Data Insights

Hunter Whitney is a human-centered design (HCD) strategist, instructor, and author who brings a distinct UX design perspective to data visualization and analytics. He currently works at eSimplicity as a Principal HCD Strategist. He has advised corporations, start-ups, government agencies, and NGOs to help them achieve their goals through a thoughtful, strategic design approach to digital products and services. He contributed a chapter in the book, “Designing for Emerging Technologies: UX for Genomics, Robotics, and the Internet of Things”. His teaching experience includes being a classroom instructor for the courses - "Design Thinking and UX Strategy" and "Human-Centered Design for Data Visualization" for UC Berkeley Extension. He is also an instructor and curriculum advisor for data visualization and UX design programs with UC Davis on Coursera.

Introduction to the 2nd Edition: From Petabytes to Insights (What’s changed in years after the first edition?)• Retrospective discussions with thought leaders about changes they’ve seen in the field and what they might signify• Topics reviewed -o Democratizing of data -The mainstreaming and commodification of data o New Jobs and roles in working with datao The evolving relationship of AI and data visualizationo Changes in “data wrangling”o Evolving data visualization toolso Data Literacy and Data Communication

Human-Centered Design for Data Visualization• Views you can use o Exploring how data technologies affect your own life and work Examples – recommender systems, work monitoring, social media ecosystems and echo chambers• Algorithmic job boardso Human-Centered Design Descriptions Connecting the visualization to the audience) Techniques for communicating data• Debiasing your data and your visualizations• Neurodiversity and inclusion considerations for working with data and visualizationso Trade-offs between simplicity versus complexityo Color and language selectiono Using different approaches to show the information in different ways for a more complete pictureo Multimodal interfaces with case studies

Measuring What Counts• Turning abstract numbers into actionable insights• Using Quantitative and Qualitative measures• What data do you need? Considerations for data collection• Data Blind spots – It’s the gaps in data that may be more important than what you have. Am I missing critical data? • Design and Data – Considerations for what metrics go on your dashboard and reports• UX Outcomeso Measuring impact and scaleo Metrics of successo Problem-Value Metricso Progress Metrics

Goals of Data Visualization -1.) Exploratory Data Visualization• “A More Beautiful Question” (Interrogating the data without coercion)o Describing the key differences between exploratory and explanatory visualizations and the spectrum in betweeno Case study updates and new ones of exploratory data analysis using interactive visualizationso Links to papers

2.) Explanatory Data Visualization• Data Storytelling - presenting an accurate and compelling narrative of the datao The strengths, weaknesses, and caveats of data storytellingo Selected data storytelling techniqueso Case study updates and new oneo Links to papers showing data visualization that help provide overall clarity and context to data-intensive projects…even for people who are not experts in the field

3.) Extrapolatory Data Visualization• Using data analysis to help make predictions and scenario testo Making well-informed projectionso Looking at potential outcome with different parameterso Visually showing uncertainty

Potential and Perils• Data and Ethics• Data Governance• Privacy versus convenience• How will humans collaborate with data tech?Where does it go from here?