This document summarizes Samuel Lampa's 2010 degree project on integrating SWI-Prolog for semantic reasoning in Bioclipse. It compares SWI-Prolog to other semantic tools like Jena and Pellet in terms of speed and expressiveness when querying biochemical data. Prolog code is presented for querying NMR spectrum data that finds molecules with peak values near a search value. SPARQL queries for the same use case are also shown. Observations indicate Prolog is fastest while SPARQL is easier to understand but Prolog allows easier parameter changes and logic reuse. A final presentation was planned for April 28, 2010.