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Geospatial Best Practices Pulling It All Together. Stephen Marley NASA/GIO April 11, 2007. Geospatial Best Practices. Starts with the business proposition Ends with business value Value is achieved by implementing geospatial interoperability

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geospatial best practices pulling it all together

Geospatial Best Practices Pulling It All Together

Stephen Marley


April 11, 2007

geospatial best practices
Geospatial Best Practices
  • Starts with the business proposition
  • Ends with business value
  • Value is achieved by implementing geospatial interoperability
  • Return on Investment is achieved by choosing the right technology
business proposition
Business Proposition
  • Understand your needs
    • Understand the business functions that geospatial data and services perform in your agency
    • Understand the data and service exchange environment with other agencies both as a Data/Service Provider and a Consumer
  • Look for opportunities for alignment / consolidation
    • Do other agencies acquire relevant data?
    • Are your services redundant with another agency’s?
    • Can you combine services with another agency?
  • Increase your ROI and/or Business Value
    • The true value of a well implemented architecture program
business driven investment

Business Value (BV)

Return on Investment (ROI)

Business Driven Investment

“Management’s Wish List”

High Business Priority

Costly To Implement

“Low Hanging Fruit”

High Business Value

Cheap to Implement

Goal 1: Improve ROI

Goal 2: Improve BV

Goal 3: Improve Both

Goal 4: Retire a Hero

“Success on a Budget”

Low Business Value

Cheap to Implement

“Sorry, not this Year”

Low Business Value

Costly to Implement

calculating value
Calculating Value
  • ROI estimates can be difficult to justify:
    • Initial Costs can be high, true benefits can take years to fully materialize
  • Calculating BV is on the surface simpler
    • However, BV can be reduced if you have not correctly specified business needs
    • However, serendipitous value is difficult to estimate
interoperability rules
Interoperability Rules!
  • Basic types of interoperability:
    • Content Interoperability
      • Enforced through Data Content and Data Format Standards
    • Service Interoperability
      • Enforced through Service Description Standards and Service Invocation Standards
    • Semantic Interoperability
      • Enforced through controlled taxonomies and ontologies
  • The type of interoperability drives your architecture choices and affects your ROI and BV potential
content driven architecture
Content Driven Architecture
  • Linear Networks (Sarnoff*)
  • Content (Data) Driven Interoperability
  • “Old-School” Data Systems
  • Characterized by Control:
  • Controlled Authoritative Data
  • Controlled Data Services
  • Provider Driven Business Domain
  • e.g. Broadcast TV, Weather Alerts


service driven architecture
Service Driven Architecture
  • Networked Systems (Metcalfe*)
  • Service Driven Interoperability
  • The leading edge of operational deployment
  • Characterized by Governance:
  • Value-Added Data & Services
  • High degree of re-use
  • Enterprise Driven Business Domain
  • e.g. SOA & Grid Applications; Wikipedia Social Model


community driven architecture
Community Driven Architecture
  • Collaborative Networks (Reed*)
  • Semantic Driven Interoperability
  • Subject of R & D
  • Characterized by Communities of Interest:
  • Community focused Data & Services
  • Community Driven Business Domain
  • e.g. The real-world


information considerations
Information Considerations
  • You do not know all the uses for your data
    • Decouple persistent “inherent” attributes (e.g. physical parameters) from transient “business” attributes (e.g. semantic meaning, business application)
    • Be realistic about what metadata is truly mandatory
  • Metadata is more valuable than Data
    • If your can’t find it, it is as if it never existed
    • Generate metadata in situ during data generation as part of your process
  • “Data are Services”
    • Data can only be accessed via a service
    • Design Services in a hierarchical fashion to maximize re-use potential
    • Avoid “service-bundling” if possible
  • Expertise Disappears:
    • Document your uncertainty about the data
    • Document the provenance of the data
technology best practices
Technology Best Practices
  • Service Driven vs. Data Driven
    • Loosely-coupled service architectures will endure disruptive technology and business changes better than tightly-coupled data driven services
    • Service driven approaches anticipates semantic interoperability where business value can be truly leveraged
  • Open vs. Proprietary
    • Implementation using non-propriety standards improves ROI by up to 25% over the lifetime of the applications
  • Use accepted community guidance