Abstract
Understanding operator practices in high-tech environments is critical, not only for improving product and workflow, but also as a design challenge. While these environments collect wealth of data, it is insufficient to understand the practice of operators. We present a research prototype that enhances engine data with operator movement data to facilitate sensemaking of operator practices. Through a transdisciplinary sensemaking session with R&D professionals, we investigated how experts perceive the prototype to make sense of the combined data. Analysis was grounded on Data/Frame Theory of Sensemaking to suggest implications on data, design, and expert sensemaking process. Results show that experts were initially fixated on resolving the consistency of the data prior exploring behavioral connections. This industrial case reveals key barriers of expert sensemaking with multimodal data, contributes practical insights for designing data and visualization of the prototype, and conceptualizes roles of intelligent systems within the sensemaking process and tools.
Keywords
Transdisciplinary sensemaking; Intelligent systems; Production printing; Multimodal data
DOI
https://doi.org/10.21606/iasdr.2025.1037
Citation
Yahya, A., de Jong, F., Chen, L.,and Funk, M.(2025) Making Sense of Transdisciplinary Sensemaking of Behavioral and Engine Data in Production Print, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.1037
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 10 - Design Practices & Impacts
Making Sense of Transdisciplinary Sensemaking of Behavioral and Engine Data in Production Print
Understanding operator practices in high-tech environments is critical, not only for improving product and workflow, but also as a design challenge. While these environments collect wealth of data, it is insufficient to understand the practice of operators. We present a research prototype that enhances engine data with operator movement data to facilitate sensemaking of operator practices. Through a transdisciplinary sensemaking session with R&D professionals, we investigated how experts perceive the prototype to make sense of the combined data. Analysis was grounded on Data/Frame Theory of Sensemaking to suggest implications on data, design, and expert sensemaking process. Results show that experts were initially fixated on resolving the consistency of the data prior exploring behavioral connections. This industrial case reveals key barriers of expert sensemaking with multimodal data, contributes practical insights for designing data and visualization of the prototype, and conceptualizes roles of intelligent systems within the sensemaking process and tools.