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On the benefits of digital libraries of case studies of analogical design: Documentation, access, analysis, and learning

Published online by Cambridge University Press:  27 April 2015

Ashok K. Goel*
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, USA Center for Biologically Inspired Design, Georgia Institute of Technology, Atlanta, Georgia, USA
Gongbo Zhang
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, USA
Bryan Wiltgen
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, USA
Yuqi Zhang
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, USA
Swaroop Vattam
Affiliation:
Design & Intelligence Laboratory, School of Interactive Computing, Georgia Institute of Technology, Atlanta, Georgia, USA Naval Research Laboratory, Washington, District of Columbia, USA
Jeannette Yen
Affiliation:
Center for Biologically Inspired Design, Georgia Institute of Technology, Atlanta, Georgia, USA
*
Reprint requests to: Ashok K. Goel, School of Interactive Computing, Georgia Institute of Technology, Technology Square Research Building, 85 Fifth Street NW, Atlanta, GA 30332, USA. E-mail: goel@cc.gatech.edu

Abstract

Digital libraries of case studies of analogical design have been popular since their advent in the early 1990s. We consider four benefits of digital libraries of case studies of analogical design in the context of biologically inspired design. First, a digital library affords documentation. The 83 case studies in our work come from 8 years of extended, collaborative design projects in an interdisciplinary class on biologically inspired design. Second, a digital library provides on-demand access to the case studies. We describe a web-based library of case studies of biologically inspired design called the Design Study Library (DSL). Third, a compilation of case studies supports analyses of broader patterns and trends. As an example, an analysis of DSL's case studies found that environmental sustainability was a major factor in about a third of the case studies and an explicit design goal in about a fourth. Fourth, a digital library of case studies can support analogical learning. Preliminary results from an exploratory study indicate that DSL may support novice learning about the processes of biologically inspired design.

Type
Special Issue Articles
Copyright
Copyright © Cambridge University Press 2015 

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References

REFERENCES

Aamodt, A., & Plaza, E. (1994). Case-based reasoning: foundational issues, methodological variations, and system approaches. AI Communications 7(1), 3959.Google Scholar
Altshuller, G. (1984). Creativity as an Exact Science: The Theory of the Solution of Inventive Problems (Williams, A., Trans.). Amsterdam: Gordon & Breach.CrossRefGoogle Scholar
Barber, J., Bhatta, S., Goel, A., Jacobson, M., Pearce, M., Penberthy, L., Shankar, M., Simpson, R., & Stroulia, E. (1992). AskJef: integrating case-based and multimedia technologies for interface design advising. Proc. 2nd Int. Conf. Artificial Intelligence in Design (AID-92), pp. 457–476. Dordrecht: Kluwer Academic.Google Scholar
Bar-Cohen, Y. (Ed.). (2011). Biomimetics: Nature-Based Innovation. Boca Raton, FL: CRC Press.Google Scholar
Baumeister, D., Tocke, R., Dwyer, J., Ritter, S., & Benyus, J. (2012). Biomimicry Resource Handbook: Biomimicry 3.8. Missoula, MT: Biomimicry Group.Google Scholar
Benyus, J. (1997). Biomimicry: Innovation Inspired by Nature. New York: William Morrow.Google Scholar
Bhatta, S., & Goel, A. (1997). An analogical theory of creativity in design. Proc. 2nd Int. Conf. CBR (ICCBR-97), LNCS, Vol. 1266, pp. 565–574. New York: Springer.CrossRefGoogle Scholar
Bhushan, B. (2009). Biomimetics: lessons from nature—an overview. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367(1893), 14451486.Google Scholar
Biomimicry 3.8 Institute. (2008). AskNature. Accessed at http://www.asknature.org/ on May 29, 2013.Google Scholar
Bonser, R., & Vincent, J. (2007). Technology trajectories, innovation, and the growth of biomimetics. Journal of Mechanical Engineering Science 221(10), 11771180.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B. (2005). A functional representation for aiding biomimetic and artificial inspiration of new ideas. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19(2), 113132.Google Scholar
Christensen, B., & Schunn, C. (2007). The relationship of analogical distance to analogical function: the case of engineering design. Memory and Cognition 35(1), 2939.Google Scholar
Clancey, W. (1997). Situated Cognition: On Human Knowledge and Computer Representations. New York: Cambridge University Press.Google Scholar
Clement, J. (2008). Creative Model Construction in Scientists and Students: The Role of Imagery, Analogy, and Mental Simulation. Dordrecht: Springer.Google Scholar
Corbin, J., & Strauss, A. (2008). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, 3rd ed.Thousand Oaks, CA: Sage.Google Scholar
Davies, J., Goel, A., & Nersessian, N. (2009). A computational model of visual analogies in design. Journal of Cognitive Systems Research 10(3), 204215.Google Scholar
Deldin, J.M., & Shuknecht, M. (2014). The AskNature Database: enabling solutions in biomimetic design. In Biologically Inspired Design: Computational Methods and Tools (Goel, A., McAdams, D., & Stone, R., Eds.). New York: Springer.Google Scholar
Dunbar, K. (1997). How scientists think: on-line creativity and conceptual change in science. In Creative Thought: An Investigation of Conceptual Structures and Processes (Ward, T., Smith, S., & Vaid, J., Eds.), pp. 461493. Washington, DC: American Psychological Association.Google Scholar
Ehrenfeld, J. (2008). Sustainability by Design: A Subversive Strategy for Transforming Our Consumer Culture. New Haven, CT: Yale University Press.Google Scholar
French, M. (1994). Invention and Evolution: Design in Nature and Engineering, 2nd ed.New York: Cambridge University Press.Google Scholar
Gebeshuber, I.C., Gruber, P., & Drack, M. (2009). A gaze into the crystal ball: biomimetics in the year 2059. Journal of Mechanical Engineering Science 223(12), 28992918.Google Scholar
Gebhardt, F., Voß, A., Gräther, W., & Schmidt-Belz, B. (1997). Reasoning With Complex Cases. Norwell, MA: Kluwer.Google Scholar
Gentner, D., & Markman, A. (1997). Structure mapping in analogy and similarity. American Psychologist 52(1), 4556.Google Scholar
Gleich, A. von, Pade, C., Petschow, U., & Pissarskoi, E. (2010). Potentials and Trends in Biomimetics. Berlin: Springer.Google Scholar
Goel, A. (1997). Design, analogy, and creativity. IEEE Expert 12(3), 6270.Google Scholar
Goel, A., Bras, B., Helms, M., Rugaber, S., Tovey, C., Vattam, S., Weissburg, M., Wiltgen, B., & Yen, J. (2011). Design patterns and cross-domain analogies in biologically inspired sustainable design. Proc. AAAI Spring Symp. AI and Sustainable Design, pp. 45–51, Stanford University, Palo Alto, CA, March.Google Scholar
Goel, A., & Chandrasekaran, B. (1992). Case-based design: a task analysis. In Artificial Intelligence Approaches to Engineering Design: Vol. 2. Innovative Design (Tong, C., & Sriram, D., Eds.), pp. 165184. San Diego, CA: Academic Press.Google Scholar
Goel, A., & Craw, S. (2005). Design, innovation and case-based reasoning. Knowledge Engineering Review 20(3), 271276.CrossRefGoogle Scholar
Goel, A., Vattam, S., Wiltgen, B., & Helms, M. (2012). Cognitive, collaborative, conceptual and creative—four characteristics of the next generation of knowledge-based CAD systems: a study in biologically inspired design. Computer-Aided Design 44(10), 879900.Google Scholar
Goel, A., Vattam, S., Wiltgen, B., & Helms, M. (2014). Information-processing theories of biologically inspired design. In Biologically Inspired Design (Goel, A., McAdams, D., & Stone, R., Eds.). London: Springer–Verlag.CrossRefGoogle Scholar
Goel, A., Zhang, G., Wiltgen, B., Zhang, Y., Vattam, S., & Yen, J. (2014). The design study library: collecting, analyzing and using case studies of biologically inspired design. Proc. 6th Int. Conf. Design Computing and Cognition, London, June 23–25.Google Scholar
Greeno, J. (1998). The situativity of knowing, learning, and research. American Psychologist 53(1), 526.CrossRefGoogle Scholar
Hayes, C., Goel, A., Tumer, I., Agogino, A., & Regli, W. (2011). Intelligent support for product design: looking backwards, looking forwards. ASME Journal of Computing and Information Science in Engineering 11(2), 020117.Google Scholar
Herrid, C. (Ed.). (2007). Start with a Story: The Case Study Method of Teaching College Science. Arlington, VA: NSTA Press.Google Scholar
Hey, J., Linsey, J., Agogino, A., & Wood, K. (2008). Analogies and metaphors in creative design. International Journal of Engineering Education 24(2), 283294.Google Scholar
Hoeller, N., Goel, A., Freixas, C., Anway, R., Upward, A., Salustri, F., & Miteva, K. (2013). Developing a common ground for learning from nature. Zygote Quarterly 7, 133145.Google Scholar
Hofstadter, D. (Ed.). (1996). Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought. New York: Harvester Wheatsheaf.Google Scholar
Holyoak, K., & Thagard, P. (1996). Mental Leaps: Analogy in Creative Thought. Cambridge, MA: MIT Press.Google Scholar
Hua, K., Faltings, B., & Smith, I. (1996). CADRE: case-based geometric design. Artificial Intelligence in Engineering 10(2), 171183.Google Scholar
Hung, W., Jonnasen, D., & Liu, R. (2008). Problem-based learning. In Handbook of Research on Educational Communications and Technology (Spector, J., Merrill, M., van Merriënboer, J., & Driscoll, M., Eds.), Vol. 1., 3rd ed., pp. 485506. Mahwah, NJ: Erlbaum.Google Scholar
Jacobs, S., Nichol, E., & Helms, M. (2014). Where are we now, and where are we going? The BioM Innovation Database. ASME Journal of Mechanical Design 136(11).Google Scholar
Kolodner, J. (1993). Case-Based Reasoning. San Francisco, CA: Morgan Kauffman.Google Scholar
Kolodner, J. (1997). Educational implications of analogy: the view from case-based reasoning. American Psychologist 52(1), 5766.CrossRefGoogle ScholarPubMed
Kulinski, J., & Gero, J. (2001). Constructive representation in situated analogy in design. Proc. CAADFutures, pp. 507–520. Amsterdam: Kluwer.Google Scholar
Lave, J., & Wenger, E. (1991). Situated Learning: Legitimate Peripheral Participation. New York: Cambridge University Press.CrossRefGoogle Scholar
Lepora, N., Verschure, P., & Prescott, T. (2013). The state of the art in biomimetics. Bioinspiration & Biomimetics 8(1).CrossRefGoogle ScholarPubMed
Maher, M., & Gomez, A. (1997). Case-based reasoning in design. IEEE Expert 12(2), 3441.Google Scholar
Maher, M., & Pu, P. (Eds.). (1997). Issues and Applications of Case-Based Reasoning in Design. Mahwah, NJ: Erlbaum.Google Scholar
Pearce, M., Goel, A., Kolodner, J., Zimring, C., Sentosa, L., & Billington, R. (1992). Case-based decision support: a case study in architectural design. IEEE Intelligent Systems 7(5), 1420.Google Scholar
Prade, H., & Gilles, R. (2014). Computational Approaches to Analogical Reasoning: Current Trends. New York: Springer.CrossRefGoogle Scholar
Prince, M.J., & Felder, R.M. (2006). Inductive teaching and learning methods: definitions, comparisons, and research bases. Journal of Engineering Education 95(2), 123138.Google Scholar
Qian, L., & Gero, J. (1996). Function–behavior–structure paths and their role in analogy-based design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 10(4), 289312.Google Scholar
Riesbeck, C., & Schank, R. (1989). Inside Case-Based Reasoning. Mahwah, NJ: Erlbaum.Google Scholar
Shu, L., Ueda, K, Chiu, I., & Cheong, H. (2011). Biologically inspired design. CIRP Annals of Manufacturing Technology 60(2).Google Scholar
Sycara, K., Guttal, R., Koning, J., Narasimhan, S., & Navinchandra, D. (1991). CADET: a case-based synthesis tool for engineering design. International Journal of Expert Systems 4(2), 157188.Google Scholar
Thomas, J. (2000). A Review of Research on Problem-Based Learning. San Rafael, CA: AutoDesk Foundation.Google Scholar
Turner, J. (2007). The Tinkerer's Accomplice: How Design Emerges from Life Itself. Cambridge, MA: Harvard University Press.Google Scholar
Turner, J., & Soar, R. (2008). Beyond biomimicry: what termites can tell us about realizing the living building. Proc. 1st Int. Conf. Industrialized Intelligent Construction, pp. 221–237, Loughborough University, May 14–16.Google Scholar
Vattam, S., & Goel, A. (2013). Biological solutions for engineering problems: cross-domain textual case-based reasoning in biologically inspired design. Proc. 21st Int. Conf. Case-Based Reasoning, pp. 343–357, Sarasota Springs, NY, July 8–11.Google Scholar
Vattam, S., Helms, M., & Goel, A. (2007). Biologically Inspired Innovation in Engineering Design: A Cognitive Study, Technical Report, GIT-GVU-07-07. Georgia Institute of Technology, Graphics Visualization and Usability Center.Google Scholar
Vincent, J., Bogatyreva, O., Bogatyrev, N., Bowyer, A., & Pahl, A. (2006). Biomimetics: its practice and theory. Journal of the Royal Society Interface 3(9), 471482.Google Scholar
Vincent, J., & Man, D. (2002). Systematic technology transfer from biology to engineering. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 360(1791), 159173.Google Scholar
Vogel, S. (2000). Cat's Paws and Catapults: Mechanical Worlds of Nature and People. New York: Norton.Google Scholar
Yen, J., Helms, M., & Goel, A., Tovey, C., & Weissburg, M. (2014). Adaptive evolution of teaching practices in biologically inspired design. In Biologically Inspired Design: Computational Methods and Tools (Goel, A., McAdams, D., & Stone, R., Eds.). London: Springer.Google Scholar