TY - GEN
T1 - SIG on Data as Human-Centered Design Material
AU - Gomez Ortega, A.
AU - van Kollenburg, Janne
AU - Shen, Yvette
AU - Murray-Rust, D.S.
AU - Nedić, Dajana
AU - Jimenez Garcia, Juan
AU - Meijer, Wo
AU - Kumar Chaudhary, Pranshu
AU - Bourgeois, J.
N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
PY - 2022
Y1 - 2022
N2 - Designers and HCI researchers from industry and academia have been exploring the opportunities that emerge from incorporating behavioral data into the design process. For this, designers employ and combine data from multiple sources, multiple scales, and types to obtain valuable insights that inform and support design decisions. This combination unfolds through interdisciplinary collaborations, enabled by various methods and approaches, including participatory data analysis, sense-making interviews, co-design workshops, and data storytelling. However, due to the personal nature of behavioral data and the open-ended, iterative approach of HumanCentered Design, data-centric design activities clash with current HCI and data science practices. As both industry and academia increasingly use data-centric design processes, we recognize a need to share both examples and experiences to reinforce that most practices (and failed experiences) do not yet emerge solely from the literature. In this Special Interest Group, we aim to provide a space for design, data, and HCI researchers and practitioners to connect, reflect on the current practices, and explore potential approaches to further integrating behavioral data into design activities.
AB - Designers and HCI researchers from industry and academia have been exploring the opportunities that emerge from incorporating behavioral data into the design process. For this, designers employ and combine data from multiple sources, multiple scales, and types to obtain valuable insights that inform and support design decisions. This combination unfolds through interdisciplinary collaborations, enabled by various methods and approaches, including participatory data analysis, sense-making interviews, co-design workshops, and data storytelling. However, due to the personal nature of behavioral data and the open-ended, iterative approach of HumanCentered Design, data-centric design activities clash with current HCI and data science practices. As both industry and academia increasingly use data-centric design processes, we recognize a need to share both examples and experiences to reinforce that most practices (and failed experiences) do not yet emerge solely from the literature. In this Special Interest Group, we aim to provide a space for design, data, and HCI researchers and practitioners to connect, reflect on the current practices, and explore potential approaches to further integrating behavioral data into design activities.
KW - Human-Centered Design
KW - Data-Centric Design
KW - Participatory Design
KW - Behavioural Data
UR - http://www.scopus.com/inward/record.url?scp=85129697772&partnerID=8YFLogxK
U2 - 10.1145/3491101.3516403
DO - 10.1145/3491101.3516403
M3 - Conference contribution
SN - 978-1-4503-9156-6
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 1
EP - 4
BT - CHI 2022 - Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
PB - ACM
CY - New Orleans LA USA
T2 - 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022
Y2 - 30 April 2022 through 5 May 2022
ER -