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

Student Name Surname Exercise #1: Case Studies in Sensing and Data Collection Real-Time Cities: an Introduction to Urban Cybernetics Harvard Design School: SCI 0646900 Spring 2014

1 | FUELBAND Its an app that visually tells a story of an individual’s daily and weekly activity / mobility trends. Project Video: http://fathom.info/yearinnikefuel

1 | FUELBAND

1 | FUELBAND Its an app that visually tells a story of an individual’s daily and weekly activity / mobility trends. Projct Video http://fathom.info/yearinnikefuel

1 | FUELBAND How was the data collected? The data was collected through a wrist band, and the outcome was visualized using Processing Why was the data collected? What is interesting about the data? The data was collected to understand daily motion/routines of nikefuelband users. This visualization gave insight on other behavior patterns found in the anonymous data, for example, to identify how the working dad, the mountaineer, the gym-rat, and the city slicker all have distinct patterns, routines, and lifestyles. Different accomplishments, interactions, events, and even prototypical days emerged in the presentation of the data. What stories about the urban dynamics can the collected data tell? The data is focused more on individual analysis, rather than urban dynamics analysis, but this information offers insighsiin urban dynmics if you show the individuals collectively in a specific geographic location, age, etc. What sort of questions about urban dynamics can be answered by looking at the data? The cadence and intensity of how each person moves, which is something is incredibly personal, yet we rarely have the opportunity to see those patterns for ourselves. This application provides awareness to each individual about self mobility, but also gives insighrs on sleeping behaviour, and other well being related factors. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? The data collected is limited to the wrist ban inputs.

1 | FUEL BAND How are particular patterns highlighted through techniques for tagging the data in order of their importance? The top of the image is meant to be striking but unique, and as a poster, suitable for viewing on the wall and at a distance: it should be evocative but also true to the data. For a closer look, the area at the bottom focuses on breaking down the actual numbers and the details of movement as recorded by the FuelBand. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? The data collected is always clear and precise (movement – exercise) but because of the visualization way, other data starts to play a role on the picture (sleeping, napping) adding more information to that what was it intended to be. Precise numbers and graphics can be found at the botom regarding the original questions addressed. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? The data is dinamic and it changes in a real time basis when using the wrist band Who is the target audience of the data presentation? Made for sport junkies – highly active people, but can be used by any individual interested in tracking their daily routines What are their goals when approaching the data presentation? What do they stand to learn? understand the similarities and differences that define the movement of the Nike+ FuelBand community. Studying minute by minute the activity of more than a million of users in the world.

2| THE PLEASANT PLACES TO LIVE A visualization analisis of where in the U.S. will you find the most “pleasant” days in a year. “pleasant” here means the mean temperature was between (55° F and 75° F), the minimum temperature was above 45° F, the maximum temperature was below 85° F and there was no significant precipitation or snow depth. Project Video http://www.kellegous.com/j/2014/02/03/pleasant-places/

2 | THE PLEASANT PLACES TO LIVE

2 | THE PLEASANT PLACES TO LIVE How was the data collected? First Kelly Norton (author) constituted what a “pleasant” day is and then they aggregate NOAA data for the last 23 years to figure out the regions of the United States with the most (and least) pleasant days in a typical year Why was the data collected? What is interesting about the data? To understand which cities of the US are the most pleasant to live in What stories about the urban dynamics can the collected data tell? The story is quite minimalistic and straightforward. There is only one story and map with dots and a zip-code search that accounts only for temperature. What sort of questions about urban dynamics can be answered by looking at the data? The questions that arise from this data are more related to what is missing in this chart that what is there. For example, what about precipitation, pollution, traffic, violence.. Kelly Norton is only considering one small factor that is temperature. That factor in itself is important but it is not the only one to take in account for addressing pleasant cities to live in . How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? The data is simple, taken from one webpage, and the presentation is minimalistic which makes the information easy to understand, and deliverable to various types of audiences..

2 | THE PLEASANT PLACES TO LIVE How are particular patterns highlighted through techniques for tagging the data in order of their importance? The definition Norton settled on was a day with average temperature between 55 and 75° F, a minimum temperature above 45° F and a maximum below 85° F, and no significant rain or snowfall. This is represented through points that have minimal information about the yearly weather of that city. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? The word “pleasant” could be understood as talking about temperature exclusively, but it can be also mis-interpreted with defining a city that has a great quality of life, and therefore confuse the viewers since the chart is only considering temperature. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? The data is static, and the posibilities for it to change are low since the study was based on a 23 year analysis of the weather. Who is the target audience of the data presentation? People interested in US cities livability or people, living in the US What are their goals when approaching the data presentation? What do they stand to learn? The goal is to view graphically the most pleasant cities to live in the US, taking only in account temperature.

3. EYE WRITER Members of Free Art and Technology (FAT), OpenFrameworks, the Graffiti Research Lab, and The Ebeling Group communities have teamed-up with a legendary LA graffiti writer, publisher and activist, named TEMPTONE. Tempt1 was diagnosed with ALS in 2003, a disease which has left him almost completely physically paralyzed… except for his eyes. This international team is working together to create a low-cost, open source eye-tracking system that will allow ALS patients to draw using just their eyes. The long-term goal is to create a professional/social network of software developers, hardware hackers, urban projection artists and ALS patients from around the world who are using local materials and open source research to creatively connect and make eye art. Project Video http://eyewriter.org

1 | Sensing the City

3) EYE WRITER How was the data collected? It is an open source software for commercially available eye tracking devices and a DIY hardware and free software. You can use for data collection for example, the Playstation Eye by Sony, and in a way they are re-appropiating a technology and linking it ti a software they developed. Why was the data collected? What is interesting about the data? The data is collected to produce a visual image displayed either on computer or on a building façade. This tool was done to allow people with paralysis to draw creatively with the movement of the eye. What is interesting is that it is a tool for empowerment and social change, promoting health and bringing awareness about ALS and other forms of paralysis. What stories about the urban dynamics can the collected data tell? It is a low cost creative technology to enable graffitti writers and artists with paralysis to draw using only their eyes, Its more a tool for individuals than an urban dynamics tool, but the imags can be projected in real time on a façade. of a building as grafffitii art.. What sort of questions about urban dynamics can be answered by looking at the data? This graffiti art brings awareness on artists with paralysis,iits democratizing public expression art through technology. How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? The data collected is limited to the eye movement possibilities

3) EYE WRITER How are particular patterns highlighted through techniques for tagging the data in order of their importance? The software has buttons to achieve different outcomes on drawing, still its limited to what the software can do, the colors available, pencil thickness. It’s a basic tool that could have added faetures in a future How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? The question adressed is answerd correctly and the outcome is straightforward. Nevertheless, the final presentation ot the data can be modified in various waysLVisuallizing it on the street, printing it for gallery purposes or simply enjoying it on a screen. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Its static, it’s a picece that has a start and an end. Yo can always do new art piees Who is the target audience of the data presentation? People with paralysis, ALS and others. What are their goals when approaching the data presentation? What do they stand to learn? The creators want this to be a tool for empowerment , for social change, to promote health reform and awarenes about ALS

4) UNICEF URBAN POPULATION MAP Data visualization of urban populations growth . Project Video: http://www.unicef.org/sowc2012/urbanmap/

4) UNICEF URBAN POPULATION MAP How was the data collected? To visualize this information, Periscopic evolved an existing map and infographicfrom Unicef’s State of the World’s Children report, and added functionality that displays the growth of urban populations from 1950 – 2050, as well as information about population for over 100 countries. It was developed in HTML5. Why was the data collected? What is interesting about the data? The data was collected for site visitors to compare total population figures against the percentage of each country that is urban for all years. It alows the viewer to understand that most people (including children living in poverty) are living in urban environments. What stories about the urban dynamics can the collected data tell? The visualization demonstrates three points: global population rates are increasing, cities are expanding, but the world isn’t getting larger What sort of questions about urban dynamics can be answered by looking at the data? Questions on economic growth, world population vs urban population, sustainability issues, future How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? They abstracted the data from the Unicefs “State of the Worlds Children” Annual Report. They combined this data with world population data from 1960 to projected 2050 data.

4) UNICEF URBAN POPULATION MAP How are particular patterns highlighted through techniques for tagging the data in order of their importance? The viewer can tap into the growing circles of urban population and obtain data on urban population numbers and percentage of it that is urban. How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? By choosing 2 relevant data sets: Urban population and % of it living in urban areas. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Static Who is the target audience of the data presentation? The audience is people in general and the aim is to create awareness of children living in poverty within urban areas What are their goals when approaching the data presentation? What do they stand to learn? The outcome of the visualization was succesfull taking in account the graphics and information displayed, but they fail to convey the idea of how hard It is to be a kid under poverty, living in a city

5) MANHATTAN MOCAP – OLIMPICS 2012 Manhattan Mocap captured the motion of three of the US medalists' (Dana Vollmer, 3-times Gold, Abby Johnston Silver, and Nick McCroryBronce) signature dives and swim styles and analyzed their summersaults, butterfly and dolphin kicks in previously unseen angles. Project Video: http://manhattanmocap.com/olympics2012

5) MANHATTAN MOCAP – OLIMPICS 2012

5) MANHATTAN MOCAP How was the data collected? They developed and deployed a sensor- motion capture system to record and 3D reconstruct their signature performances Why was the data collected? What is interesting about the data? What is interesting about the data is that it is not only showing information to an awdience, but that its also helping improve the performance of professional athletes. What stories about the urban dynamics can the collected data tell? Performance, movement What sort of questions about urban dynamics can be answered by looking at the data? The questions are more related to an individuals performance during a competition in relationship to their movements How is the magnitude of the data is dealt with; limiting the collected data, limiting the dimensions in the data set, or abstracting the data? They are taking in consideration movement and speed y, limiting the data to that. It would be interesting if they could compare the data of several people together to see what makes the winner win in terms of movement. The graphic is divided in kick, grab, recovery, and then again kick, grab and so forth.

5) MANHATTAN MOCAP How are particular patterns highlighted through techniques for tagging the data in order of their importance? Pionts in the body through space. 2. Graphic data on speed (kick, grab, recovery) How does the original question to be addressed operate as the benchmark for eliminating unnecessary details in the data? The question is answered vaguely with graphics that are lacking performance information. Is the data of a static or dynamic nature? If dynamic, what is the frequency of change and what happens when it starts to change? Static data Who is the target audience of the data presentation? Public interested in the Olimpics and Performance. This tool can also be used by profesional swimmers/athletes to track their performances What are their goals when approaching the data presentation? What do they stand to learn? They want to visualize the performance of several athletes and understand their patterns of movement and speed.

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