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Due to the popularity of smart mobile phones and context-aware technology,various contextual data relevant to users' diverse activities with mobilephones is available around us. This enables the study on mobile phone data andcontext-awareness in computing, for the purpose of building data-drivenintelligent mobile applications, not only on a single device but also in adistributed environment for the benefit of end users. Based on the availabilityof mobile phone data, and the usefulness of data-driven applications, in thispaper, we discuss about mobile data science that involves in collecting themobile phone data from various sources and building data-driven models usingmachine learning techniques, in order to make dynamic decisions intelligentlyin various day-to-day situations of the users. For this, we first discuss thefundamental concepts and the potentiality of mobile data science to buildintelligent applications. We also highlight the key elements and explainvarious key modules involving in the process of mobile data science. Thisarticle is the first in the field to draw a big picture, and thinking aboutmobile data science, and it's potentiality in developing various data-drivenintelligent mobile applications. We believe this study will help both theresearchers and application developers for building smart data-driven mobileapplications, to assist the end mobile phone users in their daily activities.

Mobile Data Science: Towards Understanding Data-Driven Intelligent Mobile Applications