Mastercard, Rockefeller Foundation Launch Online Data Platform For Non-Profits

The Rockefeller Foundation, along with the Mastercard Center for Inclusive Growth, announced their new platform data.org today in Davos. The site will be a dynamic platform for data science partnerships committed to improve the field’s social impact.

The philanthropy organizations also revealed today a $10 million “impact challenge” to crowdsource data science initiatives and solutions for organizations in the non-profit, civic, and government space.

They intend to build on the legacy of the original DATA.org website—launched in 2002.

“Our commitment to building the field of data science is rooted in the belief that data-driven insights can deliver transformational change that improves the lives of vulnerable people and helps solve the world’s most pressing challenges,” said Michael Froman, vice chairman of Mastercard. “We must make sure that even as people have unprecedented access to technology, we don’t allow a new digital divide to emerge.”

Today’s announcement is the next big chapter of a $50 million commitment Mastercard and the Rockefeller Foundation made in 2019 regarding an assertive, strategic transformational model for philanthropy.

“While the private sector has been gathering data and using data science analytics, such as artificial intelligence for many years, most non-profit, civic and public sector institutions still lack the resources to do so,” said Dr. Rajiv Shah, President of The Rockefeller Foundation. “Just as these tools have given businesses competitive edges, enabling them to find nuanced ways to improve productivity and market impact, data science can increase the speed, depth, and accuracy of analyzing a social challenge, pointing to solutions, partnerships, and innovative investments that can provide impact.”

The 2020 data.org site will build non-profit organizations’ capacity with education and training in a manner that will unify people and organizations in the cause of positive social change with responsible data science and usage.