Due to the popularity of smart mobile phones and context-aware technology,
various contextual data relevant to users' diverse activities with mobile
phones is available around us. This enables the study on mobile phone data and
context-awareness in computing, for the purpose of building data-driven
intelligent mobile applications, not only on a single device but also in a
distributed environment for the benefit of end users. Based on the availability
of mobile phone data, and the usefulness of data-driven applications, in this
paper, we discuss about mobile data science that involves in collecting the
mobile phone data from various sources and building data-driven models using
machine learning techniques, in order to make dynamic decisions intelligently
in various day-to-day situations of the users. For this, we first discuss the
fundamental concepts and the potentiality of mobile data science to build
intelligent applications. We also highlight the key elements and explain
various key modules involving in the process of mobile data science. This
article is the first in the field to draw a big picture, and thinking about
mobile data science, and it's potentiality in developing various data-driven
intelligent mobile applications. We believe this study will help both the
researchers and application developers for building smart data-driven mobile
applications, to assist the end mobile phone users in their daily activities.Comment: Journal, 11 pages, Double Colum
