Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900

1. TIFFANY CHEN Exercise #2: Case Studies in Data Analysis (5 Ways to Make a Story out of Numbers) Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900 Spring 2014

2. THE PUBLIC MEMORY What makes a “space” become a “place”? What defines the social and collective engagement of a place? With the following case studies, the narrative of a “Public Memory” is revealed through the connection of digital and physical space with ephemeral human impressions. In discovering public meaning derived from the collection of “sensed” memories, we are able to uncover patterns of urban engagement and ultimately create the public memory of “a place.” 1 | MY BLOCK NYC 2 | X-RAY TRAIN VISION 3 | MAP YOUR MOVES 4 | SERENDIPITOR 5 | LIVEHOODS

3. 1 | MY BLOCK NYC “My Block NYC” is an interactive video platform that creates a map of the city with users’ videos. The platform allows users to upload videos to a certain street, and users can then filter videos not just geographically, but also by age, time of day, and topic. As founder Alex Kalman states, “We wanted to create, online, a way to explore a city from the human perspective.” The project was part of the MoMa exhibit “Talk to Me: Design and the Communication between People and Objects.” http://www.myblocknyc.com/#/video/id/1035

4. 1 | MY BLOCK NYC

5. 1 | MY BLOCK NYC What is the raw data? Raw video footage uploaded by all users. What processes are deployed to transform the raw data to information? The video platform initiates geotagging and user inputted data in order to create meaningful filters for each uploaded video. What is the information that is the outcome of the aforementioned processes? The tagging of uploaded videos enables the platform to create a collective map of New York City using peoples’ videos.

6. 1 | MY BLOCK NYC How the act of sensing or access to raw data leads to comparison, judgment, reflection, reasoning, and abstraction? The access to raw video footage uploaded by users that is directly related to a personal memory and experience allows for other users to project and transform the data into a new public memory. As all films are shot outside and within one NYC block, data instances are isolated, but when layered and stitched together with the larger map, they present an extremely powerful reflection of the city’s past, present, and future. How the sum of all the above processes is resulting in a limited sort of agency for the data-driven construct? From the geo-tagging and categorization of videos by age, time of day, and topic, the My Block NYC interface ultimately creates a data-driven construct that provides users the ability to explore the city from a human perspective and build upon archived public memories. Urban agency is not limited, however, the visual and contextual agency of the uploaded videos are limited due to the tagging and direct connection to city blocks.

7. 2 | X-RAY TRAIN VISION This project presents a “Comfort Zone Display,” which shows train passengers where and how heavy the population of any given train is. Status screens, are equipped with unique information for certain trains, and thus allows riders to maintain more “comfortable” commuting conditions. http://www.psfk.com/2010/05/smart-display-shows-passenger-density-in-trains.html

8. 2 | X-RAY TRAIN VISION

9. 2 | X-RAY TRAIN VISION What is the raw data? Amount of people on the train, and their relative locations within the car. What processes are deployed to transform the raw data to information? Sensors that are within the train car send information to LED screens informing riders how many people are in each car. What is the information that is the outcome of the aforementioned processes? The sensing processes provide information on not only the number of people in each car, but also their relative positions, and concentration within a given spatial construct.

10. 2 | X-RAY TRAIN VISION How the act of sensing or access to raw data leads to comparison, judgment, reflection, reasoning, and abstraction? Riders are able to assess their relative “comfort level” in relationship to the visual density of people in each train car. How the sum of all the above processes is resulting in a limited sort of agency for the data-driven construct? This sensor and display based interface provides public transit users with not only information on the train platform, but also allows them to project their own comfort levels based on visual live-feed data. Users are provided with increased agency in their ability to better inform personal decisions on what conditions will be most “comfortable” for them as individuals.

11. 3 | MAP YOUR MOVES Map Your Moves is an interactive visual exploration of where New Yorkers have moved in the last decade. Through the processing of survey data and the isolation of geographic locations relating directly to movement towards and away form New York, this interface creates a dynamic narrative on the public memory of a transient city. http://moritz.stefaner.eu/projects/map%20your%20moves/

12. 3 | MAP YOUR MOVES What is the raw data? Survey data collected by WNYC from over 1,700 people. Geo-coordinate information was gathered from gpsvisulizer.com What processes are deployed to transform the raw data to information? Visual markers are used to correspond to specific zip code areas. What is the information that is the outcome of the aforementioned processes? The parsing of the collected data presents a narrative on the transient nature of New York City as an urban environment.

13. 3 | MAP YOUR MOVES How the act of sensing or access to raw data leads to comparison, judgment, reflection, reasoning, and abstraction? By visualizing not only movement but also volume of movement within a spatial construct, users of the interface experience the public memories of transient space. The process of connecting geographic movement with time and space captures many nuances of New York City that would otherwise often be missed. From the spectrum of movement types to inward and outward trajectories, this interface presents the city as an embodiment of its interstitial public memories. How the sum of all the above processes is resulting in a limited sort of agency for the data-driven construct? The visualization of the interface itself limits the agency of the data-driven construct, because all information is essentially seen in relation to one “node,” New York City. Even as users explore the peripheral nodes representing other cities around the globe, the data access and analyzed is always examined through the lens of the New York “bubble.”

14. 4 | SERENDIPITOR Inspired by the Situationists, Serendipitor is an iPhone app that utilizes Google’s Map API to “find something by looking for something else.” The app combines directions generated by the routing service with instructions for action and movements. As one navigates the route, directions are design to “minor displacements” which allow users to form unanticipated connections with their surroundings and ultimately heighten the imageability of the city itself. Project Video: http://vimeo.com/14205766

15. 4 | SERENDIPITOR What is the raw data? User inputted locations and Google Maps GPS tracking. What processes are deployed to transform the raw data to information? The Google Maps API routing services provides a variety of directions for the user to choose from. The application then applies its own set of directions to create an added layer of discovery to transform pure locational information into an experiential journey. What is the information that is the outcome of the aforementioned processes? A previously unexplored and unexamined route is revealed.

16. 4 | SERENDIPITOR How the act of sensing or access to raw data leads to comparison, judgment, reflection, reasoning, and abstraction? The processing of a simple urban route allows for the user to reflect upon the creation of their personal urban memories. The application is not about providing a means to get from point A to point B, but rather about injecting a sense of urban consciousness into the user. How the sum of all the above processes is resulting in a limited sort of agency for the data-driven construct? Seredipitor ultimately limits the user’s agency by defining set routes with explicit instructions along the way.

17. 5 | LIVEHOODS Livehoods reveals how people and places in a city connect to form the dynamic characters of local urban areas. The shapes of these hoods are determined by the patterns of people who check-in to them, and if many of the same people check-in to two nearby locations, these locations then become part of the same livehood. Neighborhoods are no longer defined by static boundaries, but rather by organic patterns of congregation. http://livehoods.org/maps/nyc

18. 4 | LIVEHOODS

19. 4 | LIVEHOODS What is the raw data? Dots are used to represent check-in locations, and groups of nearby dots of the same color form a virtual “livehood.” Tweets and social media check-ins are used as raw data. What processes are deployed to transform the raw data to information? Given data from over 18 million foursquare check-ins, Livehoods groups nearby venues into areas based on patterns in the set of people who check-in to them. What is the information that is the outcome of the aforementioned processes? Through the processing of raw data such as tweets and check-ins, Livehoods is able to investigate factors that come together to shape the social dynamics of city, including municipal borders, demographics, geography, and architecture. To the left is a neighborLivehoods map of Pittsburgh hood known as the Southside Flats, and as shown by the color-coded markers, there are four separate livehoods within it. According to the map people who frequent the blue area actually come from other surrounding areas. Why? The small blue Livehood is a plaza with a grocery store. Grocery stores tend to have important implications for both community and economic development, because they anchor neighborhoods and attract new businesses. In this context, Livehoods is an extremely resourceful tool to help people understand their communities and implement new improvement projects.

20. 4 | LIVEHOODS How the act of sensing or access to raw data leads to comparison, judgment, reflection, reasoning, and abstraction? By examining patterns of check-ins, Livehoods is able to learn about the different areas that comprise a city, allowing users to study the social dynamics, structure, and character of cities on a large scale. Like neighborhoods, Livehoods are a representation of the organizational structure of the city; Livehoodsgive users a human perspective of a city’s structure, and allow us to reconceptualize the dynamics of a city based on the way people actually use it. How the sum of all the above processes is resulting in a limited sort of agency for the data-driven construct? The analysis of contextual connections from check-in data occurring in close range limits the agency of the construct to the temporal nature of people’s patterns of movement. This agency, however, is ultimately the way in which the interface is truly able to dissect and isolate neighborhood instances within the larger urban fabric.