A significant and daunting challenge for science data and service centers and repositories is to establish trustworthiness and fitness for purpose, i.e., suitability, at the level of individual data products and services. Having content-rich, interoperable and discoverable quality descriptive information will help organizations address this challenge. The scalability of curating such information, either as metadata records or as documents, has considerable challenges of its own. This session invites presentations on approaches, frameworks, workflows, best practices, tools, etc., that are under development or being implemented towards systematically evaluating quality attributes of individual data products and services, and automatically generating content-rich quality descriptive information that is interoperable and discoverable. All types of data, all perspectives of data and information quality, and all aspects of product and service quality attributes are welcome.