Data Quality (DQ) has been an acknowledged issue for a long time. Several researchers have indicated that maintaining the quality of data is often acknowledged as problematic, but is also seen as critical to effective decision-making in engineering asset management (AM). The study presents an AM specific DQ framework, which aims to provide a comprehensive structure for understanding, identifying AM DQ problems in an organised way. The framework was examined in a preliminary case study of two large Australian engineering organisations. The empirical findings from the research were used to validate the proposed AM DQ framework. As AM data and informational needs are very different to a typical business environment, a gap exists in the availability of DQ solutions for engineering asset management. Thus there is a need for the development of DQ solutions for engineering asset management.