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Geospatial Best Practices Pulling It All Together

Stephen Marley

NASA/GIO

April 11, 2007

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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

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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

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Business Driven Investment

Return on Investment (ROI)

Bus

ines

s V

alue

(B

V)

“Low Hanging Fruit”High Business ValueCheap to Implement

“Management’s Wish List”High Business Priority

Costly To Implement

“Success on a Budget”Low Business ValueCheap to Implement“Sorry, not this Year”

Low Business ValueCostly to Implement

Goal 1: Improve ROI

Goal 2: Improve BV

Goal 3: Improve Both

Goal 4: Retire a Hero

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Calculating Value

• ROI estimates can be difficult to justify:– Initial Costs can be high, true benefits can

take years to fully materialize• http://gita.org/gita-in-action/roi.asp

• 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

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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

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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

B = fBV RD ×N( )*http://www.infoanarchy.org/en/Sarnoff's_Law

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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 ModelB = fBV RS ×N2( )*http://en.wikipedia.org/wiki/Metcalfe's_law

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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

B = fBV RC ×2N( )*http://en.wikipedia.org/wiki/Reed's_law

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Architecture Comparison

Expense Ratio Compared to SarnoffNumber Data Users = 1000Ratio of Business Value = 1

1.00E-08

1.00E-07

1.00E-06

1.00E-05

1.00E-04

1.00E-03

1.00E-02

1.00E-01

1.00E+00

1.00E+01

1.00E+02

1.00E+03

1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64

Number Systems/Collaboratives

Expense Ratio (ROI) Compared to Linear

MetcalfeReed

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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

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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• http://gio.gsfc.nasa.gov/docs/ROI%20Study.pdf

• Use accepted community guidance• http://www.cio.gov/documents/FEA_Geospatial_Profile_v1-1.pdf

• http://www.fgdc.gov/standards/standards_publications/• http://gai.fgdc.gov/girm/

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Questions

Stephen.R.Marley.1@gsfc.nasa.gov