Work reported in this chapter focuses on the learner's interaction with resources on the Semantic Web; in particular with the semi-structured data that can be exposed to the user via domain-specific inference templates. We assessed this capability to use information from multiple sources of the service-based ASPL-v2 framework and analyzed it in terms of assisting users with interpreting connections in the academic domain; for example, identifying leading experts, recognizing communities of practice, or associating research topics and issues with particular publication outlets. The outcomes of a user-based study are reported, with our semantic platform found to outperform other similar tools – including the generic search engine aggregator Ask and semi-specialized Google Scholar.