Abstract
This chapter reports on the development of a general framework for describing complex design which can be applied in different design contexts to identify commonalities and discrepancies in the perspectives that people adopt. The framework was built from interviews with practitioners from the complex design field of Synthetic Biology. However, we demonstrate its broad relevance by applying it to describe the sociotechnical example of “designing out crime.” The framework consists of three dimensions, each reflecting a different aspect of complex design, as described by the study’s participants. The first of these dimensions is the characterization of system complexity, the second is the design objective identified with respect to this complexity, and the third is the design approach applied to realize this objective. Because of its domain-neutrality, the framework could assist designers working in different complex design contexts (e.g. swarm robotics, policy formation, and healthcare), to identify when they are addressing design problems that share fundamental similarities. The framework could also assist different designers working on the same complex design challenge to identify discrepancies in their complex design practices or problem framings. In the same way that complex design challenges are never truly “solved,” the framework is not presented here as “finished,” but as an empirically grounded work-in-progress. Studies of other complex design fields would further develop the framework, better supporting cross-domain knowledge-sharing in complex design activities.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
We use the terms “complex design challenge” and “complex design problem” interchangeably but tend to use “complex design problem” when referring to the problem itself (e.g. reducing crime in a region of the city) and “challenge” when referring to the problem as something that needs to be addressed for a broader set of objectives (e.g. reducing crime for social improvement).
- 2.
One coder had a background in computer science and complexity science; one coder had a background in mechanical engineering and engineering design. We report on the backgrounds to increase the transparency of the methods used. Qualitative inductive methods are interpretive by nature, and other analysts (from the same or other backgrounds) might arrive at different interpretations.
References
Abbott, R. (2006). Complex systems + systems engineering = complex systems engineering. Conference on Systems Engineering Research, Los Angeles, April 6–9.
Agapakis, C. M. (2014). Designing synthetic biology. ACS Synthetic Biology, 3(3), 121–128.
Anderson, J., Strelkowa, N., Stan, G.-B., Douglas, T., Savulescu, J., Barahona, M., et al. (2012). Engineering and ethical perspectives in synthetic biology. EMBO Reports, 13(7), 584–590.
Andrianantoandro, E., Basu, S., Karig, D. K., & Weiss, R. (2006). Synthetic biology: New engineering rules for an emerging discipline. Molecular Systems Biology, 2(1), 2006.28.
Benner, S. A., & Sismour, M. (2005). Synthetic biology. Nature Reviews Genetics, 6(7), 533–543.
Bobrow, D. B. (2006). Policy design: Ubiquitous, necessary, and difficult. In B. G. Peters & J. Pierre (Eds.), Handbook of public policy (pp. 75–96). Los Angeles: Sage.
Braun, C., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Breakwell, G. M. (2006). Interviewing methods. In G. M. Breakwell, J. A. Smith, & D. B. Wright (Eds.), Research methods in psychology (pp. 232–253). Los Angeles: Sage.
Buchli, J., & Santini, C. C. (2005). Complexity engineering: Harnessing emergent phenomena as opportunities for engineering. Reports of the Santa Fe Institute’s Complex Systems Summer School 2005
Chen, C.-C., & Crilly, N. (2014a). Modularity, redundancy and degeneracy: Cross-domain perspectives on key design principles. Paper presented at the 8th Annual IEEE Systems Conference, 546–553, Ottawa, March 31-April 3.
Chen, C.-C., & Crilly, N. (2014b). Towards a framework of design principles: Classifying system features, behaviours and types. Paper presented at the Design Research Society Conference 2014, Umea, Sweden, June 16–19.
Chen, C.-C., & Crilly, N. (2016a). Describing complex design practices with a cross-domain framework: Learning from synthetic biology and Swarm Robotics. Research in Engineering Design, 27(3), 291–305.
Chen, C.-C., & Crilly, N. (2016b). From modularity to emergence: A primer on the design and science of complex systems. Technical Report CUED/C-EDC/TR.166. University of Cambridge, Department of Engineering. ISSN 0963-5432. https://doi.org/10.17863/CAM.4503
Clarkson, P. J., Buckle, P., Coleman, R., Stubbs, D., Ward, J., Jarrett, J., et al. (2004). Design for patient safety: A review of the effectiveness of design in the UK health service. Journal of Engineering Design, 15(2), 123–140.
Crowe, T. D. (2000). Crime prevention through environmental design. Oxford, UK: Butterworth-Heinemann.
de Weck, O. L., Roos, D., & Magee, C. L. (2011). Engineering systems: Meeting human needs in a complex technological world. Cambridge, MA: MIT Press.
Duarte, O. C., Lulham, R., & Kaldor, L. (2011). Co-designing out crime. CoDesign 7(3–4): Special issue on Socially Responsive Design.
Endy, D. (2005). Foundations for engineering biology. Nature, 438(7067), 449–453.
Forrest, S., Balthrop, J., Glickman, M., & Ackley, D. (2005). Computation in the wild. In E. Jen (Ed.), Robust design: A repertoire of biological, ecological, and engineering case studies (pp. 207–230). Oxford: Oxford University Press.
Frei, R., & Serugendo, G. D. M. (2011a). Concepts in complexity engineering. International Journal of Bio-Inspired Computation, 3(2), 123–139.
Frei, R., & Serugendo, G. D. M. (2011b). Advances in complexity engineering. International Journal of Bio-inspired Computation, 3(4), 199–212.
Fu, P. (2006). A perspective of synthetic biology: Assembling building blocks for novel functions. Biotechnology Journal, 1(6), 690–699.
Gao, L. (2000). On inferring autonomous system relationships in the Internet. IEEE/ACM Transactions on Networking, 9(6), 733–745.
Jeffrey, C. R. (1977). Crime prevention through environmental design. Los Angeles: Sage.
Jones, P. (2014). Systemic design principles for complex social systems. In G. Metcalf (Ed.), Social Systems and Design (pp. 91–128). Tokyo: Springer.
Knight, T. F. (2005). Engineering novel life. Molecular Systems Biology, 1(1), 0020.
Kwok, R. (2010). Five hard truths for synthetic biology. Nature, 463(7279), 288–289.
Maher, M. L., & Poon, J. (1994). Modelling design exploration as co-evolution. Microcomputers in Civil Engineering on Evolutionary Systems in Design, 11(3), 195–210.
Nair, G., Ditton, J., & Phillips, S. (1993). Environmental improvements and the fear of crime. The sad case of the ‘Pond’ area in Glasgow. The British Journal of Criminology, 33(4), 555–561.
Nature. (2014). Beyond divisions: Building the future of synthetic biology. Nature, 509(7499), 134–254.
Purncik, P. M., & Weiss, R. (2009). The second wave of synthetic biology: From modules to systems. Nature Reviews in Molecular Cell Biology, 10(6), 410–422.
Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155–169.
Sevaldson, B. (2011). Gigamapping: Visualization for complexity and systems thinking in design. Helsinki, Finland: Nordic Design Research Conference.
Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2), 237–246.
Tolk, A. (2012). Engineering principles of compact modeling and distributed simulation. Hoboken, NJ: Wiley.
Vinnakota, T. R., & Narayana, M. (2014). Integration of design thinking with strategy and innovation in an enterprise context. Paper presented at the IEEE International Conference on Management of Innovation and Technology, Singapore, 23–25 September.
Visser, W. (2004). Dynamic aspects of design cognition. Research Report RR-5144. HAL Id: inria-00071439.
Wiltschnig, S., Christensen, B. T., & Ball, L. J. (2013). Collaborative problem-solution co-evolution in creative design. Design Studies, 34(5), 515–542.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Japan KK, part of Springer Nature
About this chapter
Cite this chapter
Chen, CC., Crilly, N. (2018). A Framework for Complex Design: Lessons from Synthetic Biology. In: Jones, P., Kijima, K. (eds) Systemic Design. Translational Systems Sciences, vol 8. Springer, Tokyo. https://doi.org/10.1007/978-4-431-55639-8_2
Download citation
DOI: https://doi.org/10.1007/978-4-431-55639-8_2
Published:
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-55638-1
Online ISBN: 978-4-431-55639-8
eBook Packages: Economics and FinanceEconomics and Finance (R0)