CONNECT. TRANSFORM. AUTOMATE.

Welcome.

Berk Bayer

The Application of Feature Manipulation Engine (FME) to Maintain

Quality Control (QC) over Standardized Spatial Data

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.

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

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.

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.

FME & Data Quality

FME tools provide robust data management capabilities:

Geometry Validator transformer

Tester transformer

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.

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 features.

The tester transformer ensures that attribute values meet the established design constructs.

Attributes that violate design considerations are noted in the error report.

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 the business/program area, it may be published for external customers.

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)