Transforming data into knowledge

Cesar Hidalgo

The Collective Learning group at the MIT Media Lab focuses on how teams, organizations, cities, and nations learn. Our research addresses both the study of knowledge + knowhow accumulated in social groups and the creation of tools that democratize data analysis and facilitate collective learning.

Established as the Macro Connections group in 2010, it was renamed as Collective Learning in 2017. The group has pioneered the study of collective learning in economies–by advancing the theory and practice of economic complexity, and in history–by creating the largest structured dataset on biographical records. The work has also encompassed extensive mapping of urban perceptions and innovative tools for predicting urban change.

The group is renowned for the development of large data visualization engines, which are tools that algorithmically transform data into stories. These visualization engines receive millions of visitors every year and include:

The Collective Learning group at the MIT Media Lab focuses on how teams, organizations, cities, and nations learn. Our research addresses both the study of knowledge + knowhow accumulated in social groups and the creation of tools that democratize data analysis and facilitate collective learning.

Established as the Macro Connections group in 2010, it was renamed as Collective Learning in 2017. The group has pioneered the study of collective learning in economies–by advancing the theory and practice of economic complexity, and in history–by creating the largest structured dataset on biographical records. The work has also encompassed extensive mapping of urban perceptions and innovative tools for predicting urban change.

The group is renowned for the development of large data visualization engines, which are tools that algorithmically transform data into stories. These visualization engines receive millions of visitors every year and include:

Group at a glance