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Information systems that support scientific collaboration often facilitate the sharing of tangible resources, such as data files, as a proxy for sharing the knowledge embedded in or emerging from those resources. Current computational aids to science work thus do little to support knowledge-based inquiry; the human knowledge that creates meaning out of analyses is often only recorded when work reaches publication—or worse, left unrecorded altogether—for lack of an abstract model for scientific concepts that can capture knowledge as it is created and used. In this research, concepts rather than datasets are treated as the primitive elements of scientific inquiry. A model for scientific concepts is developed that incorporates representation of (1) the situated processes of science work, (2) the social construction of knowledge, and (3) the emergence and evolution of understanding over time. In this model, knowledge is the result of collaboration, negotiation, and manipulation by teams of researchers. Capturing the situations in which knowledge is created and used helps these collaborators discover areas of agreement and discord, while allowing individual inquirers to maintain different perspectives on the same information. The capture of provenance information allows historical trails of reasoning to be reconstructed, revealing the process by which knowledge is adopted, revised, and reused in a community. This work leverages advancement in the areas of cyberinfrastructure and the Semantic Web to produce a proof-of-concept system, called Codex, based on this situated knowledge model. Codex supports visualization of knowledge structures and inference across those structures. The proof-of-concept is deployed in two collaborative application contexts, human-environment interaction and geoscience. These use cases demonstrate the viability of Codex to support distributed teams of learners and researchers by encouraging greater appreciation for shared understanding.