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About The SIG
The Data-Informed Design SIG of the Design Society is set up to provide a forum for identifying, sharing and disseminating how we facilitate the “smart” use of data to produce better design solutions.
The use of data guiding product development and design is nothing new. However, we’re facing the “data tsunami”, and unfettered access to data will not shape future design. Design is ubiquitous; therefore, it’s difficult to see it solely as an outcome of an algorithmic or computational approach. We see the main challenges ahead not in gathering more data (it is naturally happening anyway) but in how we facilitate the “smart” use of data to produce better design solutions.
The two major disruptive trends in the industry - electrification and digitalization will force us to use unorthodox interdisciplinary approaches. The major goals of the SIG are to seek answers to the “How to differentiate and unite Design Quality, Perceived quality, Human-Machine Interaction issues, User Interface Design, Customer Experience, Design Experience, Gamification approach?” These goals reflect industrial needs aligned with the scientific advancements regarding Data-Informed Design (DID).
The Data-Informed Design is different from the Data-Driven Design. For the Data-Informed Design, data is not the main input - designers use data to inform their decisions, but they treat data as the product. In other words, the designers use data as a source of information and other inputs: qualitative, contextual etc.
The SIG aims to perform experiments with various agents and media to understand what methods and types of data collection for the further analysis needed to facilitate the inclusive design. Specifically, we want to address areas of Illumination and Sustainable Materials evaluation via visual cues. The initial phase of the SIG activities will focus on “preparation and understanding” data for the successful development of ML algorithms suitable for industrial use. Today most of these algorithms are broad and general. We aim to advance a communication theory in design addressing informational asymmetries via different channels (visual, haptic, auditory, olfactory - being real, augmented, and virtual).
As we mentioned above, SIG sees data not as an actor (e.g., data-driven) but as a design material, applying a pragmatic approach, and following a long tradition of developing new knowledge by empirical approach and mixing methods, including new and old paradigms. The outcome produced by AI/ML can be a starting point for a designer's creative expression. As a group, we also have established collaborations with the industry addressing a variety of real-world tasks.
Specifically, we want to address these Design Theory topics:
- A theoretical foundation for Data-Informed Design. Areas and practical studies related to perceived quality, design quality, definition and quantification of design attributes.
- Investigate the consequences of data on design activities and processes. How should we change the design methods? Implications at the individual, organizational and managerial levels.
- Contribute to the study and assessment of neuro-physiological differences between divergent and convergent thinking tasks occurring in design processes, eventually analysing differences for data-informed sessions.
- Interface analysis between multi-modal user experience judgements and the transfer in (technical) product requirements with a special focus on perceived material quality (e.g., textiles).
- Investigate the application of shape intuitive perception modelling techniques into automated ML generation/design processes (parametric, generative design, etc.)
- How to differentiate and unite Perceived quality, Human-Machine Interaction issues, User Interface Design, User Experience, Customer Experience, and Gamification approach?
- How can we collect data (granular data collection methods)? What is the right way to use data once we've collected it?
We also want to address industrial needs:
- How to differentiate and define the user experience, good perceived quality, good customer features and physical user experience? How to move towards future mobility with customer focus in mind?
- How can tech innovation be best implemented through design, and how does that generate value for the end consumer?
- What design aspects relate most to value to the customer? What are consumers willing to pay for with respect to design?
- How can organizations best align and function in order to execute product definitions?
- Investigate the relationship of China/Asia vs EU vs North America: optimizing customer user experience.
Our goal is to address specific topics. A data-informed decision-making approach works well with the “Why?” The data-informed design is more relevant when it comes to strategic, fundamental design decisions with a contextual inquiry. Today, the understanding of data's role in examining future design solutions is at a rudimentary stage. There are few theories and even fewer frameworks. Interpreting data into design strategies for human benefit demands data-literate designers, and this type of education is one of the primary goals of the SIG. As a SIG, we naturally see our mission to connect industrial needs with scientific methods.