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					Knowledge Farming
City Knowledge and the Long Tail of
            Small Cities




          Fabio Carrera

           Santa Fe, February 20, 2007
                     Bio
                  Fabio Carrera
 Born in Venice, Italy
 BSEE and MSCS @ WPI
 PhD @ MIT
    Urban Information Systems and Planning
 Teaching @ WPI and MIT
 Director of Venice and Boston Project Centers
 Founder and Director of City Lab (WPI)
    LOUIS (Local Online Urban Information System)
 Planning Board in Spencer, MA
 Consultant to municipalities
    Forma Urbis sas and City Knowledge LLC
Presentation Outline
 City Knowledge
    The 6 Tools
    Birth Certificates
 Data Farming
 The Long Tail of Small Cities
Presentation Outline
 City Knowledge
    The 6 Tools
    Birth Certificates
 Data Farming
 The Long Tail of Small Cities
    City Knowledge
             Promotes

the transformation of municipalities
from hunter-gatherers of urban data
 to farmers of municipal information
The Premises of CK
   Municipalities are the locus of change
   Cities = Structures + Activities
   Reality = Backlog + Future Change
   Space Is the Glue
   Middle-out = Top-down + Bottom-up
   Government only has 6 tools for
    implementation and data collection
The Premises of CK
 Municipalities are the locus of change
      Like = Structures + Activities
  Cities politics, “all change is local”
      Most = Backlog + Future Change
  Realitychange is filtered by municipalities
      with
  SpaceCK: the Glue
            Is
      City departments implement information strategies
 Middle-out = Top-down +atBottom-up
      Urban information is farmed-in a fine grain
      Documentation becomes 5 (or so)
 Government only has Information tools for
      Intra- and Inter-departmental sharing is commonplace
    implementation
      Regional patterns (SDI) emerge upon municipal foundations
The Premises of CK
 Municipalities are the locus of change
 Cities = Structures + Activities
       Fundamental problem to decide what the form
“TheStructures Backlog ispermanentChange of a human
  Reality = are more + Future
 settlement consists of […]
    Space Is change can
  Structuralthe Glue be captured
 […] the chosen ground is the spatiotemporal distribution of
  Activities are more dynamic and fickle
    Middle-out = the physical + Bottom-up
human actions and Top-down things which are the context
 of Activities can be frozen in time and space (snapshots)
    those actions […]”.
 Government only has 5 (or so) tools for
  with CK:
    implementation                      Lynch, updated
    Information about structures is routinely Good City Form, p. 48
     Activities are “spatialized”
     Activities are periodically frozen
The Premises of CK
 Municipalities are the locus of change
 Cities = Structures + Activities
 Reality = Backlog + Future Change
      There is the of “reality” already out there…
  Space Is a lot Glue
      But the amount of information is finite
 Middle-out = Top-down + Bottom-up
      with CK the backlog can be completely captured
                                5 (or so) tools
  Government only has slow so, with CK for
      Urban change is rather
    implementation is captured at the source
      all Structural change
      snapshots of activities are creatively obtained
   with CK, municipal information is “farmed” daily
The Premises of CK
 Municipalities are the locus of change
 Cities = Structures + Activities
 Reality = Backlog + Future Change
 Space Is the Glue
  Middle-out = Top-down + Bottom-up
      within CK:
      Space plays key role in 5 (or so) tools farming
 Governmentaonly has municipal informationfor
      Addresses are no longer primary spatial identifiers
    implementation
      GIS means Geographic Indexing Systems
      Space indexes our datasets
The Premises of CK
 Municipalities are the locus of change
 Cities = Structures + Activities
 Reality = Backlog + Future Change
 Space Is the Glue
 Middle-out = Top-down + Bottom-up
      Top-down is only has 5 structured…
  Government rigorous and (or so) tools for
      … but is received as an “imposition” and resisted
    implementation
   Bottom-up is passionate and self-interested…
      … but unstructured, unscalable and unsustainable
   with CK:
      Pure top-down and bottom-up approaches disappear
      Middle-out combines the positive traits of both
The Premises of CK
  1. Ownership & Operation
 2.Municipalities are the locus of change
      Regulation
 3.Cities = Structures + Activities
      Incentives/Disincentives
 4.Reality = Backlog + Future Change
      Education & Information
      Rights
 5.Space Is the Glue
      Mitigation = Top-down
 6.Middle-out & Compensation+ Bottom-up
 Government only has 6 tools for
  implementation (and information gathering)
   with CK:
     Municipalities consciously & creatively combine the 6 tools for
       Information Farming
       Policy/Plan Implementation
Presentation Outline
 City Knowledge
    The 6 Tools
    Birth Certificates
 Data Farming
 The Long Tail of Small Cities
                   of Gov.’t
     6 Tools Data Farming
        applied to
1.   Ownership and Operation
2.   Regulation
3.   Incentives/Disincentives
4.   Education and Information
5.   Right swapping
6.   Mitigation and Compensation
          6 Tools of Gov.’t
                 applied to Data Farming
1. Ownership and Operation
2.  Regulation
      whereby municipalities…
      Adopt internal mechanisms to
3. Incentives/Disincentives farm THEIR OWN data
      Emphasize Information in Standard Operating Procedures
4. Education and Information all internal processes
      Extract Informational Returns from
5. Right swapping
      Change “job descriptions” for personnel to include information
      Catch up with their own “backlog”
                 and Compensation
6. Mitigation all future internal change as it happens
      Intercept
          6 Tools of Gov.’t
                  applied to Data Farming
1. Ownership and Operation
2. Regulation
3.  Incentives/Disincentives
       whereby municipalities…
4. Education and Information of their regulations
      Make informational Returns part
      Force outside entities to provide information (for free)
5. Right swapping requirements (permits, plans…)
      Change submission
6. Mitigation and Compensation contracts
      Modify maintenance and management
        Institute yearly renewals for data updates
        Apply regulations to capture backlog as well
        Invent creative ways to acquire datasets
        Become “validators” instead of “collectors”
         6 Tools of Gov.’t
                 applied to Data Farming
1. Ownership and Operation
2. Regulation
3. Incentives/Disincentives
      whereby and Information
4.  Educationmunicipalities…
      Routinely entice
5. Right swappingoutside entities into providing information
      Change submission fee structures (permits, plans…)
6. Mitigation and Compensation
      Make “old ways” costly (disincentives)
        Make it cheaper to do the right thing (incentives)
        Provide benefits for data updates
        Invent bonuses for data backlog
        Reward and enforce collaboration
        Validate incoming data
        6 Tools of Gov.’t
                applied to Data Farming
1. Ownership and Operation
2. Regulation
3. Incentives/Disincentives
4. Education and Information
5.  Right swapping
       whereby municipalities…
      Constantly educate citizens about the
6. Mitigation and Compensation use of data
       Are always transparent about motives for data collection
       Explore potential for volunteer citizen input
       Incite “peer-production”
       Make educational institutions partners in the process
       Acknowledge and Reward collaboration
       Include this aspect in ALL their initiatives
        6 Tools of Gov.’t
                applied to Data Farming
1. Ownership and Operation
2. Regulation
3. Incentives/Disincentives
4. Education and Information
5. Right swapping
      Requires and creativity but is
6.  Mitigation“real” Compensationvery powerful
   More useful for implementation, to
     Trade-up “as-of” rights in exchange for desired outcomes
   in the end municipalities can…
     include informational returns any time rights are renegotiated
     increase “as-of” rights in exchange for data
          6 Tools of Gov.’t
                  applied to Data Farming
1.    Ownership and Operation
2.    Regulation
3.    Incentives/Disincentives
4.    Education and Information
5.    Right swapping
6.    Mitigation and Compensation
      More useful for implementation, to…
        Mitigate negative consequences of initiatives
        Remove final obstacles to implementation
      with this tool municipalities could…
        accumulate complaints and suggestions from affected parties
        provide online tools for quantifying and logging problems
Presentation Outline
 City Knowledge
    The 6 Tools
    Birth Certificates
 Data Farming
 The Long Tail of Small Cities
   Birth Certificates
                      the concept

 Municipalities treat their assets as newborn babies
 Municipalities identify “parent” dept’s
 Dept’s produce a “birth certificate” for each asset
   Parent dept. assigns “name” (and code)
   Death and Adoption certificates are treated similarly
 Other dept’s refer to assets by their given name
 A municipal spatial data infrastructure emerges
Presentation Outline
 City Knowledge
    The 6 Tools
    Birth Certificates
 Data Farming
 The Long Tail of Small Cities
      Data Farming
the future of Municipal Information Systems
   Municipal Spatial Data Infrastructures emerge
   Towns have “plan-ready” information
   Municipalities stop hunting-and-gathering
   Information is instead farmed
   Change is captured at the source (for free)
   Open-source web-GIS dominate
   New business models emerge
   Web services are the currency
   Profits come from “changers” and “users”
   Private sector contributes fine-grained data
          Web-services
                   and City Knowledge
 Open-source web-GIS are the platform
   Light clients or AJAX apps replace standalone apps
   Systems are upgraded regularly on server
 Municipalities get data and applications for free
 Web services are the tools
   Dept’s mash-up web-services to suit needs
 Metadata is reliably available
 Web 2.0 techniques are commonplace
   Folksonomies
   Reputation Management, etc.
 Urban Information Systems exploit the Long Tail
Presentation Outline
 City Knowledge
    The 6 Tools
    Birth Certificates
 Data Farming
 The Long Tail of Small Cities
The Long Tail

163,547   towns (local gov.t) in the world
163,239   < 1 Million pop.
159,349   < 100,000 pop.
130,206   < 10,000 pop.
 64,307   < 1,000 pop.
         The Long Tail
                and City Knowledge
                   Size of Cities

                           ANY TOWN
      Large Cities
                              Small Cities



The total population that lives in small and medium
cities greater than the population in megacities. Small
towns (“tail”) represent a huge market opportunity.
         The Long Tail
               within a Municipality
Change managed by various Departments
                             Target main
         ANY DEPARTMENT departments
        Planning, Buildings,
               DPW
                                  Other
                               Departments




The Long Tail is Fractal. Starting with the “head”
makes sense, but all departments ought to eventually
adopt the CK approach.
The Long Tail
         The Long Tail
                within a Department
 Amount of Change by different “agents”
                                major agents
             ANY AGENT
         specific developers,
          contractors, staff

                                    Other agents




Again, the “head” will yield instant benefits, although
the change generated by agents in the tail may be
quantitatively just as large. Target all agents eventually
         The Long Tail
         within an administrative process
 Change produced via various processes
                              Low-hanging
       subdivision approvals,    fruits
       construction permits,
             contracts ANY PROCESS
                               Other Processes




Processes in the head are major vehicles of change.
Minor processes in the tail still add up to major change.
Eventually all processes will be addressed by CK.
         The Long Tail
                   past and future
         Change produced over time


          BACKLOG

                              Future Change




The backlog may be huge but it is finite and worth
catching up with. Focusing on the long tail of future
piecemeal change will close the loop forever.
           In Summary
   Municipal Spatial Data Infrastructures flourish
   Departments farm their “data plots”
   The 6 tools make data farming perpetual/free
   Fine-grain is achieved routinely
   Backlog is completely captured
   Change is intercepted as it happens
   Technologies automate/facilitate data collection
   Web-services enable intra-/inter-dept. sharing
   Information is treated like an infrastructure
        More about CK



                   carrera@wpi.edu
http://www.wpi.edu/~carrera/Publications/Publications.html
    http://www.wpi.edu/~carrera/MIT/dissertation.html

				
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