TY - JOUR
T1 - From big data to deep insight in developmental science
AU - Gilmore, Rick O.
N1 - Publisher Copyright:
© 2016 Wiley Periodicals, Inc.
PY - 2016/3/1
Y1 - 2016/3/1
N2 - 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.
AB - 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.
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U2 - 10.1002/wcs.1379
DO - 10.1002/wcs.1379
M3 - Article
C2 - 26805777
AN - SCOPUS:84958775463
SN - 1939-5078
VL - 7
SP - 112
EP - 126
JO - Wiley Interdisciplinary Reviews: Cognitive Science
JF - Wiley Interdisciplinary Reviews: Cognitive Science
IS - 2
ER -