Protecting privacy: Towards a visual framework for handling end-user data

Ensuring the privacy of end-user data is of paramount importance. Allowing data analysts access to personally identifiable information can lead to legal problems, especially when the end-user has not given permission for such data to be used. This paper is concerned with the specification and processing of data collected from consumers as they interact with services such as those presented as `smart-phone' applications. Consumers are (should be) asked whether they want to opt-out of various kinds of their data being collected and/or used for marketing and other data analysis purposes. This impacts on the manner in which their data can be used by analysts. The process to determine the transformations that data must undergo in order to be used lawfully involves a wide range of stakeholders: software engineers, lawyers, analysts and marketing personnel, to name some. Each of these stakeholders has different expertise and prior knowledge that must be taken into account when devising methods of communication between them. We argue that visual (diagrammatic) notations developed for this purpose aid effective communication between these diverse groups. To date, there is no general method for visualising the transformations that raw data must undergo. We address this by utilising the concept diagram notation to rigorously depict, abstractly, how the data needs to be processed and the effects upon that data under various privacy related transformations.