Data Physicalization

Lecturer:
Beat Rossmy (LMU) , Luke Haliburton (LMU)
Ceenu George (Universität Augsburg)
Rosa van Koningsbruggen (Bauhaus-Universität Weimar)
Professor in Charge:
PD Dr. habil. Alexander Wiethoff (LMU)
Hours per week: 4
ECTS credits: 6
Modul:
P3.2:
Designworkshop 2 (für Master MCI)
P2, P3 oder P6:
Vertiefende Themen für Master

• Contents
• Application
• Schedule
• Location

Contents

Computers and sensors are becoming more and more integrated and ubiquitous in users' daily environments and routines. Thus, the amount and types of information that is collected is constantly growing. In communication between users, such information can be crucial, but is sometimes difficult to convey due to the lack of language. For example, it is easy to report on a successful training session by referring to miles run or time spent in the gym, but other areas lack such quantifiable metrics or even understandable language at all. We call such information "hidden data" that is typically not directly accessible to users, such as hormone levels, emotional status, or memories and dreams. The goal of this course is to explore the possibilities of data physicalization of such "hidden data", allowing users to learn a physical language that they can use as a medium for implicit or explicit communication in a collocated situation. The course is conducted in an interdisciplinary collaboration between LMU Munich, Bauhaus University Weimar, and University of Augsburg and aims to explore and prototype physical artifacts. In this course, students will focus on research topics such as "interactive/intelligent materials", "flexible/deformable interface materials", "shape-changing interfaces", and "ambient/peripheral interfaces". We encourage students to participate who have a high interest in prototyping with hardware (e.g., Arduino), working with unconventional materials (e.g., silicone), or using traditional fabrication techniques (e.g., origami-folding).

Application

Interested students can apply for this course via Uni2Work .

All applications have to include the following information:

• Briefly describe your motivation for participation in this course.
• Describe relevant expertise, for example from previous courses, jobs and other projects.

Schedule

Course Times

Lecture: Monday 9:15 - 10:45

Tutorial: Monday 11:00 - 12:30

Location

TBA