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The Triple B: Big Data, Biotechnology, and Biomimicry

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Biotechnology and Future Cities

Abstract

As the drive for data-driven solutions is supported by increased funding in Research and Development (R&D) in various industries, the role of technology to generate datasets in various urban quarters is being sought, furthering the prospect of smart cities and their applications. However, data is also being driven in biological fields leading to new ways to understand how organisms function and how those react to specific and unpredictable environments, rendering us with new insights into how resilience works. This can further the prospect of biomimicry and lead to enhanced sustainability and resilience in cities, as supported by the proponent of the concept.

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References

  • Adesina, O., Anzai, I. A., Avalos, J. L., & Barstow, B. (2017). Embracing Biological solutions to the sustainable energy challenge. Chem, 2(1), 20–51.

    Article  Google Scholar 

  • Ali, U. (2017, April 26). Could biomimicry revolutionise renewable energy? Retrieved from https://www.power-technology.com/features/featurecould-biomimicry-revolutionise-renewable-energy-5796192/.

  • Allam, M. Z. (2018). Redefining the smart city: Culture, metabolism and governance. Case Study of Port Louis, Mauritius (PhD thesis). Curtin University, Perth, Australia. Retrieved from https://espace.curtin.edu.au/handle/20.500.11937/70707.

  • Allam, Z. (2017). A theoretical application of the Extended Metabolism Model in Port Louis in a bid to promote urban sustainability. Paper presented at the 2nd International Conference on Energy, Environment and Climate Change (ICEECC 2017), Mauritius.

    Google Scholar 

  • Allam, Z. (2018). Contextualising the smart city for sustainability and inclusivity. New Design Ideas, 2(2), 124–127.

    Google Scholar 

  • Allam, Z. (2019). The emergence of anti-privacy and control at the nexus between the concepts of safe city and smart city. Smart Cities, 2(1), 96–105.

    Article  Google Scholar 

  • Allam, Z. (2020a). Data as the new driving gears of urbanization. In Z. Allam (Ed.), Cities and the digital revolution: Aligning technology and humanity (pp. 1–29). Cham: Springer.

    Chapter  Google Scholar 

  • Allam, Z. (2020b). Digital urban networks and social media. In Z. Allam (Ed.), Cities and the digital revolution: Aligning technology and humanity (pp. 61–83). Cham: Springer.

    Chapter  Google Scholar 

  • Allam, Z. (2020c). Privatization and privacy in the digital city. In Z. Allam (Ed.), Cities and the digital revolution: Aligning technology and humanity (pp. 85–106). Cham: Springer.

    Chapter  Google Scholar 

  • Allam, Z. (2020d). Theology, sustainability and big data. In Z. Allam (Ed.), Theology and urban sustainability (pp. 53–67). Cham: Springer.

    Chapter  Google Scholar 

  • Allam, Z. (2020e). Urban Chaos and the AI Messiah. In Z. Allam (Ed.), Cities and the digital revolution: Aligning technology and humanity (pp. 31–60). Cham: Springer.

    Chapter  Google Scholar 

  • Allam, Z., & Dhunny, Z. A. (2019). On big data, artificial intelligence and smart cities. Cities, 89, 80–91.

    Article  Google Scholar 

  • Allam, Z., & Jones, S. D. (2019). The potential of blockchain within air rights development as a prevention measure against urban sprawl. Urban Science, 3(1), 38.

    Google Scholar 

  • Allam, Z., & Newman, P. (2018). Redefining the smart city: Culture, metabolism and governance. Smart Cities, 1, 4–25.

    Article  Google Scholar 

  • Allam, Z., Tegally, H., & Thondoo, M. (2019). Redefining the use of big data in urban health for increased liveability in smart cities. Smart Cities, 2(2), 259–268.

    Article  Google Scholar 

  • Aron, J. (2015, February 11). Glassed-in DNA makes the ultimate time capsule. Retrieved from https://www.newscientist.com/article/mg22530084-300-glassed-in-dna-makes-the-ultimate-time-capsule/#.VONYR1PF_Md.

  • Aslam, B., Basit, M., Nisar, M. A., Khurshid, M., & Rasool, M. H. (2017). Proteomics: Technologies and their applications. Journal of Chromatographic Science, 55(2), 182–196.

    Article  Google Scholar 

  • Aziz, M. S., & El sherif, A. Y. (2016). Biomimicry as an approach for bio-inspired structure with the aid of computation. Alexandria Engineering Journal, 55(1), 707–714.

    Google Scholar 

  • Bassoo, V., Ramnarain-Seetohul, V., Hurbungs, V., Fowdur, T. P., & Beeharry, Y. (2018). Big data analytics for smart cities. In N. Dey, A. Hassanien, C. Bhatt, & S. Stapathy (Eds.), Internet of things and big data analytics toward next-generation intelligence (Vol. 30). Studies in Big Data. Cham: Springer.

    Google Scholar 

  • Bayat, A. (2002). Science, medicine, and the future: Bioinformatics. BMJ (Clinical Research Ed.), 324(7344), 1018–1022.

    Article  Google Scholar 

  • Benyus, J. M. (1997). Biomimicry: Innovation inspired by nature. New York, NY: William Morrow and Company.

    Google Scholar 

  • Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences of the United States of America, 104(17), 7301–7306.

    Article  Google Scholar 

  • Buckingham, L., & Hogan, J. M. (2014). Computational science for undergraduate biologists via QUT.Bio.Excel. Procedia Computer Science, 29, 1403–1412.

    Article  Google Scholar 

  • Cheng, S., Li, X., Zhihan, L. V., Song, H., Jia, T., & Lu, N. (2018). Data analytics of urban fabric metrics for smart cities. Future Generation Computer Systems (in press).

    Google Scholar 

  • Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., … Greene, C. S. (2018). Opportunities and obstacles for deep learning in biology and medicine. Journal of the Royal Society, Interface, 15(141), 20170387.

    Google Scholar 

  • Choudhuri, S. (2014). Chapter 4—The beginning of bioinformatics. In S. Choudhuri (Ed.), Bioinformatics for Beginners (pp. 73–76). Oxford: Academic Press.

    Chapter  Google Scholar 

  • Cianchetti, M., Laschi, C., Menciassi, A., & Dario, P. (2018). Biomedical applications of soft robotics. Nature Reviews Materials, 3(6), 143–153.

    Article  Google Scholar 

  • Dabeedooal, J. Y., Dindoyal, V., Allam, Z., & Jones, S. D. (2019). Smart tourism as a pillar for sustainable urban development: An alternate smart city strategy from mauritius. Smart Cities, 2(2), 153–162.

    Google Scholar 

  • De Brevern, A. G., Meyniel, J.-P., Fairhead, C., Neuvéglise, C., & Malpertuy, A. (2015). Trends in IT innovation to build a next generation bioinformatics solution to manage and analyse biological big data produced by NGS technologies. BioMed Research International, 2015, 15.

    Article  Google Scholar 

  • EEA. (2019). Paving the way for a circular economy: Insights on status and potentials. Luxembourg. Retrieved from https://circulareconomy.europa.eu/platform/sites/default/files/th-al-19-014-en-n.pdf.

  • Garrod, R. P., Harris, L. G., Schofield, W. C. E., McGettrick, J., Ward, L. J., Teare, D. O. H., & Badyal, J. P. S. (2007). Mimicking a Stenocara Beetle’s Back for microcondensation using plasmachemical patterned superhydrophobic-superhydrophilic surfaces. Langmuir, 23(2), 689–693.

    Google Scholar 

  • Gupta, S., Mateu, J., Degbelo, A., & Pebesma, E. (2018). Quality of life, big data and the power of statistics. Statistics & Probability Letters, 136, 101–104.

    Article  Google Scholar 

  • Hayes, S., Desha, C., & Gibbs, M. (2019). Findings of case-study analysis: System-level biomimicry in built-environment design. Biomimetics, 4(4), 73.

    Article  Google Scholar 

  • Imani, M., Donn, M., & Balador, Z. (2019). Bio-inspired materials: Contribution of biology to energy efficiency of buildings. In L. M. T. Martínez, O. V. Kharissova, & B. I. Kharisov (Eds.), Handbook of ecomaterials (pp. 2213–2236). Cham: Springer.

    Chapter  Google Scholar 

  • Johnson, C. H., Ivanisevic, J., & Siuzdak, G. (2016). Metabolomics: Beyond biomarkers and towards mechanisms. Nature Reviews Molecular Cell Biology, 17(7), 451–459.

    Article  Google Scholar 

  • Kennedy, E. B. (2017). Biomimicry: Design by analogy to biology. Research-Technology Management, 60(6), 51–56.

    Article  Google Scholar 

  • Kiser, B. (2016). Circular economy: Getting the circulation going. Nature, 531, 443.

    Article  Google Scholar 

  • Leipold, S., & Petit-Boix, A. (2018). The circular economy and the bio-based sector—Perspectives of European and German stakeholders. Journal of Cleaner Production, 201, 1125–1137.

    Article  Google Scholar 

  • Lesk, A. M. (2007). Introduction to genomics. Oxford: Oxford University Press.

    Google Scholar 

  • Li, S.-Y., Ng, I. S., Chen, P. T., Chiang, C.-J., & Chao, Y.-P. (2018). Biorefining of protein waste for production of sustainable fuels and chemicals. Biotechnology for Biofuels, 11(1), 256.

    Article  Google Scholar 

  • Liebler, D. (2001). Introduction to proteomics: Tools for the new biology. Totowa, NJ: Humana Press.

    Book  Google Scholar 

  • Liu, X., & Locasale, J. W. (2017). Metabolomics: A primer. Trends in Biochemical Sciences, 42(4), 274–284.

    Article  Google Scholar 

  • Martín-Palma, R. J., & Lakhtakia, A. (2013). Engineered biomimicry for harvesting solar energy: A bird’s eye view. International Journal of Smart and Nano Materials, 4(2), 83–90.

    Article  Google Scholar 

  • Masterson, A. (2017, March 7). One day, more than your genes will be stored in DNA. Retrieved from https://cosmosmagazine.com/technology/one-day-more-than-your-genes-will-be-stored-in-dna.

  • Merelli, I., Pérez-Sánchez, H., Gesing, S., & D’Agostino, D. (2014). Managing, analysing, and integrating big data in medical bioinformatics: Open problems and future perspectives. BioMed Research International, 2014, 13.

    Google Scholar 

  • Mielenz, J. R. (2011). Biofuels from protein. Nature Biotechnology, 29(4), 327–328.

    Article  Google Scholar 

  • Mohs, R. C., & Greig, N. H. (2017). Drug discovery and development: Role of basic biological research. Alzheimer’s & Dementia (New York, N.Y.), 3(4), 651–657.

    Google Scholar 

  • Mutowo, P., Bento, A. P., Dedman, N., Gaulton, A., Hersey, A., Lomax, J., & Overington, J. P. (2016). A drug target slim: using gene ontology and gene ontology annotations to navigate protein-ligand target space in ChEMBL. Journal of Biomed Semantics, 7(1), 59.

    Google Scholar 

  • Oliveira, A. L. (2019). Biotechnology. Big Data and Artificial Intelligence., 14(8), 1800613.

    Google Scholar 

  • Panda, D., Molla, K. A., Baig, M. J., Swain, A., Behera, D., & Dash, M. (2018). DNA as a digital information storage device: Hope or hype? 3 Biotech, 8(5), 239.

    Google Scholar 

  • Pedersen Zari, M. (2010). Biomimetic design for climate change adaptation and mitigation. Architectural Science Review, 53(2), 172–183.

    Google Scholar 

  • Radwan, G. A. N., & Osama, N. (2016). Biomimicry, an approach, for energy efficient building skin design. Procedia Environmental Sciences, 34, 178–189.

    Article  Google Scholar 

  • Saravanan, V. (2018). Big data in massive parallel processing: A multi-core processors perspective. Buffalo, NY: State University of New York.

    Book  Google Scholar 

  • Silva, B. N., Khan, M., & Han, K. (2018). Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities. Sustainable Cities and Society, 38, 697–713.

    Article  Google Scholar 

  • Stojanovic, N. (2007). Computational genomics: Current methods. Norfolk, UK: Horizon Bioscience.

    Google Scholar 

  • Suhai, S. (2000). Genomics and proteomics: Functional and computational aspects. In Proceedings of the International Symposium on Genomics and Proteomics: Functional and Computational Aspects, Held October 4–7, 1998, in Heidelberg, Germany, Springer US.

    Google Scholar 

  • Tate, W. L., Bals, L., Bals, C., & Foerstl, K. (2019). Seeing the forest and not the trees: Learning from nature’s circular economy. Resources, Conservation and Recycling, 149, 115–129.

    Article  Google Scholar 

  • Taylor Buck, N. (2015). The art of imitating life: The potential contribution of biomimicry in shaping the future of our cities. Environment and Planning B: Urban Analytics and City Science, 44(1), 120–140.

    Google Scholar 

  • Thakuriah, P., Tilahun, N., & Zellner, M. (2017). Big data and urban informatics: Innovations and challenges to urban planning and knowledge discovery. In Seeing cities through big data: Research, methods and applications in urban informatics (pp. 11–48). Cham: Springer.

    Google Scholar 

  • The World Bank. (2016). World Development Report: Digital Dividend. Retrieved from Washington, DC: http://documents.worldbank.org/curated/en/896971468194972881/310436360_20160263021502/additional/102725-PUB-Replacement-PUBLIC.pdf.

  • Turner, S. (2008, May 14–16). Beyond biomimicry: What termites can tell us about realizing the living building. Paper presented at the Proceedings of 1st International Conference on Industrialized, Intelligent Construction, Leicester, UK.

    Google Scholar 

  • U.S. National Library of Medicine. (2019, November 12). Genetics Home Reference. Retrieved from https://ghr.nlm.nih.gov/primer/basics/gene.

  • Wise, C., Pawlyn, M., & Braungart, M. (2013). Eco-engineering: Living in a materials world. Nature, 494(7436), 172–175.

    Article  Google Scholar 

  • Yang, J. (2019). Cloud computing for storing and analyzing petabytes of genomic data. Journal of Industrial Information Integration, 15, 50–57.

    Article  Google Scholar 

  • Yun, M. J., Sim, Y. H., Cha, S. I., & Lee, D. Y. (2019). Leaf Anatomy and 3-D Structure Mimic to Solar Cells with light trapping and 3-D arrayed submodule for Enhanced Electricity Production. Scientific Reports, 9(1), 10273.

    Article  Google Scholar 

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Authors and Affiliations

  1. Live+Smart Research Lab, School of Architecture & Built Environment, Deakin University, Geelong, VIC, Australia

    Zaheer Allam

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  1. Zaheer Allam
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Allam, Z. (2020). The Triple B: Big Data, Biotechnology, and Biomimicry. In: Biotechnology and Future Cities. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-43815-9_2

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  • DOI: https://doi.org/10.1007/978-3-030-43815-9_2

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  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-030-43814-2

  • Online ISBN: 978-3-030-43815-9

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