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Managing Data Interoperability with FME

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

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Managing Data Interoperability with FME

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  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

  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

  5. Why Spatial ETL? • Traditional approaches to data translation and data model manipulation are not viable • Complex, inefficient and time-consuming

  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

  7. FME Capabilities • The only complete spatial ETL solution • Translatespatial data from one format to another • Transformspatial data into the precise data model you need • Integratedifferent data types into a single data model • Distributespatial data to users where, when and how they need it

  8. FME Desktop • Flexible and powerful spatial ETL toolset • Translate, transform and integrate data in hundreds of formats • Graphical authoring environment Step 1 - ExtractSelect and add the source dataset(s) Step 2 - TransformAdd 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

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

  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 requirementfor 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: • Evaluation • Assembly • Transformation • Validation • Publication Based on the Spatial ETL concept (Extract, Transform and Load), as applied to INSPIRE SDI’s

  15. Metadata – Data about data Describes data structures • tables • geometry types • data types • fields Describes data content • coordinate system • extent • modification date • quality, ownership, etc.

  16. Metadata - Purpose

  17. Key FME Metadata Capabilities Reading Writing Updating Harvesting Validating Integration with web services

  18. 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

  19. Schema Mapping in FME Feature Type Mapping in FME Workbench Attribute Mapping in FME Workbench

  20. FME Data Model Restructuring: Attribute Names & Values • Value Mapping

  21. FME SchemaMapper: INSPIRE geographic names FME Workspace Name mapping Name & value mapping

  22. 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

  23. 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

  24. 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.) Publication with FME Server 24

  25. 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

  26. 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

  27. Thank You • For more information: • Email: ckirk@imgs.ie or tkent@imgs.ie • Web: www.imgs.ie

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