Collaborative Course:

Dessau Department of Design + Dessau Institute of Architecture

Coordinators and Tutors:

Manuel Kretzer (DDD) & Sina Mostafavi (DIA)

Tuesdays, 9:30 - 12:30

Rooms

Materiability Lab (05, 026)
Design Project Space (01, 102)
DIA Studio Space (03, 103)
Robotics Lab (05, 032)

Dates

8. Oct. / 12:00 / 03, 103 _ First Meeting & Intro  
8. Oct. _ Start DIA students & First Assignment
22. Oct _ Start Design students & DIA Presentations
19. Nov _ First Group Presentations 
17. Dec _ Second Group Presentations   
25. Jan _ Final Group Presentations during Dessau Design Schau

Introduction

With the continuous rise of smartwatches, fitness trackers and other wearable devices the amount of personal data that we are constantly collecting keep growing endlessly. Steps, active energy, sleep, heart rate, blood sugar, blood pressure, weight, calories, nutrition, water intake, meditation, activities, places, means of transport, screen time, productivity, workouts, mood, stairs, bodyfat, social interaction, music are just a few of the things we can easily keep track off. Most of this data leads to something that is commonly referred to as the “quantified self,” which is both a cultural phenomenon of self-tracking through technology and a community of consumers and suppliers of self-tracking tools who share an interest in self-knowledge and personal improvement through numbers.

Whilst the quantified self-movement has faced varied criticism related mostly to issues of data privacy and health literacy skills, the focus of this course is less on individual perfection or social challenges but rather on the question, how these tools could be useful for us as designers.

What do all these numbers stand for and is there more to find than a personal diary or the achievement of consecutive goals?

Is it possible to abstract that data and use it for something else, something physical, something tangible?

Can the tools that help us record and collect that information become tools for design? Can we draw shapes with our heartbeat? Can we sculpt forms through the number of steps we walk or the calories we burn? Can sleep quality become a replacement for the computer mouse and hence would this allow us to work in our sleep?

Can we control the results through self-conditioning or through smart means of translation rather than them being pure representations of our daily activities?

Or lies the potential of personal information solely in the creation of individualised responses?

Brief

Students in this course will work in interdisciplinary teams, comprised of both architecture and design students. The first task will be to understand and decide what types of personal data each group can collect, how they vary among different persons and situations and how they can be compared or combined. Are there correlations between the different strains - such as being more productive when it rains or when a certain type of music is played - and how do they influence each other. Depending on the extent of these numeric figures the groups are then asked to develop methods to manipulate and translate the results and finally decide on how they can become productive tools for design. Using an industrial robot as well as other digital fabrication procedures, such as laser cutting, milling or 3D printing the final task will be to develop a collection of physical objects. The set of objects should both show that they belong to the same procedure but also stand for their individuality.

Requirements

Each student should have at least a smartphone, which can track steps and location and if possible some sort of fitness or activity tracker like an Apple Watch, Nike+ Fuel, Fitbit or similar https://www.techradar.com/news/best-cheap-activity-trackers. There are various apps for both IOS and Android that allow for the collection of different sets of data, some of which are mentioned in the links below or can be found doing a quick web search. Students should also have a laptop computer with McNeel Rhino https://www.rhino3d.com/download and interest/ knowledge in using Grasshopper (or any other programming language such as Processing or Python).

Further Reading

https://www.thevectorimpact.com/how-to-change-your-life/
http://www.markwk.com/data-analysis-for-apple-health.html
https://quantifiedself.com/
http://www.ryanpraski.com/apple-health-data-how-to-export-analyze-visualize-guide/
https://blog.rescuetime.com/doing-beautiful-things-with-self-tracking-data/
https://blog.zenobase.com/post/100624681047
http://feltron.com/FAR14.html
http://manuellukas.me/projects/tracking/tracking.html
http://responsivedesign.de/the-entire-history-of-me/ 
http://responsivedesign.de/the-shape-of-music/
http://responsivedesign.de/generative-art/ 
https://blog.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life/
http://sinamostafavi.com/project/robotic-painting-of-material-architecture/
http://sinamostafavi.com/project/multicolor-robotic-light-printing/
http://sinamostafavi.com/project/tram-robotic-stepframes/