1. Mapping Geospatially Enabled Systems to
Enterprise Architecture and Analytics
Dennis Crow, Ph.D, PMP

2. Mapping Geospatially Enabled Systems to
Enterprise Architecture and Analytics
“Analytics” and “Geographic Information Systems” are ubiquitous terms now.
There are innumerable geo-enabled applications and location-based services
Where does Enterprise Geospatial Architecture fit into that picture?
Finding Enterprise Architecture on a map always seems difficult

3. Thinking about using GIS should begin with the notion of “geospatially
enabled” systems or analyticcs, not with implementing “GIS.”
This is not just a sofware or application development
process, but a process of providing information and analysis
that is applicable to and needed by different audiences.
Geospatially enabled data and systems must be
flexible to use with many other approaches to
Business Intelligence and Analytics as well as plain old
statistics, and unique geospatial statistical operations.
Enterprise
View of
Geographic
Information
Systems
Organizations contemplating using Geographic
Information Systems need an enterprise architecture that
puts geospatial data, applications, and analytics within
the total context of software development and data
management as well as coordinates among all groups
involved in standing up and maintaining geospatially
enabled systems.
All common processes and standards must be applied to
geospatially enabled systems. Geospatial data and
applications should not be regarded as ancillary to
others or as exclusive from all other standards for data
management and metadata.
A Roadmap covers all geospatially enabled systems, not just selective or
“special” applications and is a foundation for future infrastructure changes
and analytical needs.

4. Enterprise Architecture sets the Stage for Geo-enabled Analytics
Geospatial Application
Development
Geospatial Master Data
Cartographic Data, Crops, Facilities,
Watersheds, Census Data, and
geospatial web services or SOA for
geospatial master data
Geospatial Master Data
Production
Imagery, Raster, Vector
(Aerial Photos, Thermal spectrum, Streets, Water bodies,
Political Boundaries)
Charts, graphs, maps associated
with other business data
Information
Standards
Geoprocessing, geocoding, modeling,
data capture, etc.
Business Intelligence
Geospatial Functional
Services
Target
Architecture
Enterprise Architecture
Data Creation, Systems Integration, Information
Dissemination, Functional Implementation,
Geospatial Data Warehouse, Geospatial
Processing as a Service

5. Data and Technology Patterns Separated but
Coordinated for Different Analytic Purposes
Planning and
Analysis
Geospatial Data
Application
Organization
Implementation
and Production
Business
Intelligence
Solutions
Public Facing
Channels
Direct Customer Interaction
Lines of Business Program Implementation
Budget, Performance, and Policy Analysis
Business Analysis,
Development
Requirements Analysis Geospatial Master
Data, Services,
Data,
Information Analysis
and System
Data Production,
EA Analysis
Integration,
Management, Services
Project Analysis
Multi-Channel Provisioning,
Distribution, and
Testing
Exchange
Hosting, Cloud
Enterprise
Information
Management,
Analytics
Geospatial
Analytics
Communication with
Lines of Business,
Staff, Analytic
Community,
Customers,
Other Groups

6. External Providers
Organization Staff
Architecture
Data
Metadata
Systems
Should Be the
Foundation
Enterprise Architects
Data Providers
Federated
Geospatial
Data
General Public
Application Developers
Business Offices
Distributed data and resources
Enterprise Data
Warehouse
(Analytic)
Geospatial Master Data
and Services
(Analytic)
Solution Architects
Customers
That serves your
community
Reseachers
Data Architects

7. Business
Systems
Datastores
Data Warehouses and
Data Stores Provide and
Consume Data Needed
to Geospatially Enable
Information
Geospatial Master Data
Provides a Geographic
Context and Receives
Data from Other
Gesopatially Enabled
Sources and Services
Other Pubic-facing
Applications
Customer Matching
Master Data
Datastore
Distributed data and resources
Enterprise Data Warehouse
(Analytic)
Tables
Geospatial Master Data and Services
(Analytic)
“Layers”
Transaction
Systems Analytics
Datastore
Other Analytical
Datastores
Other External Serving
Datastores
Exterma; Datastore
and Processing
Services
Internal Data and
Services

8. Analytics are only as good as the geospatial data produced and
maintained from authoritative sources and metadata
Source: U.S. Federal Geographic Data Committee Geospatial Data Life Cycle
http://www.fgdc.gov/policyandplanning/a-16/index_html

9. Information Shared with Performance Assessment Community becomes Feedback for Improvements
Information needed to analyze
program performance against
desired or required metrics
Geospatial Data Becomes Part of the
Information Stream
IT Facilitation
Operational
Business Sponsors
Strategic Decision Makers
Data
Applications
Business
Analyst
Business Expert
GIS
Budget
Analyists
Business
Data
Testing
Architecture
Business
Rules
Policy
Analyst
Business
Analyst
Feed back on Outcomes of Program
Performance based on metrics to Business
Information Return to Business
Researcher
Analyses based on business data or data provided to other sources
Analysis and data shape program budget and IT investment decisions
Information about performance
output of programs

10. Geo-enabled
applications are likely
to use distributed and
coordinated geospatial
data and business data
that is flexible for
multiple audiences and
multiple channels.
Dash Boards
Enterprise
Reporting
Geospatial
Analysis
Statistical
Analysis
Data
Visualizatio
n
Business Data
Master Geospatial Data Hub
Geospatial Data
Data Mining

11. Mapping Geospatially Enabled Systems to
Enterprise Architecture and Analytics
Dennis Crow, Ph.D, PMP
dcrow1953@gmail.com
http://www.linkedin.com/in/dcrowwdc