GIS, database, text, XML, web, 3D, sensor and non-spatial Review format and semantic translation needs Decide how to perform necessary joins ID joins, spatial relates, nearest neighbor, one to many relationships Goal is to build a data structure that corresponds with your published standard
  • 17. Metadata – Data about data Describes data structures tables geometry types data types fields Describes data content coordinate system extent modification date quality, ownership, etc.
  • 19. Key FME Metadata Capabilities Reading Writing Updating Harvesting Validating Integration with web services
  • 20. CSW: Catalog Service for the Web Deegree GeoNetwork OpenGIS TerraCatalog
  • 21. Data Transformation - Schema Reshape source data to match required destination schema Schema mapping feature type attribute name new attribute creation code lists conditional value mappings
  • 22. Schema Mapping in FME Feature Type Mapping in FME Workbench Attribute Mapping in FME Workbench
  • 23. FME Data Model Restructuring: Attribute Names & Values  Value Mapping
  • 24. FME SchemaMapper: INSPIRE geographic names FME Workspace Name mapping Name & value mapping
  • 25. Transformation: Geometry Non-spatial to spatial Geometry extraction (spatial to GML) Representation transform: CAD drawing lines with labels to GIS polygonal features with attributes Coordinate System Reprojection (ED50 to ETRF89) Simple to complex geometry Source point and polygon data to multiple geometric representations (city as point / area, river as line / area) Generalization and interpolation Highly granular national and regional datasets often require thinning to be usable on pan-European scales
  • 26. Validation Schema validation i.e. INSPIRE (xsds) Data integrity Unique IDs Geometric integrity (closed polygons) Null values (nullable?) Valid values: ranges and domain codes Data gaps Bounds Network integrity Custom validity rules specific to domain Validation automation via FME Server upload Ensure data quality throughout the data transformation process
  • 27. Publication Produce INSPIRE compliant GML Provide discovery, view or download services, for WxS, GML and other desired formats Publish with FME Server or integrate with your geo web server of choice: Spatial Data Services
  • 28. Publication with FME Server Publish workspace to FME Server Store the workspace in a central repository Make your FME workspaces available to others –over the web Register the workspace with one or more services (Data Streaming, Data Download, etc.) 28
  • 29. FME Tools for INSPIRE Format translation Schema mapping String and list manipulation Data validation Database load and extract XML,GML,WFS: reading, validation, publication Web services: WFS, WMS, integration with others Metadata support Enterprise services with FME Server
  • 30. Other ETL Software Options Intergraph GeoMedia Fusion GeoKettle – Open Source Snowflake Software Spatial Data Integrator – Open Source
  • 31. Summary FME can provide all the tools to help build support your data sharing needs: Integrate your data sources Manage your meta data catalogues Transform your data to standard schemas Publish the data in the required formats
  • 32. Thank You For more information: Email: ckirk@imgs.ie or tkent@imgs.ie Twitter: @Ciarankirk Web: www.imgs.ie

Notas del editor

  1. http://en.wikipedia.org/wiki/Geospatial_metadatahttp://en.wikipedia.org/wiki/Metadata
  2. Supports searchesAllows you to review content without having to read all the data firstDiscover what’s availableSupport data management and updatesprovides parameters for automating processingControl accessTrack ownership
  3. Read metadata attributesXML reading, writing, updatingSchema readingReading from web sourcesIntegration with web servicesHarvest and validation capabilitiesCreation of your own web services