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CONNECT. TRANSFORM. AUTOMATE.
Welcome.
Berk Bayer
The Application of Feature Manipulation Engine (FME) to Maintain
Quality...
Introduction
 I am a Data Management Specialist with the
Northrop Grumman Corporation working at the
Bureau of Land Manag...
Today’s Agenda
 Advantages of Data Standardization
 FME & Data Quality
 Geometry Validator Transformer
 Building Geome...
Advantages of Data
Standardization
 Data standardization ensures common
understanding of content and quality.
 Data stan...
FME & Data Quality
 Quality Control (QC) over standardized data:
Improves data integrity.
Builds confidence in critical...
FME & Data Quality
 FME tools provide robust data management
capabilities:
Geometry Validator transformer
Tester transf...
Geometry Validator Transformer
 As features are harvested from the states, they
undergo a geometry validation process:
F...
Building Geometry Checks
 Our organization uses a similar outline of the
diagram below to validate feature geometry:
Building Geometry Checks
Building Geometry Checks
Building Geometry Checks
Building Geometry Checks
Tester Transformer
 Our organization uses the tester transformer to
evaluate the attribute integrity of harvested
feature...
Building Attribute Checks
Building Attribute Checks
Building Attribute Checks
Building Attribute Checks
Building Attribute Checks
Building Attribute Checks
Interpreting The Error Table
Maintaining QC
 Data is periodically harvested from the states.
 Once the data satisfies QC measures, as
established by ...
Thank You!
 Questions?
 For more information:
 Berk Bayer (bbayer@blm.gov)
 Tom Chatfield (tchatfie@blm.gov)
 Jeff Sa...
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The Application of Feature Manipulation Engine (FME) to Maintain Quality Control (QC) over Standardized Spatial Data

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Presented by Berk Bayer, Northrop Grumman Corporation

See more FME World Tour 2014 presentations at www.safe.com/recap2014

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The Application of Feature Manipulation Engine (FME) to Maintain Quality Control (QC) over Standardized Spatial Data

  1. 1. CONNECT. TRANSFORM. AUTOMATE. Welcome. Berk Bayer The Application of Feature Manipulation Engine (FME) to Maintain Quality Control (QC) over Standardized Spatial Data
  2. 2. Introduction  I am a Data Management Specialist with the Northrop Grumman Corporation working at the Bureau of Land Management National Operations Center (NOC) in Denver, Colorado.  The NOC harvests and maintains standardized spatial data from the twelve administrative states in the Bureau.
  3. 3. Today’s Agenda  Advantages of Data Standardization  FME & Data Quality  Geometry Validator Transformer  Building Geometry Checks  Tester Transformer  Building Attribute Checks  Interpreting The Error Table  Maintaining QC
  4. 4. Advantages of Data Standardization  Data standardization ensures common understanding of content and quality.  Data standardization serves to resolve data anomalies and data conflicts.  Data standardization optimizes resources needed for organizational data calls.
  5. 5. FME & Data Quality  Quality Control (QC) over standardized data: Improves data integrity. Builds confidence in critical business decisions. Builds trust in the organization.  FME helps to develop an effective QC plan.
  6. 6. FME & Data Quality  FME tools provide robust data management capabilities: Geometry Validator transformer Tester transformer
  7. 7. Geometry Validator Transformer  As features are harvested from the states, they undergo a geometry validation process: FME attempts to repair any features with null, degenerate/corrupt or self-intersecting geometries. An error report is created showing all features and it’s status as passing, repaired, or not repaired.
  8. 8. Building Geometry Checks  Our organization uses a similar outline of the diagram below to validate feature geometry:
  9. 9. Building Geometry Checks
  10. 10. Building Geometry Checks
  11. 11. Building Geometry Checks
  12. 12. Building Geometry Checks
  13. 13. Tester Transformer  Our organization uses the tester transformer to evaluate the attribute integrity of harvested features.  The tester transformer ensures that attribute values meet the established design constructs.  Attributes that violate design considerations are noted in the error report.
  14. 14. Building Attribute Checks
  15. 15. Building Attribute Checks
  16. 16. Building Attribute Checks
  17. 17. Building Attribute Checks
  18. 18. Building Attribute Checks
  19. 19. Building Attribute Checks
  20. 20. Interpreting The Error Table
  21. 21. Maintaining QC  Data is periodically harvested from the states.  Once the data satisfies QC measures, as established by the business/program area, it may be published for external customers.
  22. 22. Thank You!  Questions?  For more information:  Berk Bayer (bbayer@blm.gov)  Tom Chatfield (tchatfie@blm.gov)  Jeff Safran (jsafran@blm.gov)  Northrop Grumman Corporation (www.ngc.com)  Bureau of Land Management (www.blm.gov)

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