The array of available network-hosted training material and advanced distributed learning content continues to expand. With this expansion, increasingly diverse applications launch training activities and content and track the progress of students and learners. Advances with standards and models help standardize content launch within specific "stovepipes" such as simulations or courseware. These standards, however, do not enable interchange of information about tracked learner experience between diverse online applications such as those increasingly hosted by Web portals. For example, learners engaging in an online small-group training experience may wish to augment understanding of a given subject with background material from a SCORM-conformant course. Yet gaming lobbies and simulation launchers do not typically contain data models and protocols for exchanging recent student experience and assessment results (and, related, the need for additional training or experience). I.e., the launch mechanisms and databases of games or simulations cannot communicate learner results and needs with coursewarelaunching applications such as Learning Management Systems (LMSs), or in a broader sense, the Web portal hosting these multiple applications. This paper describes a service-centric information service that combines training and assessment information into a single distilled joint profile to track current Knowledge, Skills and Abilities and to set the stage for robust adaptive support to the learner. This "Learner Profile"---built using existing standards and models and translating data where data model gaps exist---is accessible via a service-centric learner profile service that serves as a base information source for querying and exchanging learner data about competencies, skills, and training records. This prototype learner information profile service enables commanders, supervisors, and learners to visualize both individual and group training accomplishments and experiences and to make decisions ranging from next-up training events to personnel utilization. Its inherent learner model enables just-in-time provisioning and the basis for Intelligent Tutoring-like behaviors.