Data is changing how we learn, and it has also changed the way people learn.
For decades, the world’s biggest and most powerful datasets – the massive quantities of data used to map the world around us – were largely kept private.
They were rarely used to inform policy and social analysis.
The biggest of these, the Global Burden of Disease (GBD), was published every five years.
But with the advent of big data in the 1990s, the datasets began to trickle into the public domain, making them available to researchers and citizens alike.
GBD is the world population’s gross domestic product, and while it is not the only global statistic, it is the most widely used, with the Global Inequality Index (GIID) ranking it among the top 10.
But big data now provides the potential to transform how we understand and analyse the world.
In this episode of the Mindmap podcast, we look at the future of big datasets and the implications for society.
First, we explore the implications of the recent discovery that data from the World Health Organization’s Global Biodemographic and Health Informatics Database (GBDB) could provide insights into trends and predictors of disease and mortality in developed countries.
Second, we hear from a few people who have seen their data used in ways that might surprise them, and we discuss how data could potentially be used to better understand and respond to health challenges around the world, from global warming to pandemic prevention.
We then look at how big data can help us understand our collective behaviour in real time.
And finally, we examine how data is being used to provide a better understanding of how we think, learn and live in the 21st century.
For more on big data and its implications, read the book Mindmap: Big Data and the Future of Learning.
This article originally appeared on BBC Future and was reprinted with permission.