Conference Agenda

There is a significant knowledge gap concerning the female body in sports partly due to research in sports physiology narrowly focusing on male athletes. It means hormonal changes around the menstrual cycle have been disregarded from critical considerations and recommendations about training and planning. Similarly, digital tracking technologies, which play an increasingly important role in sports, often overlook the menstrual cycle or invite athletes to reduce a situated and embodied experience into a discrete data point. In this paper, we use intimate data as material to design tracking practices for menstruating athletes. Specifically, we use the principles of Data Feminism of examining and challenging power to (1) underline current issues and practices of menstruating athletes through a large-scale survey, and (2) propose an alternative tracking solution through a participatory co-creation session with athletes and their intimate data. We reflect on the process of designing with and for intimate data.

With rapid advancements in information technology, data has emerged as a crucial material that broadens the scope of design. Product designers urgently need to develop a comprehensive understanding of the role of data in design and how data can effectively shape and guide the creative design process. In this study, we identified different types of data in design by using bibliometric analysis and conducted semi-structured interviews using qualitative analysis with 12 experienced smart product designers, aiming to understand how product designers in various fields practically apply data in their design process. We have developed a taxonomy to leverage data in design, clarifying its impact and illuminating common challenges in data-driven decision-making throughout the design stages. This study aims to promote a shift toward a data-driven design paradigm, highlighted by a nuanced understanding of data's role in the design process.

The Uncanny Valley (UV) is a vital part of design research because it directly affects users' emotional responses and acceptance of anthropomorphic technical products. Traditional research relies on curve fitting to measure UV effects. However, these works often overlook the impact of data quality including scale and distribution on the accuracy and stability of fitting results. This study places a strong emphasis on the mediating role of data in UV, revisiting UV using a dataset comprising 1,000 static facial images of humanoid entities, evenly spanning the entire human likeness spectrum. The results reveal a different UV shape than Mori's original curve, especially for humanoid entities with moderate to low human likeness. Additionally, this paper explores how data quality affects UV effect curve fitting results by using sampling technologies to construct subsets. We highlight the importance of data-driven design research and provide a new perspective on avoiding and alleviating UV effects.

The concept of smart cities encompasses not just technological advancement but also citizen well-being and sustainability. However, the increasing data availability often leads to a technology-centric focus, neglecting integration with citizen participation. The design could bridge this gap by facilitating data translation and accessibility. Therefore, this study aimed to test a process for co-analyzing mixed data through collaborative activities and data visualization tools, immersing participants in the impact of weather on urban mobility. The data sources included quantitative data from the transport providers, social networks, and qualitative data from a diary study. The process revealed significant potential, with participants reporting ease in analyzing substantial data volumes and finding the proposal innovative and enjoyable. Future steps may involve enhancing interactive visualizations and automating data-narrative integration for broader adaptability. The contribution of this study lies in a co-design process with data storytelling tools, for any project with a large volume of information.

This paper explores the role of intuition in the adoption of data-driven ap-proaches in design within the broad domain of user experience design. To better understand the relationship between intuition and data-driven approaches, we conducted a mixed methods study entailing a qualitative exploration (n=10) of the challenges and opportunities professional designers face when working with data-driven methods, such as potential creativity constraints, knowledge gaps, tool deficiencies, collaboration difficulties, and ethical concerns. We then question whether these challenges stem from the intuitive nature of design work and the types of individuals it attracts and investigate this question using a quantita-tive online study (n=110). Contributions include a review of current practices in data-driven design and an analysis of how predispositions for intuition predict the use of data-driven approaches. This research could provide insights into why designers may resist data-driven methods.