City Knowledge

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City Knowledge

• A Web-services Approach for the Emergence of
  Sustainable Municipal Spatial Infrastructures

for theBeyond SDI Workshop _at_ GIScience
Fabio Carrera
MIT/WPI
Muenster, September 20, 2006
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Biographical Sketch
Fabio Carrera

• Born in Venice, Italy
• BSEE and MSCS _at_ WPI
• PhD _at_ MIT
• Urban Information Systems and Planning
• Teaching _at_ 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

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Presentation Outline
Beyond SDI

• SDIs in 2016 (MSDIs)
• City Knowledge
• The 6 Tools
• Birth Certificates
• Web-services and the Long Tail

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Presentation Outline
Beyond SDI

• SDIs in 2016 (MSDIs)
• City Knowledge
• The 6 Tools
• Birth Certificates
• Web-services and the Long Tail

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SDIs in 2016
A positive local scenario

• 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

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Presentation Outline
Beyond SDI

• SDIs in 2016
• City Knowledge
• The 6 Tools
• Birth Certificates
• Web-services and the Long Tail

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Promotes the transformation of
municipalitiesfrom hunter-gatherers of urban
data to farmers of municipal information
City Knowledge
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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

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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 5 (or so) tools for
  implementation

• Like politics, all change is local
• Most change is filtered by municipalities
• by 2016
• City departments implement information strategies
• City knowledge is accumulated at a fine grain
• Documentation becomes Information
• Intra- and Inter-departmental sharing is
  commonplace
• Regional patterns (SDI) emerge upon municipal
  foundations

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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 5 (or so) tools for
  implementation

The Fundamental problem is to decide what the
form of a human settlement consists of
the chosen ground is the spatiotemporal
distribution of human actions and the physical
things which are the context of those actions
.

• Structures are more permanent
• Structural change can be captured
• Activities are more dynamic and fickle
• Activities can be frozen in time and space
  (snapshots)
• by 2016
• Information about structures is routinely updated
• Activities are spatialized
• Activities are periodically frozen

Lynch, Good City Form, p. 48
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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 5 (or so) tools for
  implementation

• There is a lot of reality already out there
• But the amount of information is finite
• by 2016 the backlog is completely captured
• Urban change is rather slow so, by 2016
• all Structural change is captured at the source
• snapshots of activities are creatively obtained
• by 2016, municipal information is farmed daily

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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 5 (or so) tools for
  implementation

• by 2016
• Space plays a key role in municipal information
  farming
• Addresses are no longer primary spatial
  identifiers
• GIS means Geographic Indexing Systems
• Space indexes our datasets

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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 5 (or so) tools for
  implementation

• Top-down is rigorous and structured but is
  received as an imposition and resisted
• Bottom-up is passionate and self-interested
  but unstructured, unscalable and unsustainable
• by 2016
• Pure top-down and bottom-up approaches disappear
• Middle-out combines the positive traits of both

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The Premises of CK

• Ownership Operation
• Regulation
• Incentives/Disincentives
• Education Information
• Rights
• Mitigation Compensation

• 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 information gathering)

• by 2016
• Municipalities consciously creatively combine
  the 6 tools for
• Information Farming
• Policy/Plan Implementation

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Presentation Outline
Beyond SDI

• SDIs in 2016
• City Knowledge
• The 6 Tools
• Birth Certificates
• Web-services and the Long Tail

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6 Tools of Gov.t
applied to Data Farming in 2016

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

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6 Tools of Gov.t
applied to Data Farming in 2016

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

• by 2016, municipalities
• Adopt internal mechanisms to farm THEIR OWN data
• Emphasize Information in Standard Operating
  Procedures
• Extract Informational Returns from all internal
  processes
• Change job descriptions for personnel to
  include information
• Catch up with their own backlog
• Intercept all future internal change as it happens

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6 Tools of Gov.t
applied to Data Farming in 2016

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

• by 2016, municipalities
• Make informational Returns part of their
  regulations
• Force outside entities to provide information
  (for free)
• Change submission requirements (permits, plans)
• Modify maintenance and management contracts
• Institute yearly renewals for data updates
• Apply regulations to capture backlog as well
• Invent creative ways to acquire datasets
• Become validators instead of collectors

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6 Tools of Gov.t
applied to Data Farming

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

• by 2016, municipalities
• Routinely entice outside entities into providing
  information
• Change submission fee structures (permits,
  plans)
• 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

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6 Tools of Gov.t
applied to Data Farming in 2016

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

• by 2016, municipalities
• Constantly educate citizens about the 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

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6 Tools of Gov.t
applied to Data Farming by 2016

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

• Requires real creativity but is very powerful
• More useful for implementation, to
• Trade-up as-of rights in exchange for desired
  outcomes
• by 2016, municipalities
• include informational returns any time rights are
  renegotiated
• increase as-of rights in exchange for data

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6 Tools of Gov.t
applied to Data Farming in 2016

• Ownership and Operation
• Regulation
• Incentives/Disincentives
• Education and Information
• Right swapping
• Mitigation and Compensation

• More useful for implementation, to
• Mitigate negative consequences of initiatives
• Remove final obstacles to implementation
• by 2016, municipalities
• accumulate complaints and suggestions from
  affected parties
• provide online tools for quantifying and logging
  problems

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Presentation Outline
Beyond SDI

• SDIs in 2016
• City Knowledge
• The 6 Tools
• Birth Certificates
• Web-services and the Long Tail

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Birth Certificates
by 2016

• Municipalities treat their assets as newborn
  babies
• Municipalities identify parent depts
• Depts produce a birth certificate for each
  asset
• Parent dept. assigns name (and code)
• Death and Adoption certificates are treated
  similarly
• Other depts refer to assets by their given name
• A municipal spatial data infrastructure emerges

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Presentation Outline
Beyond SDI

• SDIs in 2016
• City Knowledge
• The 6 Tools
• Birth Certificates
• Web-services and the Long Tail

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Web-services
by 2016

• Open-source web-GIS will dominate
• Light clients or AJAX apps replace standalone
  apps
• Systems are upgraded regularly on server
• Municipalities get data and applications for free
• Web services are source of real profits
• Depts 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

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The Long Tail
in Municipal Spatial Data Infrastructures
Size of Cities
ANY TOWN
Large Cities
Small Cities
The total population that lives in small and
medium cities is at least as big as that in
megacities. Small towns (tail) represent a
huge market opportunity.
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The Long Tail
within a Municipal Spatial Data Infrastructure
Change managed by various Departments
Target main departments
ANY DEPARTMENT
Planning, Buildings, DPW
Other Departments
The Long Tail is Fractal.
The Long Tail is Fractal. Starting with the
head makes sense here, though all departments
will eventually adopt the CK approach leading to
MSDI.
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The Long Tail
within a Department in the MSDI
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
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The Long Tail
produced by agents of change in an MSDI
Change produced via various processes
Low-hanging fruits
subdivision approvals, 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.
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The Long Tail
of processes within an MSDI
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.
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The Long Tail
in 2016
Although much urban change may be created by few
(frequent) actors red part of tail many
additional actors may infrequently contribute
piecemeal change down the long tail represented
here by the yellow portion of the graph. Often,
the large number of small actors can cumulatively
outweigh the big actors, such that in aggregate
they comprise the majority of urban change.
Another way to look at the Long Tail is to
consider the red part of the tail to represent
the Backlog and the yellow portion to represent
future change. In fact the long tail is
fractal in nature, so the yellow part will itself
be composed of a red part and a yellow part ad
infinitum.
Yet another way to look at the Long Tail is to
consider the two colors to represent not the
creation of urban change, but the
collection/farming of the data associated with
it. Under a CK regime, the red part might
represent the bulk of the municipal farming of
data obtained through a variety of mechanisms
that leverage the 6 tools. The yellow part may
represent mechanisms that yield less data or data
that are produced by other agencies or by
citizens.
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Beyond MSDI -gt SDI
by 2016

• 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

and its really going to happen!
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Fabio Carrera
carrera_at_wpi.edu http//www.wpi.edu/carrera