A substantial portion of usability work involves the coordinated collection of data by a team of specialists with varied backgrounds, employing multiple collection methods, and observing users with a wide range of skills, work contexts, goals, and responsibilities. The desired result is an improved system design, and the means to that end are the successful detection of, and reaction to, real deficiencies in system usability that severely impact the quality of experience for a range of users. In the context of user-centered design processes, valid and reliable data from a representative user sample is simply not enough. High-quality usability data is not just representative of reality. It is useful. It is persuasive in the eyes of the right stakeholders. It results in verifiable improvements to the system for which it is intended to represent a deficiency. The data must be efficiently and effectively translated into development action items with appropriate priority levels, and it must result in effective work products downstream, leading to cost-effective design changes. The remainder of this article (a) briefly reviews basic usability data collection concepts, (b) examines the dimensions that make up high-quality usability data, and (c) suggests future trends in usability data quality research.