The increasing availability of large-scale datasets such as sensor data or social media data and increasingly accessible data science tools create unique opportunities for design. However, the relationship between data science practices and design methods is still underdeveloped. In this paper, we propose that data exploration activities can be effectively embedded within a broader design inquiry framework and define a new design method, coined Data Exploration for Design, to support methodical designerly data exploration. The design method addresses the novice’s learning curve and supporting developing a data exploration inquiry mindset with procedures and curated tools. The empirical evaluation highlights support for producing exploration outcomes that are worth the additional technical effort. We close the paper by positioning the findings in design methodology literature and motivating data exploration principles for design inquiry. The principles urge to acknowledge biases in data collection, spending time with the data, using visualizations as a means-to-an-end, and designers being part of the data collection.
|Tidsskrift||Interaction Design and Architecture(s)|
|Udgave nummer||Summer 2020|
|Status||Udgivet - 2020|