  We present a shared data model for enabling data science in Massive Open
Online Courses (MOOCs). The model captures students interactions with the
online platform. The data model is platform agnostic and is based on some basic
core actions that students take on an online learning platform. Students
usually interact with the platform in four different modes: Observing,
Submitting, Collaborating and giving feedback. In observing mode students are
simply browsing the online platform, watching videos, reading material, reading
book or watching forums. In submitting mode, students submit information to the
platform. This includes submissions towards quizzes, homeworks, or any
assessment modules. In collaborating mode students interact with other students
or instructors on forums, collaboratively editing wiki or chatting on google
hangout or other hangout venues. With this basic definitions of activities, and
a data model to store events pertaining to these activities, we then create a
common terminology to map Coursera and edX data into this shared data model.
This shared data model called MOOCdb becomes the foundation for a number of
collaborative frameworks that enable progress in data science without the need
to share the data.
