No CrossRef data available.
Article contents
UNDERSTANDING THE CHALLENGES AROUND DESIGN ACTIVITIES THAT INCORPORATE BEHAVIORAL DATA
Published online by Cambridge University Press: 19 June 2023
Abstract
Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Recently, methods and approaches such as Participatory Data Analysis, Data-Enabled Design, and Contextual Inquiry have highlighted how design activities can benefit from behavioral data. This data offers new ways to learn from what people do and how they do it, across time and space. However, behavioral data introduces changes and frictions to design activities and poses several challenges for designers to overcome. In this paper, we conduct two workshops with 18 expert designers, from industry and academia, to understand the nature of these challenges, beyond the technical aspects. We contribute by underlining the challenges and opportunities of incorporating behavioral data into design activities; including a design perspective on data, interacting with participants, and interacting with regulatory bodies. We translate our findings into opportunities for a better alignment between regulatory bodies, designers, and participants. We propose to harness the iterative nature of design activities and embedded it into a process that allows for continuous reflection, reassessment, and review of highly dynamic datasets.
- Type
- Article
- Information
- Creative Commons
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.- Copyright
- The Author(s), 2023. Published by Cambridge University Press
References
Bogers, S., Frens, J., van Kollenburg, J., Deckers, E. and Hummels, C. (2016), “Connected Baby Bottle”, in: Proceedings of the 2016 ACM Conference on Designing Interactive Systems, ACM, New York, NY, USA, pp. 301–311, http://doi.org/10.1145/2901790.2901855. https://dl.acm.org/doi/10.1145/2901790.2901855CrossRefGoogle Scholar
Bornakke, T. and Due, B.L. (2018), “Big-Thick Blending: A method for mixing analytical insights from big and thick data sources”, Big Data and Society, Vol. 5 No. 1, pp. 1–16, http://doi.org/10.1177/2053951718765026.CrossRefGoogle Scholar
Bourgeois, J., Van Der Linden, J., Kortuem, G., Price, B.A. and Rimmer, C. (2014), “Using participatory data analysis to understand social constraints and opportunities of electricity demand-shifting”, in: ICTfor Sus- tainability 2014, ICT4S 2014, Atlantis Press, Stockholm, Sweden, pp. 392–401, http://doi.org/10.2991/ict4s-14.2014.49.Google Scholar
Braun, V. and Clarke, V. (2013), Successful Qualitative Research. A Practical Guide for Beginners, SAGE Publications Ltd, London.Google Scholar
Briard, T., Jean, C., Aoussat, A., Veron, P., Le Cardinal, J. and Wartzack, S. (2021), “Data-driven design challenges in the early stages of the product development process”, Proceedings of the Design Society, Vol. 1 No. AUGUST, pp. 851–860, http://doi.org/10.1017/pds.2021.85.CrossRefGoogle Scholar
Cila, N., Smit, I., Giaccardi, E. and Krose, B. (2017), “Products as agents: Metaphors for designing the products of the IoT age”, in: Conference on Human Factors in Computing Systems - Proceedings, Vol. 2017- May, Association for Computing Machinery, Denver, USA, pp. 448–459, http://doi.org/10.1145/3025453.3025797.CrossRefGoogle Scholar
Goodman, E. (2014), “Design and ethics in the era of big data”, Interactions, Vol. 21 No. 3, pp. 22–24, http://doi.org/10.1145/2598902.CrossRefGoogle Scholar
Gorkovenko, K., Burnett, D.J., Thorp, J., Richards, D. and Murray-Rust, D. (2019), “Supporting Real-Time Contextual Inquiry Through Sensor Data Supporting Real-Time Contextual Inquiry Through Sensor Data”, in: Ethnographic Praxis in Industry Conference Proceedings, Edinburgh, UK, pp. 1–29.Google Scholar
Gorkovenko, K., Burnett, D.J., Thorp, J.K., Richards, D. and Murray-Rust, D. (2020), “Exploring the Future of Data-Driven Product Design”, in: Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, New York, NY, USA, pp. 1–14, http://doi.org/10.1145/3313831.3376560.CrossRefGoogle Scholar
Jung, J., Kleinsmann, M. and Snelders, D. (2019), “Reviewing design movement towards the collective computing era: How will future design activities differ from those in current and past eras of modern computing?”, in: Moultrie, J. and Shaw, A. (Editors), International Association of Societies of Design Research Conference 2019, September, IASDR 2019 Research Papers, Manchester, United Kingdom, pp. 1–16. URL: https://iasdr2019.org/uploads/files/Proceedings/ch-f-1141-Jun-J.pdfGoogle Scholar
Jung, Y.W., Lim, Y.K. and Kim, M.S. (2017), “Possibilities and limitations of online document tools for design collaboration: The case of Google Docs”, in: Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW, Association for Computing Machinery, New York, New York, USA, pp. 1096–1108, http://doi.org/10.1145/2998181.2998297.CrossRefGoogle Scholar
Koepsell, D., Brinkman, W.P. and Pont, S. (2015), “Human Participants in Engineering Research: Notes from a Fledgling Ethics Committee”, Science and Engineering Ethics, Vol. 21 No. 4, pp. 1033–1048, http://doi.org/10.1007/s11948-014-9568-2. http://link.springer.com/10.1007/s11948-014-9568-2CrossRefGoogle Scholar
Lu, J., Gomez Ortega, A., Gongalves, M. and Bourgeois, J. (2021), “the Impact of Data on the Role of Designers and Their Process”, Proceedings of the Design Society, Vol. 1 No. August, pp. 3021–3030, http://doi.org/10.1017/pds.2021.563.CrossRefGoogle Scholar
Munteanu, C., Molyneaux, H., Moncur, W., Romero, M., O'Donnell, S. and Vines, J. (2015), “Situational ethics: Re-thinking approaches to formal ethics requirements for human-computer interaction”, Conference on Human Factors in Computing Systems - Proceedings, Vol. 2015-April, pp. 105–114, http://doi.org/10.1145/2702123.2702481.CrossRefGoogle Scholar
Sanders, E. and Stappers, P. (2008), “Co-creation and the new landscapes of design”, CoDesign, Vol. 4 No. 1, pp. 5–18, http://doi.org/10.1080/15710880701875068.CrossRefGoogle Scholar
Speed, C. and Oberlander, J. (2016), “Designing from, with and by Data: Introducing the ablative framework”, in: Proceedings of DRS 2016 International Conference: Future–Focused Thinking, Design Research Society, Brighton, UK, pp. 2991–3004, http://doi.org/10.21606/drs.2016.433.CrossRefGoogle Scholar
Steen, M. (2015), “Upon Opening the Black Box and Finding It Full: Exploring the Ethics in Design Practices”, Science Technology and Human Values, Vol. 40 No. 3, pp. 389–420, http://doi.org/10.1177/0162243914547645.CrossRefGoogle Scholar
Tolmie, P., Crabtree, A., Rodden, T., Colley, J. and Luger, E. (2016), “"This has to be the cats" - Personal Data Legibility in Networked Sensing Systems”, in: Proceedings of the 19th ACM Conference on Computer- Supported Cooperative Work & Social Computing, CSCW '16, ACM, New York, NY, USA, pp. 491–502, http://doi.org/10.1145/2818048.2819992. https://dl.acm.org/doi/10.1145/2818048.2819992CrossRefGoogle Scholar
Vines, J., Clarke, R., Wright, P., McCarthy, J. and Oliver, P. (2013), “Configuring Participation: On How We Involve People in Design”, in: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI '13, Association for Computing Machinery, New York, NY, USA, p. 429–438, http://doi.org/10.1145/2470654.2470716.CrossRefGoogle Scholar
Whittle, J. (2014), “How much participation is enough? A comparison of six participatory design projects in terms of outcomes”, ACM International Conference Proceeding Series, Vol. 1, pp. 121–130, http://doi.org/10.1145/2661435.2661445.CrossRefGoogle Scholar
You have
Access
Open access