Course Schedule

Module 1: Introduction to Urban Data

Date Lecture Slides Reading Assignment
Tuesday, January 19: Introduction to Urban Analytics*
  1. Singleton, Spielman, and Folch (2018) Chapter 1, “Questioning the city through urban analytics.”
  2. Kim, Annette. 2018. Satellite Images can Harm the Poorest Citizens.
  3. Optional: Hollands, Robert G. 2008. “Will the Real Smart City Please Stand up?: Intelligent, Progressive or Entrepreneurial?” City 12 (3): 303–20.
Thursday, January 21: Data Fundamentals for Planners*
  1. Singleton, Spielman, and Folch (2018) Chapter 2, “Sensing the city.”
  2. Boyd, Danah, and Kate Crawford. 2012. “CRITICAL QUESTIONS FOR BIG DATA: Provocations for a Cultural, Technological, and Scholarly Phenomenon.” Information, Communication & Society 15 (5): 662–79. doi:10.1080/1369118X.2012.678878.
  3. Neruda, Pablo, and Margaret Sayers Peden. 1986. “Ode to Numbers.” The Massachusetts Review 27 (3/4): 464–66.

  4. Wheelan (2013) Chapter 7, "The Importance of Data."
Tuesday, January 26: Metadata: Understanding the US Census*
  1. Jurjevich et al. 2018. Navigating Statistical Uncertainty: How Urban and Regional Planners Understand and Work with American Community Survey (ACS) Data for Guiding Policy. Journal of the American Planning Association, 84(2), 112-126.
  2. B. Strasser and P. Edwards, “Big Data is the Answer… But What is the Question?” Osiris 32, 2017: pp. 328-345.
  3. Alba, Richard. 2015. “The Myth of a White Minority.” The New York Times, June 11.
Thursday, January 28: Using Census Data
  1. Bureau, U. S. Census. 2021.
  2. Social Explorer. 2021.
  3. U.S. Bureau of the Census, TO. 2009. “A Compass for Using and Understanding American Community Survey Data.” [for reference only]
Tuesday, February 2: Stats and the American Community Survey
  1. Cochran, Abby. 2020. Stats for CP 101. (Part 1 and Part 2)

  2. Recommended: Wheelan (2013) Chapters 2, 3, & 4 "Descriptive Statistics,” "Descriptive Deception, "The Central Limit Theorem”
Thursday, February 4: Static Data Visualization*
  1. Few, Stephen. 2012. Show Me the Numbers: Designing Tables and Graphs to Enlighten. 2nd ed. USA: Analytics Press. [Lots of pictures, quick reading!] Chapter 3 pg. 39-60 “Differing Roles of Tables and Graphs”, Chapter 4 pp. 53-60 “Fundamental Variations of Tables”, Chapter 5 pg. 67-79 “Attributes of Pre-attentive Processing" & “Applying Visual Attributes to Design”, Chapter 6 pg. 101-135 “Graph Design Solutions”, Chapter 11 pg. 257-270 “Displaying Many Variables at Once”, Chapter 13 pg. 295-306 “Telling Compelling Stories with Numbers”, Appendix A “Table and Graph Design at a Glance” pg. 309-310.
  2. Tufte, Edward R. 1983. The Visual Display of Quantitative Information. Graphics Press. Chapter 2, "Graphical Integrity".

Optional: Check out Picktochart for infographics, And the whole Tufte book is great – especially check out Chapter 1, “Graphical Excellence.”
Tuesday, February 9: Neighborhood Data and Indicators: The Urban Displacement Project*
  1. Singleton, Spielman, and Folch (2018) Chapter 5, “Differences Within Cities”
  2. Chapple & Zuk, “Forewarned: The Use of Neighborhood Warning Systems for Gentrification and Displacement.”
  3. Urban Displacement Project [SKIM]
Thursday, February 11: Introduction to Economic Data and the Longitudinal Household-Employment Data
  1. Abowd, J. J., Haltiwanger, J., & Lane, J. (2004). Integrated longitudinal employer-employee data for the United States. American Economic Review, 94(2), 224-229.

Module 2: Mapping the City

Date Lecture Slides Reading Assignment
Tuesday, February 16: Spatial Data & GIS Fundamentals*

(Guest: Irene Farah Rivadeneyra)
  1. Singleton, Spielman, and Folch (2018) Chapter 4, “Visualizing the city."
  2. Monmonier, Mark. 1996 Chapters 1, 2, 3, 4, and 10 How to Lie with Maps. University of Chicago Press.
  3. Additional GIS mapping information
 Assignment #1 due
Thursday, February 18: Accessibility*

(Guest: Chester Harvey)
  1. Hamraie, Aimi. 2018. “A Smart City Is an Accessible City.” The Atlantic. November 6, 2018.
  2. Walker Jarrett. 2011. “transit’s product: mobility or access?” Human Transit. January 16, 2011.
  3. Optional: “Curb Cuts.” 2018. 99% Invisible (blog). Accessed May 23, 2018.
  4. Optional: Samuel D. Blanchard and Paul Waddell. 2017. "UrbanAccess: Generalized Methodology for Measuring Regional Accessibility with an Integrated Pedestrian and Transit Network." Transportation Research Record: Journal of the Transportation Research Board. No. 2653. pp. 35–44.
Tuesday, February 23: Introduction to Story Mapping

Examples to review:

  1. The Lines that Shape our Cities
  2. The Evolution of the American Census
  3. Displacement in the Bay Area
  4. Mapping Segregation in DC.
  5. Creating a neighborhood change zoning plan for Spruce Hill
  6. Gangs of Los Angeles (2015)
  7. Atlas for a Changing Planet
  8. Katrina +10: A Decade of Change in New Orleans
  9. Nature–Based Climate Solutions by The Nature Conservancy
  10. River of Forgiveness

You can find more examples at ESRI’s gallery.
Thursday, February 25: Participatory Mapping*
  1. Erin McElroy, The Ethics and Data of Mapping Displacement
  2. Parker, Brenda. “Constructing Community through Maps? Power and Praxis in Community Mapping.” Professional Geographer, 58:4, (2006): 470-484.
  3. Norwood, Carla, and Gabriel Cumming. "Making maps that matter: Situating GIS within community conversations about changing landscapes." Cartographica: The International Journal for Geographic Information and Geovisualization 47.1 (2012): 2-17.
  4. Check out the Street Story Project
Tuesday, March 2: Power, Place and Mapping*
  1. Webinar on Ethical Spatial Analytics. (Note: you must register to get access. Watch at least one of the talks. Highly recommended: Vadjunec or Sieber.)
  2. Harley, J. Brian. “Maps, knowledge, and power” (Chapter 8). In Henderson, George and Waterstone, Marvin. Geographic thought: a praxis perspective, 1988. 129-148.
Thursday, March 4: Midterm Quiz #1

Module 3: Data Science for Planners: Big Data and Analytics

(Guest Jason Lally, formerly of SF Open Data)

Date Lecture Slides Reading Assignment
Tuesday, March 9: Introduction to Big Data*
  1. Foster, Ian, Rayid Ghani, Ron S. Jarmin, Frauke Kreuter, and Julia Lane. 2017. “Introduction.” Pp. 1-19 in Big Data and Social Science: A Practical Guide to Methods and Tools. Boca Raton, FL: Taylor & Francis Group.”
  2. Gitelman, Lisa and Virginia Jackson. 2013. Introduction. Raw data is an oxymoron. MIT Press.
  3. Crawford, Kate. 2013. “The hidden biases in big data.” Harvard Business Review 1.
Thursday, March 11: Big Data – and Ethics – for Planners*
  1. Schweitzer, Lisa. 2014. “Planning and Social Media: A Case Study of Public Transit and Stigma on Twitter.” Journal of the American Planning Association 80 (3): 218–38.
  2. Crawford, Kate. “The Trouble with Bias”, NIPS conference keynote, December 2017 (especially minutes 14:00 - 38:00)
  3. Barocas, S. and d. boyd (2017). "Engaging the Ethics of Data Science in Practice," Communications of the ACM, Vol. 60 No. 11, Pages 23-25.
  4. M. Zook, S. Barocas, d. boyd, K. Crawford, E. Keller, S.P. Gangadharan, et al. (2017) "Ten simple rules for responsible big data research." PLoS Comput Biol 13(3).

Lab Midterm - no lab this week!

Tuesday, March 16: Complex Urban Modeling: Machine Learning*

(Guest: Pavan Yedavalli)
  1. Foster, Ian et al. 2017. “Machine Learning.” Pp. 147-186 in Big Data and Social Science: A Practical Guide to Methods and Tools. Boca Raton, FL: Taylor & Francis Group.
  2. Pedro Domingos, A Few Useful Things to Know About Machine Learning (2012)
Assignment #2 due
Thursday, March 18: Using Data Science to Understand Segregation and Evictions*

(Guest: Tim Thomas, live lecture with recording posted afterwards)
No lab this week!
Tuesday, March 30: Research Design and Urban Data Science*
  1. Singleton, Spielman, and Folch (2018) Chapter 6, “Explaining the city.”
  2. Kontokosta, Constantine E. "Urban informatics in the science and practice of planning." Journal of Planning Education and Research (2018): 0739456X18793716.
Thursday, April 1: Volunteered Geographic Information*

(Guest: Sam Maurer)
  1. Jiang, Bin, and Jean-Claude Thill. 2015. “Volunteered Geographic Information: Towards the Establishment of a New Paradigm.” Computers, Environment and Urban Systems, Special Issue on Volunteered Geographic Information, 53 (September): 1–3.
  2. Boeing, Geoff, and Paul Waddell. 2016. “New Insights into Rental Housing Markets Across the United States: Web Scraping and Analyzing Craigslist Rental Listings.” Journal of Planning Education and Research.
  3. Shelton, Taylor, Ate Poorthuis, and Matthew Zook. "Social media and the city: Rethinking urban socio-spatial inequality using user-generated geographic information." Landscape and Urban Planning 142 (2015): 198-211.
Midterm Quiz #2 due April 2
Tuesday, April 6: Urban Data Analytics*
  1. G.C. Bowker and S.L. Star, Sorting Things Out: Classification and Its Consequences (Cambridge, MA: MIT Press, 2000), Introduction ("To Classify is Human"), read pp. 1-16.
  2. Suel, Esra, John W. Polak, James E. Bennett, and Majid Ezzati. "Measuring social, environmental and health inequalities using deep learning and street imagery." Nature scientific reports 9,1 (2019): 1-10.
  3. Stewart, Matthew. 2019. “The Real Estate Sector is Using Algorithms to Work Out the Best Places to Gentrify.” Failed Architecture.
  4. Wheelan (2013) Chapters 8 & 11, “Correlation”, “Regression Analysis” (recommended)
  5. Optional: Reades, J., De Souza, J., & Hubbard, P. (2018). Understanding urban gentrification through machine learning. Urban Studies, 0042098018789054.
Thursday, April 8: Open Data & Using Portals*
  1. Lohr, Steve. 2016. “Website Seeks to Make Government Data Easier to Sift Through.” The New York Times, April 4.
  2. Spiker, Steve. 2013. “Oakland and the Search for the Open City.” Pp. 105-124 in Beyond Transparency: Open Data and the Future of Civic Innovation. San Francisco, CA: Code for America.
  3. Johnson, Jeffrey Alan. 2014. “From Open Data to Information Justice.” Ethics and Information Technology 16 (4): 263–74.

Lab 9: Python - Web Scraping

Assignment #3 proposals due

Tuesday, April 13: Interactive Visualizations*
  1. Hemmersam, Peter, Nicole Martin, Even Westvang, Jonny Aspen, and Andrew Morrison. 2015. “Exploring Urban Data Visualization and Public Participation in Planning.” Journal of Urban Technology 22 (4): 45–64.
  2. Anderson, Meghan Keaney. 2016. “12 Complex Concepts Made Easier Through Great Data Visualization — ReadThink (by HubSpot).” Medium. June 27.

Explore additional interactive visualizations here:

  • http://polygraph.cool/history/
  • http://goodcitylife.org/chattymaps/index.html
  • http://218consultants.com/interactive-suitability-map/ (Look at all 3 interactive maps)
  • https://ourworldindata.org/a-history-of-global-living-conditions-in-5-charts/
  • http://www.urban.org/features/vision-equitable-dc
  • http://www.urbandisplacement.org

    • Optional: Foster, Ian et al. 2017. “Working with Web Data and APIs.” Pp. 23-70 and “Information Visualization.” Pp. 243-263 in Big Data and Social Science: A Practical Guide to Methods and Tools. Boca Raton, FL: Taylor & Francis Group.

    Thursday, April 15: Defining Smart Cities in Theory and Practice*

    (Guest: Dagin Faulkner)
    1. Batty, M. 2016. “How Disruptive Is the Smart Cities Movement?” Environment and Planning B: Planning and Design 43 (3): 441–43
    2. Shelton, Taylor, Matthew Zook, and Alan Wiig. 2015. “The ‘Actually Existing Smart City.’” Cambridge Journal of Regions, Economy and Society 8 (1): 13–25. doi:10.1093/cjres/rsu026.
    3. P. Dourish, Code and the City, Rob Kitchin and Sung-Yueh Perng, eds. (Routledge, 2016), "The Internet of Urban Things," pp. 27-49
    4. T. Misra, "The New Digital Sanctuaries," Citylab, November 14, 2017.
    Tuesday, April 20: Smart Institutions & e-Governance*
    1. Noveck, Beth Simone. 2015. Smart Citizens, Smarter State: The Technologies of Expertise and the Future of Governing. Harvard University Press.; Chapter 1 & Conclusion, “From Open Government to Smarter Governance”, pg. 1 - 43; “Conclusion: The Daedalus Project”, pg. 267 – 275
    2. V. Eubanks, "Want to Predict the Future of Surveillance? Ask Poor Communities," The American Prospect, January 15, 2014.
    3. Look over https://smartcitizen.me/
    4. For a great example of an open data site, see data.mesaaz.gov
    Thursday, April 22: Civic Hacking and Equity*

    (Guest Cal Civic Hacks-Ideathon Organizers and Winners)
    1. Watch Dr. Jeanne Holm, Deputy Mayor for Innovation, City of Los Angeles on Using Data to Improve Equity.
      2. OR
    2. Michael Migurski (Remix) and Nick Chin (Sidewalk Labs). Cities: No More Guessing, Lots More Knowing (Locate 18).

      3. AND
    3. Barns, Sarah. "Mine your data: open data, digital strategies and entrepreneurial governance by code." Urban Geography 37.4 (2016): 554-571.
    Tuesday, April 27: Presenting Data
    1. Schwabish, Jonathan. 2017. Chapter 1 “Theory, Planning and Design”; Chapter 4 “The Text Slide”; and Chapter 5 “The Data Visualization Slide”; in Better Presentations: A Guide for Scholars, Researchers, and Wonks. New York: Columbia University Press.
    2. Tufte, Edward, R. 2003. The Cognitive Style of PowerPoint. Graphics Press. (Part 1 and Part 2)
    3. Doumont, Jean-luc. 2005. “The Cognitive Style of PowerPoint: Slides Are Not All Evil.” ResearchGate 52 (1): 64–70.
    4. Parker, Ian. May 28, 2001. Absolute Powerpoint: Can a software package edit our thoughts? The New Yorker.
    5. Optional: Schwabish, Jonathan. 2017. Chapter 2 “Color” in Better Presentations: A Guide for Scholars, Researchers, and Wonks. New York: Columbia University Press.
    Thursday, April 29: The Inclusive Smart City*
    1. Singleton, Spielman, and Folch (2018) Chapter 8, pg. 151 “Networks Supporting Human Progress” & Chapter 9, “The Future of Urban Analytics”
    2. Zook, Matthew. 2016. “Crowd-sourcing the Smart City: Using Big Geosocial Media Metrics in Urban Governance.” Unpublished paper.
    Lab 12: Open Help Session (optional)
    Assignment #3 due Friday, May 7