Perceptual User Interfaces Logo
University of Stuttgart Logo

User Interface Dataset Collection

Dataset image

Description: Data-driven models help user interface (UI) designers understand best practices and trends, and can be used to make predictions about design performance and support the creation of adaptive UIs. Current works explored mobile UIs such as RICO, which was collected via a system that combined crowdsourcing and automation to scalably mine design and interaction data from Android apps at runtime. However, there is no available dataset for desktop UIs. This research gap is waiting for you to fill.

Goal: Following prior works that collected datasets of mobile user interfaces [1,2], design and conduct the study to collect and annotate desktop user interfaces.

Supervisor: Guanhua Zhang

Distribution: 20% Literature, 60% Data collection and annotation, 20% Analysis and discussion

Requirements: Strong programming skills, prefarrably having experience in data mining.


[1] Biplab Deka, Zifeng Huang, Chad Franzen, Joshua Hibschman, Daniel Afergan, Yang Li, Jeffrey Nichols and Ranjitha Kumar. 2017. Rico: A Mobile App Dataset for Building Data-Driven Design Applications. In Proceedings of the 30th Annual Symposium on User Interface Software and Technology (UIST '17).

[2] Biplab Deka, Zifeng Huang, and Ranjitha Kumar. 2016. ERICA: Interaction Mining Mobile Apps. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16).