Data quality is often described as “data that is fit for use by data consumers”. The development of the internet and the various web technologies has increased the expectations of good data quality level among the data consumers. Web portals are meant to attract a wide variety of users and serve as an important means to access data in this information era. There is a need to assess the quality of these data, and so a framework to assess the data quality is wanted. This thesis proposes a framework to assess data quality in university web portals. The proposed framework captures essential DQ dimensions in four categories namely Intrinsic, Representational, Contextual, and Accessibility. In order to develop this framework, DQ dimensions were derived from literature. Next to that special attention was given to data consumers (users of university web portals), this led to the expansion and modification of the dimensions to emphasize the growing importance of the user’s perspective. The set of DQ dimensions has been tested with users using two pre-validations before the final validation of the framework. The proposed framework containing 35 dimensions is validated with user groups of two different universities: TU-Delft, The Netherlands and Pondicherry University, India. The validation showed that all DQ dimensions in the framework were valuable and important from the data consumer’s view of perspective. As an evaluation approach, this framework has been compared with an existing portal data quality model and found this new framework has important DQ dimensions in the context of a UWP. As a consequence, the proposed framework emphasizes the user’s perspective on data quality.