Course Schedule

Some links to readings are still being adjusted, and will be finalized soon.

Module 1: Introduction to Urban Data

Date Lecture Slides Reading Assignment
Tuesday, January 21: 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 23: 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.
  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 28: 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 30: Using Census Data
  1. Bureau, U. S. Census. 2020.
  2. Social Explorer. 2020.
  3. U.S. Bureau of the Census, TO. 2009. “A Compass for Using and Understanding American Community Survey Data.” [for reference only]
Tuesday, February 4: Stats and the American Community Survey
  1. Cochran, Abby. 2020. Stats for CP 101 (Video available soon on bcourses)

  2. Singleton, Spielman, and Folch (2018) Chapter 6, “Explaining the city”

  3. Wheelan (2013) Chapters 2, 3, & 4 "Descriptive Statistics,” "Descriptive Deception, "“The Central Limit Theorem”
Thursday, February 6: Static Data Visualization
  1. Few (2012) 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 [Lots of pictures, quick reading!]

  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 11: 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 13: 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 18: Spatial Data & GIS Fundamentals

  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
Thursday, February 20: Accessibility*
  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. Walker Jarrett. 2011. “transit’s product: mobility or access?” Human Transit. January 16, 2011.

    4. Optional:

  4. “Curb Cuts.” 2018. 99% Invisible (blog). Accessed May 23, 2018.
  5. 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 25: Introduction to Story Mapping*

Examples to review: **planning to move these to the story mapping page**

  1. Displacement in the Bay Area
  2. Mapping Segregation in DC.
  3. Creating a neighborhood change zoning plan for Spruce Hill
  4. Gangs of Los Angeles (2015)
  5. Atlas for a Changing Planet
  6. Katrina +10: A Decade of Change in New Orleans
  7. You can find more examples at ESRI’s gallery:
Thursday, February 27: Participatory Mapping (Kate Beck, SafeTREC, invited)*
  1. Parker, Brenda. “Constructing Community through Maps? Power and Praxis in Community Mapping.” Professional Geographer, 58:4, (2006): 470-484.
  2. 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.
  3. Check out the Street Story Project
Tuesday, March 3: Power, Place and Mapping (Steve Spiker, invited)*
  1. 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 5: Midterm Quiz #1

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

Date Lecture Slides Reading Assignment
Tuesday, March 10: 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 12: 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 8: In-Lab Midterm

Tuesday, March 17: Complex Urban Modeling: Machine Learning (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)
Thursday, March 19: Deploying Data Science Techniques in Urban Research
No lab this week!
Tuesday, March 31: Volunteered Geographic Information (Sam Maurer, guest speaker)*
  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.
Thursday, April 2: 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. Wheelan (2013) Chapters 8 & 11, “Correlation”, “Regression Analysis”

  3. Reades, J., De Souza, J., & Hubbard, P. (2018). Understanding urban gentrification through machine learning.
  4. Stewart, Matthew. 2019. “The Real Estate Sector is Using Algorithms to Work Out the Best Places to Gentrify.” Failed Architecture.
Tuesday, April 7: Open Data & Using Portals (Jason Lally, DataSF, Invited)*
  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. Wheelan (2013) Chapters 8 & 11, “Correlation”, “Regression Analysis”

  4. Johnson, Jeffrey Alan. 2014. “From Open Data to Information Justice.” Ethics and Information Technology 16 (4): 263–74.
Thursday, April 9: Midterm Quiz #2
Tuesday, April 14: 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. Johnson, Jeffrey Alan. 2014. “From Open Data to Information Justice.” Ethics and Information Technology 16 (4): 263–74.

    3. Explore additional interactive visualizations here

  3. 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 16: Defining Smart Cities in Theory and Practice* (guest speaker TBD)
  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), pp. 27-49

  3. T. Misra, "The New Digital Sanctuaries," Citylab, November 14, 2017.
Tuesday, April 21: Smart Institutions & e-Governance (Raleigh McCoy, MTC, invited)*
  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. P. Dourish, Code and the City, Rob Kitchin and Sung-Yueh Perng, eds. (Routledge, 2016), pp. 27-49

  3. Also look over smartcitizen.me/
Thursday, April 23: Civic Hacking and Equity (Emily Wasserman, Code for SF, invited)*
  1. Barns, Sarah. "Mine your data: open data, digital strategies and entrepreneurial governance by code." Urban Geography 37.4 (2016): 554-571.
  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), pp. 27-49

  3. T. Misra, "The New Digital Sanctuaries," Citylab, November 14, 2017.
Tuesday, April 28: 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.

  3. Doumont, Jean-luc. 2005. “The Cognitive Style of PowerPoint: Slides Are Not All Evil.” ResearchGate 52 (1): 64–70.
  4. T. Misra, "The New Digital Sanctuaries," Citylab, November 14, 2017.
  5. Parker, Ian. May 28, 2001. Absolute Powerpoint: Can a software package edit our thoughts? The New Yorker. Citylab, November 14, 2017.
  6. Optional Schwabish, Jonathan. 2017. Chapter 2 “Color” in Better Presentations: A Guide for Scholars, Researchers, and Wonks. New York: Columbia University Press. Citylab, November 14, 2017.
Thursday, April 30: 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. Tufte, Edward, R. 2003. The Cognitive Style of PowerPoint. Graphics Press.

  3. Doumont, Jean-luc. 2005. “The Cognitive Style of PowerPoint: Slides Are Not All Evil.” ResearchGate 52 (1): 64–70.
  4. T. Misra, Zook, Matthew. 2016. “Crowd-sourcing the Smart City: Using Big Geosocial Media Metrics in Urban Governance.” Unpublished paper.
Lab 14: Open Help Session (optional)