This paper presents the process of development and the characteristics of an evaluation collection for a personalisation system for digital newspapers. This system selects, adapts and presents contents according to a user model that define information needs. The collection presented here contains data that are cross-related over four different axes: a set of news items from an electronic newspaper, collected into subsets corresponding to a particular sequence of days, packaged together and cross-indexed with a set of user profiles that represent the particular evolution of interests of a set of real users over the given days, expressed in each case according to four different representation frameworks: newspaper sections, Yahoo categories, keywords, and relevance feedback over the set of news items for the previous day. This information provides a minimum starting material over which one can evaluate for a given system how it addresses the first two observations - adapting to differen...