DATA VISUALIZATIONS FOR FINANCIAL TRANSPARENCY AND ACCOUNTABILITY Development Gateway Vanessa Goas Deputy Director of Operations
About Development Gateway • Nonprofit social enterprise operating in 25+ countries • Three areas of focus
• Technology • Research and Learning • Data Transparency and Use
• Founding partner of OpenGov Hub, Feedback Labs, and AidData
• Helping data escape the spreadsheet
Drowning in big data?
Poll question When asked to review some data visualizations, what did most people say they remembered the most about it? 1. Specific data points 2. Style of the visualization 3. Title of the visualization 4. Source of the data
Source: Borkin et al
Myths and Realities of Data Myths • More data is better data • Data science is a niche tool • Creating visuals needs big budget and tech expertise
Reality • Can tell a clear story • The right systems make the difference • Not everyone wants an Excel file but some still do
Why data visualization for accountability and transparency?
• Works in tandem with accessible data • Clarifies the financial life cycle • Supports internal audiences • Educates external audiences – from expert to novice
• Lets people ask the right questions
How do I start? •Decide what you want to achieve •Get to know your audience •Collect and clean your data •Visualize it!
Elements of a smart visualization •Memorable visualizations: • Include text which contextualizes the visualization
• Use relevant pictures and icons • Reflect the user’s world view • Allow the user to download the data if they want
Case study: Open Contracting
Case study: Aid Management Platform
Case Study: EITI
Broader Lessons •Data is just the start •Visualizations are one piece of the puzzle •Data standards make the difference •Make it compelling by knowing your audience
Discussion questions • What have been some of your most successful uses of
data visualization?
• What do you see as the biggest challenges for creating smart visualizations in your organization?
• What do you see as the next emerging trend in data visualization?
• What kind of visualizations are most important for you as a user of data?