Types and Use of Data for Urban Planning/Design Research
Qualitative Data
Ordinal Data: an ordinal scale in categories.
Nominal Data (nominal scale): a variable with categories without a natural order or ranking. But the order is arbitrary so mean, median or standard deviation would be meaningless. The percentage would be meaningful. (e.g. blood type, zip code, gender, race, eye color, etc.)
Quantitative Data
Continuous Data: an infinite number of possible values within
a selected range (e.g. temperature, height, weight range, etc.) - height can be 180cm or 180.00001cm or 180.0000000001cm (but, hardly notice the difference)
Discrete Data: a finite number of possible values (e.g. days of the week, number of passengers, etc.)
Civic Data Use Catalog with Urban Questions
- Health & Human Service
- When clients apply for / obtain multiple services, which service do they typically apply for first?
- How do we help clients leaving the criminal justice system, foster care, homeless shelters, etc. get and keep jobs?
- Which individuals and families placed into permanent housing are most at risk of returning to the homeless services system?
- Which city services have the greatest impact on reducing entry into homeless shelters?
- Which client characteristics indicate that a client will leave a homeless shelter without a subsidy?
- Which clients would benefit the most from housing services?
- Which seniors in need of services and resources currently aren’t receiving them?
2. Infrastructure
- How can we reduce outage rates for the agency fleet without purchasing new vehicles? Under what circumstances do outages take place most frequently?
- Is there a relationship between “greened” infrastructure and health?
- How can we better predict where the next major street light cable failure will be?
- Can we predict what areas have more open hydrants?
- Where should snow removal happen first?
- Under what circumstances do residents throw recyclables in the trash instead of in recycling bins (and how can we mitigate this in order to increase recycling diversion rates)?
- What are the current refuse locations in the city? Which receives the highest amount of complaints?
3. Public Safety
- How can we anticipate where vulnerable people will need help evacuating?
- How can we preempt youth violent crime?
- How can ambulances respond to medical emergencies faster?
- How can data sharing improve disaster response?
- Which streets will need to be evacuated before a flood?
- How can social media data help identify public safety issues?
- Where is a crime most likely to take place on a specific day?
4. Regulation
- Which construction/renovation projects are the highest risk / should be inspected first?
- Which equipment (such as boilers, elevators, cranes, vehicles, etc.) is the highest risk / should be inspected first?
- How many inter-agency inspections are conducted each year? Do they effectively detect current violations?
- Which city debts are least likely to be paid?
- Which taxpayers are least like to pay?
- How can we tap social media for information on illegal businesses?
5. Mobility
- How can we reduce accidents involving city vehicles? Where and when do most accidents involving city vehicles occur?
- How can we reduce the number of traffic accidents?
- How can cities best regulate micro-mobility?
- Which intersections are likely to be blocked, and when?
- Can cities do residents to more sustainable modes of travel?
(Source: https://datasmart.ash.harvard.edu/)
6. Design
- Does the integration of renewable energies in urban designs contribute to raising the economic value of the real estate?
- How to integrate the new land-use, urban transport planning concepts, and proposed projects with the actual existing land-use conditions?
- What is the status of the prototype and applications to the field of landscape architecture?
- Can you suggest examples of well-designed bicycle parking/shelter integrated into the urban realm?
- What is the appropriate methodology for cityscape assessment?
