City Knowledge

1. City Knowledge for theBeyond SDI Workshop @ GIScience A Web-services Approach for the Emergence of Sustainable Municipal Spatial Infrastructures Fabio Carrera MIT/WPI Muenster, September 20, 2006

2. Fabio Carrera Biographical Sketch 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

3. Beyond SDI Presentation Outline SDIs in 2016 (MSDIs) City Knowledge The 6 Tools Birth Certificates Web-services and the “Long Tail”

4. Beyond SDI Presentation Outline SDIs in 2016 (MSDIs) City Knowledge The 6 Tools Birth Certificates Web-services and the “Long Tail”

5. A positive local scenario SDIs in 2016 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

6. Beyond SDI Presentation Outline SDI’s in 2016 City Knowledge The 6 Tools Birth Certificates Web-services and the “Long Tail”

7. City Knowledge Promotesthe transformation of municipalitiesfrom hunter-gatherers of urban data to farmers of municipal information

8. 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

9. 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 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

10. The Premises of CK • 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 • “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 […]”. 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 Lynch, Good City Form, p. 48

11. The Premises of CK • 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 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

12. The Premises of CK • 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 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

13. 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

14. Ownership & Operation • Regulation • Incentives/Disincentives • Education & Information • Rights • Mitigation & Compensation 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 information gathering) • by 2016 • Municipalities consciously & creatively combine the 6 tools for • Information Farming • Policy/Plan Implementation

15. Beyond SDI Presentation Outline SDI’s in 2016 City Knowledge The 6 Tools Birth Certificates Web-services and the “Long Tail”

16. applied to Data Farming in 2016 6 Tools of Gov.’t Ownership and Operation Regulation Incentives/Disincentives Education and Information Right swapping Mitigation and Compensation

17. applied to Data Farming in 2016 • 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 6 Tools of Gov.’t Ownership and Operation Regulation Incentives/Disincentives Education and Information Right swapping Mitigation and Compensation

18. applied to Data Farming in 2016 6 Tools of Gov.’t • 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” Ownership and Operation Regulation Incentives/Disincentives Education and Information Right swapping Mitigation and Compensation

19. applied to Data Farming 6 Tools of Gov.’t • 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 Ownership and Operation Regulation Incentives/Disincentives Education and Information Right swapping Mitigation and Compensation

20. applied to Data Farming in 2016 6 Tools of Gov.’t • 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 Ownership and Operation Regulation Incentives/Disincentives Education and Information Right swapping Mitigation and Compensation

21. applied to Data Farming by 2016 6 Tools of Gov.’t 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

22. applied to Data Farming in 2016 6 Tools of Gov.’t 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

23. Beyond SDI Presentation Outline SDI’s in 2016 City Knowledge The 6 Tools Birth Certificates Web-services and the “Long Tail”

24. by 2016… • 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 Birth Certificates

25. Beyond SDI Presentation Outline SDI’s in 2016 City Knowledge The 6 Tools Birth Certificates Web-services and the “Long Tail”

26. 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 • 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 Web-services

27. in Municipal Spatial Data Infrastructures Size of Cities The Long Tail 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.

28. within a Municipal Spatial Data Infrastructure Change managed by various Departments The Long Tail 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.

29. within a Department in the MSDI Amount of Change by different “agents” The Long Tail 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

30. produced by agents of change in an MSDI Change produced via various processes The Long Tail 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.

31. of processes within an MSDI Change produced over time The Long Tail 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.

32. by 2016… Beyond MSDI -> SDI 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 it’s really going to happen!

33. carrera@wpi.edu • http://www.wpi.edu/~carrera Fabio Carrera