With the advance and wide usage of GPS enabled devices and other positioning systems, mobility behaviour of individuals can now be captured and streamed into a data warehouse for online or historical data analysis. We refer to such data as mobility data. Mobility data mining comes into picture as an emerging field which aims to extract knowledge from mobility data with a lot of opportunities as well as risks. The risks arise from the fact that, the mobility data is mostly about people, where they have been, at what times, how often, and with whom. Therefore privacy is a major concern, and needs to be addressed before the opportunities of mobility data mining can be harvested. MODAP aims to stimulate an interdisciplinary research area combining a variety of disciplines such as data mining, geography, visualization, data/knowledge representation, and transforming them into a new context of mobility while considering privacy which is the social aspect of this project. The high impact of MODAP is mainly due to the two related facets of its area of interest, i.e., people's movement behaviour, and the associated privacy implications. Privacy is often associated with the negative impact of technology, especially with recent scandals in the US such as AOL's data release which had a lot of media coverage. MODAP aims to turn this negative impact into positive impact by showing that privacy technology can be integrated into mobility data mining which is a challenging task. This very aim of MODAP also imposes a high risk, since nobody knows what kinds of privacy threats exist due to mobility data and how such data can be linked to other data sources.