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What’s State of the Data?

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ESRI Federal GIS Conference 2015

08 February 2015

Derek Silva – NGA, Greg Brunner – ESRI

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Agenda

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• Background

• Principle Functions

• Development Objectives

• Quality Elements

• Web Application Demo

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Background

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• NGA Strategic Goal is to provide online, on-demand access

– Provide Geospatial-Intelligence (GEOINT) through data, products, and services

– Allow customers to operate mostly in a Self-Service mode

• Operations in the Data-Rich Environment – Move NGA from content producers, to

content managers– Provide insight into data quality

• State of the Data– A systematic approach to evaluate data so

customers will know its quality and mission suitability

– Facilitates GEOINT discovery, accessibility, usability and improvability

NGA Photo

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Principle Functions• Develop automated processes to

capture quality elements

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• Apply statistics and science to content management

• Anticipatorily alert of potential enrichment areas

• Compare data to current ground truth activities

• Incorporate formulas/models to generate on-the-fly statistics

Commercial

NGA (in-house)

International

Academia

Industry

TODAYPAST

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SituationUnderstand the current State

of the Data

• No global assessment capabilities regarding data density, accuracy & currency

• No systematic approach to data maintenance or enrichment

• No centralized application for user/customer interaction

BehaviorDevelop metrics to measure

data quality

• Develop analytic methodology to assign rankings/values to data

• Enhancement of the six quality elements established by the NGA Content Maturity Model

• Create graphic user interface effectively allowing interaction between NGA and its external customer base

ImpactUnderstand the desired future

end state of the data

• Identify the likely mission required: Humanitarian Aid & Disaster Relief (HADR), Offensive/Defensive Operations)

• Determine density requirements (Global, Regional, Local, Urban)

• One-stop-shop with a dynamically enabled service for data evaluation and quality transparency

Developmental Objectives

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Quality Elements Matrix

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Quality Elements Measure Description Data Sources

Completeness Feature Density per Specified Area Data Source A / Data Source B

Logical Consistency Average Number of Attribution Deficiencies per Feature over a Specified Area Data Source A / Attribution Requirements

Source Lineage Primary Data Source used in the Conflation / Integration Production Process Multiple Vector Data Sources

Positional Accuracy Spatial Relationship between Multiple Vector Data Sources Data Source A / Data Source B

Thematic Accuracy Scale Suitability and Density Requirements Population Data / Completeness Quality Element

Temporal Accuracy Vector Data Currency Data Source A / Change Detection Data Source

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Web Application Demo

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• State of the Data application benefits:

– A baseline to content management on a global scale

– A diagnostic tool to direct analyst to potential enrichment areas

– A systematic approach to data evaluation and quality transparency

– Statistical approach to the removal of subjective analysis

– Decrease in resources necessary to perform quality assurance

Summary

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