OCAD University Open Research Repository

Documented: Embedding and Retrieving Information from 3D Printed Objects

Ettehadi, Omid / OE (2020) Documented: Embedding and Retrieving Information from 3D Printed Objects. Masters thesis, OCAD University.

Item Type: Thesis
Creators: Ettehadi, Omid / OE

Documentation is an essential aspect of building interactive physical objects. For makers, documentation serves as a record that can be shared with others to demonstrate a project’s building (what and how) and decision-making (why) process. A documentation’s end-users (i.e., the makers themselves or people interested in rebuilding or learning about the project) can then self-refect on these records and take away their own lessons regarding the project. However, in the case of physical objects, we think that refecting on their documentation can be challenging since the documentation and the object are two separate artifacts. We explore this assumption in this thesis. Specifcally, we asked if embedding the documentation into the object being made will promote self-refection and whether this facilitates a deeper understanding of the object and its design process.
We took three main steps to address our questions: (1) we used artifact analysis to identify the strengths and limitations of current documentation styles (i.e., text, picture, and video-based documentations) that makers typically use; (2) we conducted interviews and brainstorming sessions with professional and hobbyist makers, and asked them to determine the strengths and weaknesses of their current documentation techniques, and the improvements they envision regarding the connection between their documentation and the built object; (3) informed by our artifact analysis and interview sessions, we proposed a prototype that provides a new method to interact with an object’s documentation, which allows people to embed and retrieve documentation-related data into and from the object, respectively.

Date: 1 April 2020
Uncontrolled Keywords: design process, documentation, data embedding, digital fabrication, self-refection, refective learning
Divisions: Graduate Studies > Digital Futures
Date Deposited: 06 May 2020 03:49
Last Modified: 20 Dec 2021 21:30
URI: http://openresearch.ocadu.ca/id/eprint/2946

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