Despite growing emphasis on ethics within computing curricula, research ethics – particularly involving the use of publicly available data – remains under-emphasized. Many computing students, faculty, and researchers report receiving little formal guidance on how to navigate the ethical complexities of collecting, analyzing, and sharing pervasive data such as public social media content, geolocation traces, or behavioral data from smart devices. To address this critical gap, we will demonstrate the PERVADE Data Ethics Decision Support Tool, a free, browser-based, interactive resource developed by a multi-institutional team of academic researchers as part of the NSF-funded PERVADE (Pervasive Data Ethics for Computational Research) project.

Rather than offering a rigid compliance checklist, the tool guides users through a series of reflective, branching questions concerning consent, identifiability, data collection, analysis, and dissemination. It also offers examples, best practices, and links to external resources, while encouraging ethical reflexivity and dialogue rather than rule-following. Designed for both self-paced learning and classroom use, the tool is well-suited for courses in computing ethics, research methods, and capstone projects.

In this interactive session, we will demonstrate how the tool works using provocative, real-world case studies such as scraping Reddit posts, analyzing dating profile data, or using mobile app traces for public health research. Attendees will engage with the tool themselves and explore how it can be used to prompt ethical reflection, facilitate classroom discussion, and support responsible research practices. We will also share curricular integration strategies and invite audience feedback on adapting the tool for diverse educational settings.