This Title All WIREs
How to cite this WIREs title:
WIREs Cogn Sci
Impact Factor: 3.476

From big data to deep insight in developmental science

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

The use of the term ‘big data’ has grown substantially over the past several decades and is now widespread. In this review, I ask what makes data ‘big’ and what implications the size, density, or complexity of datasets have for the science of human development. A survey of existing datasets illustrates how existing large, complex, multilevel, and multimeasure data can reveal the complexities of developmental processes. At the same time, significant technical, policy, ethics, transparency, cultural, and conceptual issues associated with the use of big data must be addressed. Most big developmental science data are currently hard to find and cumbersome to access, the field lacks a culture of data sharing, and there is no consensus about who owns or should control research data. But, these barriers are dissolving. Developmental researchers are finding new ways to collect, manage, store, share, and enable others to reuse data. This promises a future in which big data can lead to deeper insights about some of the most profound questions in behavioral science. WIREs Cogn Sci 2016, 7:112–126. doi: 10.1002/wcs.1379 This article is categorized under: Psychology > Development and Aging

Browse by Topic

Psychology > Development and Aging

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts