Pulling Together - Matanuska-Susitna Borough School District
Geospatial Best Practices Pulling It All Together
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Transcript of Geospatial Best Practices Pulling It All Together
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
• Return on Investment is achieved by choosing the right technology
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
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
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
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
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
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
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
Architecture ComparisonExpense Ratio Compared to Sarnoff
Number 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
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• 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/
Questions