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A Framework for Complex Design: Lessons from Synthetic Biology

  • Chih-Chun ChenEmail author
  • Nathan Crilly
Chapter
Part of the Translational Systems Sciences book series (TSS, volume 8)

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.

References

  1. Abbott, R. (2006). Complex systems + systems engineering = complex systems engineering. Conference on Systems Engineering Research, Los Angeles, April 6–9.Google Scholar
  2. Agapakis, C. M. (2014). Designing synthetic biology. ACS Synthetic Biology, 3(3), 121–128.CrossRefGoogle Scholar
  3. 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.CrossRefGoogle Scholar
  4. 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.Google Scholar
  5. Benner, S. A., & Sismour, M. (2005). Synthetic biology. Nature Reviews Genetics, 6(7), 533–543.CrossRefGoogle Scholar
  6. 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.CrossRefGoogle Scholar
  7. Braun, C., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.CrossRefGoogle Scholar
  8. 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.Google Scholar
  9. 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 2005Google Scholar
  10. 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.Google Scholar
  11. 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.Google Scholar
  12. 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.CrossRefGoogle Scholar
  13. 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
  14. 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.CrossRefGoogle Scholar
  15. Crowe, T. D. (2000). Crime prevention through environmental design. Oxford, UK: Butterworth-Heinemann.Google Scholar
  16. de Weck, O. L., Roos, D., & Magee, C. L. (2011). Engineering systems: Meeting human needs in a complex technological world. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
  17. Duarte, O. C., Lulham, R., & Kaldor, L. (2011). Co-designing out crime. CoDesign 7(3–4): Special issue on Socially Responsive Design.Google Scholar
  18. Endy, D. (2005). Foundations for engineering biology. Nature, 438(7067), 449–453.CrossRefGoogle Scholar
  19. 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.Google Scholar
  20. Frei, R., & Serugendo, G. D. M. (2011a). Concepts in complexity engineering. International Journal of Bio-Inspired Computation, 3(2), 123–139.CrossRefGoogle Scholar
  21. Frei, R., & Serugendo, G. D. M. (2011b). Advances in complexity engineering. International Journal of Bio-inspired Computation, 3(4), 199–212.CrossRefGoogle Scholar
  22. Fu, P. (2006). A perspective of synthetic biology: Assembling building blocks for novel functions. Biotechnology Journal, 1(6), 690–699.CrossRefGoogle Scholar
  23. Gao, L. (2000). On inferring autonomous system relationships in the Internet. IEEE/ACM Transactions on Networking, 9(6), 733–745.Google Scholar
  24. Jeffrey, C. R. (1977). Crime prevention through environmental design. Los Angeles: Sage.Google Scholar
  25. Jones, P. (2014). Systemic design principles for complex social systems. In G. Metcalf (Ed.), Social Systems and Design (pp. 91–128). Tokyo: Springer.Google Scholar
  26. Knight, T. F. (2005). Engineering novel life. Molecular Systems Biology, 1(1), 0020.CrossRefGoogle Scholar
  27. Kwok, R. (2010). Five hard truths for synthetic biology. Nature, 463(7279), 288–289.CrossRefGoogle Scholar
  28. 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.CrossRefGoogle Scholar
  29. 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.CrossRefGoogle Scholar
  30. Nature. (2014). Beyond divisions: Building the future of synthetic biology. Nature, 509(7499), 134–254.Google Scholar
  31. 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.Google Scholar
  32. Rittel, H. W. J., & Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155–169.CrossRefGoogle Scholar
  33. Sevaldson, B. (2011). Gigamapping: Visualization for complexity and systems thinking in design. Helsinki, Finland: Nordic Design Research Conference.Google Scholar
  34. Thomas, D. R. (2006). A general inductive approach for analyzing qualitative evaluation data. American Journal of Evaluation, 27(2), 237–246.CrossRefGoogle Scholar
  35. Tolk, A. (2012). Engineering principles of compact modeling and distributed simulation. Hoboken, NJ: Wiley.CrossRefGoogle Scholar
  36. 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.Google Scholar
  37. Visser, W. (2004). Dynamic aspects of design cognition. Research Report RR-5144. HAL Id: inria-00071439.Google Scholar
  38. Wiltschnig, S., Christensen, B. T., & Ball, L. J. (2013). Collaborative problem-solution co-evolution in creative design. Design Studies, 34(5), 515–542.CrossRefGoogle Scholar

Copyright information

© Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of CambridgeCambridgeUK

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