Foraging for Inspiration: Understanding and Supporting the Online Information Seeking Practices of Biologically Inspired Designers

Author:

Vattam Swaroop S.1,Goel Ashok K.1

Affiliation:

1. Georgia Institute of Technology, Atlanta, GA

Abstract

Finding suitable biological systems to emulate is one of the key initial steps in biologically inspired design. Designers often turn to online information environments such as the World Wide Web to seek biological sources of inspiration, which poses its own set of challenges. The focus of our research is to understand and address those challenges. In this paper, we first present an information-processing model of the task of seeking bio-inspiration in online information environments based on our observations of designers engaged in biologically inspired design. Then, we analyze the information foraging behavior of designers that is encapsulated in this model to understand the costs associated with this task. Next, we propose an approach for enhancing information environments to better support the task of seeking bio-inspiration. Our approach augments individual information resources within an information environment with conceptual models to make the task of finding relevant information resources more efficient. Finally, we describe an interactive online information environment called Biologue that realizes this approach.

Publisher

ASMEDC

Cited by 24 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. BioSpark: An End-to-End Generative System for Biological-Analogical Inspirations and Ideation;Extended Abstracts of the CHI Conference on Human Factors in Computing Systems;2024-05-11

2. BIDTrainer: An LLMs-driven Education Tool for Enhancing the Understanding and Reasoning in Bio-inspired Design;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

3. Biological knowledge capture and representation inspired by Zachman Framework principles;International Journal on Interactive Design and Manufacturing (IJIDeM);2023-03-15

4. Recognizing the Structure of Biological Designs in Text Documents;Design Computing and Cognition’22;2023

5. Free-text inspiration search for systematic bio-inspiration support of engineering design;Artificial Intelligence for Engineering Design, Analysis and Manufacturing;2023

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