Syllabus
Sensing and Urban Spaces
Urban Informatics 2 Data Workshop
Columbia Graduate School of Architecture, Planning and Preservation
Urban Planning Program
Spring 2020
Summary
tl;dr: Build sensors. Think about how data can support agendas in spatial and environmental justice, as well as enumerating use of public space. Play as a critical practice will be our M.O.
In recent years, interest in “public life” — people’s daily interactions within the built environment (Gehl 2011) — has been renewed as urban spaces are being transformed into areas for recreation, socializing and human activity. However, many of the commonly-accepted theories in environmental psychology and planning were generated from limited observations — limited by time and space. This course asks in what ways can sensing technologies validate or challenge these theories of public space and social interaction, and how do we intersect them with aspects of environmental quality and justice, sustainability, equity and overall general well-being?
In this semester, in addition to addressing critical questions of environmental equity and the use of public space, we critically engage in questions of “play” as a mechanism to consider questions of human-computer-urban interfaces and interaction with the public.
Participants in this hands-on workshop will design and implement prototypes for the creating of data on human activity, and environmental conditions and quality. Students will also learn methodologies to analyze and present the data. We will use the university context as a living laboratory to test and reevaluate the commonly-accepted theories of public life while engaging in critical conversations that balance the positive aspects of better-informed design and policy with the challenges concerning data ethics, surveillance, and privacy.
Learning Objectives
In this class, students will not only discuss how sensing technologies, as proxies for smart cities technologies, may or may not support larger design and justice objectives, students will also engage in hands-on development and testing of sensor prototypes to support their inquiries into these topics. As such, objectives for this class widely range from hardware development to theoretical understandings of the ethics involved in these technologies within a democratic society. Largely, we can think of the data within the framework of technical (from “technos”, meaning “art, skill, cunning of hand” as it pertains to the science of craft) and theoretical (as a set of knowledge and philosophically-based outcomes):
Technical: Ability to design and implement basic hardware prototypes; Ability to create and process machine data; Understanding of how sensing technologies work; Understand how to implement sensors to support planning objectives
Theoretical: Understand of the potentials and limitations of smart cities technologies; Understand the critical aspects of sensing and privacy, ethics and surveillance; Ability to discuss environmental and social justice differences across the fabric of the city using data; Ability to measure behavioral phenomena. Think critically about human-computer interfaces, including questions of empathy and reciprocity.
Ultimately, the objectives of this class is to learn by doing while being reflective practitioners as we question the application and use of these tools and discussions to the creation and promotion of better environments.
Instruction
This class marries several instructional formats to facilitate both an interrogation of these methods from a critical distance, but also by actively learning the methods through use. In the first approach, seminar-styled, student-driven discussions and presentations will consider various approaches and techniques, as well as their opportunities, limitations, and implications on research, design and planning. In a practical approach, a physical prototyping project will form the cornerstone by which we can engage in these conversations in an active sense, using the work as an anchor to the conversations surrounding these techniques and datasets. While certain class meeting sessions are planned for project development and discussion of research design and methods, students are expected to use their projects as additional discussion material throughout the semester.
Prerequisites
Due to the wide variation is skillsets, the general mantra for the class is that course participants are required, at a minimum, to approach the activities and lectures with enthusiasm, grit and/or perseverance. There is no other requirement although coding experience is highly recommended.
Equipment
Students will be building their own physical prototypes for deployment, and will be required to purchase any sensors or equipment they may require. An Arduino breadboard may be borrowed for final projects, but students are required to return this at the end of the term.
Assignments and Grading
The class is organized as a series of sprints — that organize the class toward the implementation of your final project. While these sprints are meant to frame sets of knowledge and skills, they should be thought of as discrete sections, but merely organizational stages in our learning.
Building Knowledge: To support a wider set of information gathering, the first half of the class has students collecting, collating and presenting case study precedent projects and readings to frame the state of understanding as we debate the potential relationships that digital information and the built environment have together. As groups, students will frame conversations for their peers to engage with these ideas and projects.
Peer Teaching: How do we translate activities and phenomena in the built environment using sensors? This module of the class everyone working together to create a common resource of sensor types and how they work — what they measure, and how. As a class, we will share this information with each other in presentational, hand-on, and archived manners for us to share this information that frames our prototyping and final project…
Final Project: The last third of the course is dedicated to a final group project, with an agenda of your choosing and may draw from any/all of the lessons from the course. We will be working with the NYC Parks Department, and projects should in some way address the challenges set forth by the Parks Department. The intent is for you to question the role of spatial and environmental equity and the policies that purport to enhance it. Here, you will implement a prototype that measures aspects of the use, interactions, quality and/or other metrics of the built environment and the people who occupy that space, and validate or disclaim those planning and design claims. You should implement the hardware with enough time to implement the sensors and to process the data.
Resources
Students are invited to visit the Columbia Makerspace in Mudd 254, as well as the GSAPP Fabrication Lab for ideas/inspiration/help in building their final prototypes.
Policies
This course will strictly enforce the GSAPP honor code, which can be viewed at https://www.arch.columbia.edu/honor-system. Plagiarism, including the use of another’s work in the class, is automatic grounds — at minimum — for failing. For more information, please refer to https://www.arch.columbia.edu/plagiarism-policy.
The School will make reasonable accommodations for persons with documented disabilities. Services are available only to students who have registered and submit appropriate documentation. As your instructor, I am happy to discuss specific needs with you as well. Please report any access related concerns about instructional material to Office of Disability Services and to me as your instructor.
Students are welcome to use electronic devices as long as they are being used for the strict and sole purpose of class-related material. Non-class related, on-screen materials during class time is strictly prohibited, unless given permission from the instructor. Penalties may include embarrassment, revoking of privileges or impacts to the student’s grade.
The University is committed to maintaining a safe environment for students. Because of this commitment and because of federal and state regulations, we must advise you that if you tell any of your instructors about sexual harassment or gender-based misconduct involving a member of the campus community, your instructor is required to report this information to the Title IX Coordinator, Margorie Fisher. While this information is considered private, it may lead to follow up. For more information on these policies, see https://www.arch.columbia.edu/discrimination-policy.
Lastly, the pressures of graduate school, family life, and living in New York City can be overwhelming. Too often in academia, and particularly in schools of architecture and planning, there is pride ascribed to unhealthy stress and behavior. (This class is about PLAY! so have fun!) While some is to be expected, should problems arise or you simply want to chat, please reach out to the instructor or the University’s resources. Your mental health and well-being are important and valued by the community, and an invitation is extended to you as a colleague and collaborator to chat at any time.
Unsolicited advice: It is guaranteed that you will be frustrated in this class—your code will not work and you won’t know why, or you’ve tried several solutions and they all fail. Technical learning is that it is best accomplished by doing, failing, failing to the point of frustration and doing some more. Expect frustrating moments to come, and be prepared to persevere past them. Mastering a technology always involves learning how to seek help with problems that exceed your understanding, even when Google or your chosen search engine fails you. It is worth noting that much of your learning will come through searching for answers, figuring out how to adapt what you found, and iterating until it works. Use each other as resources and share resources amongst yourselves. (Anecdotally, I once spent 8 hours frustratingly reviewing a modest piece of code that would not compile due to a single errant semi-colon.)
The best advice I can offer is to start early, and ask for help. Should you feel that despite your perseverance and resourcefulness that you are still finding problems, you should not hesitate to contact the instructor.
PS... You may want to remember this statement exists for later in the semester! ❤️
Schedule (abbreviated)
