Software engineering meta-data (SE data), such as revision control data, Github project data or test reports, is typically semi-structured, it comprises a mixture of formatted and free-text fields and is often self-describing. Semi-structured SE data cannot be queried in a SQL-like manner because of its lack of structure. Consequently, there are a variety of customized tools built to analyze specific datasets but these do not generalize. We propose to develop a generic framework for exploration and querying of semi-structured SE data. Our approach investigates the use of a formal concept lattice as a universal data structure and a tag cloud as an intuitive interface to support data exploration.