Data Physicalization

Dozenten:
Beat Rossmy (LMU) , Luke Haliburton (LMU)
Ceenu George (Universität Augsburg)
Rosa van Koningsbruggen (Bauhaus-Universität Weimar)
Betreuende Professoren:
PD Dr. habil. Alexander Wiethoff (LMU)
Semesterwochenstunden: 4
ECTS-Credits: 6
Modul:
P3.2:
Designworkshop 2 (für Master MCI)
P2, P3 oder P6:
Vertiefende Themen für Master

• Inhalte
• Bewerbung
• Zeitplan
• Ort

Inhalte

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).

Bewerbung

Interessierte Studenten können sich für dieses Praktikum über Uni2Work bewerben.

Alle Bewerbungen sollen folgende Informationen enthalten:

• Beschreiben Sie kurz Ihre Motivation für die Teilnahme an diesem Kurs.
• Beschreiben Sie relevante Fachkenntnisse, beispielsweise aus früheren Kursen, Jobs und anderen Projekten.

Zeitplan

Course Times

Lecture: Monday 9:15 - 10:45

Tutorial: Monday 11:00 - 12:30

Ort

TBA