Scientists often build and use highly customized systems to support observation and analysis efforts. Creating effective ontologies to manage and share data products created from those systems is a difficult task that requires collaboration among domain experts, e.g., scientists and knowledge representation experts. A framework is presented that scientists can use to create ontologies that describe how customized systems capture and transform data into products that support scientific findings. The framework establishes an abstraction that leverages knowledge representation expertise to describe data transformation processes in a consistent way that highlights properties relevant to data users. The intention is to create effective ontologies for scientific data management by focusing on scientist-driven descriptions. The framework consists of an upper-level ontology specified with description logic and supported with a graphical language with minimal constructs that facilitates use by scientists. Evaluation of the framework's usefulness for scientists is presented.