Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social science, the Internet of Things, and cloud computing. The field encompasses the larger areas of data analytics, machine learning, and managing big data, while related new scientific challenges range from data capture, creation, storage, search, sharing, analysis, and visualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situations
An analytical framework to nowcast well-being using mobile phone data
PAPPALARDO, LUCA;GABRIELLI, LORENZO;PEDRESCHI, DINO;GIANNOTTI, FOSCA
2016-01-01
Abstract
Data-driven scientific discovery is a key emerging paradigm driving research innovation and industrial development in domains such as business, social science, the Internet of Things, and cloud computing. The field encompasses the larger areas of data analytics, machine learning, and managing big data, while related new scientific challenges range from data capture, creation, storage, search, sharing, analysis, and visualization, to integration across heterogeneous, interdependent complex resources for real-time decision-making, collaboration, and value creation. The journal welcomes experimental and theoretical findings on data science and advanced analytics along with their applications to real-life situationsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.