Beyond Traditional Characterizations in the Age of Data: Big Models, Scalable Algorithms, and Meaningful Solutions

What are data and network models? What are efficient algorithms? What are meaningful solutions? Big Data, Network Sciences, and Machine Learning have fundamentally challenged the basic characterizations in computing, from the conventional graph-theoretical modeling of networks to the traditional polynomial-time worst-case measures of efficiency: