MALDI imaging mass spectrometry is a powerful tool for morphology-based proteomic tissue analysis. However, peptide identification is still a major challenge due to low S/N ratios, low mass accuracy and difficulties in correlating observed m/z species with peptide identities. To address this, we have analyzed tryptic digests of formalin-fixed paraffin-embedded tissue microarray cores, from 31 ovarian cancer patients, by LC-MS/MS. The sample preparation closely resembled the MALDI imaging workflow in order to create representative reference data sets containing peptides also observable in MALDI imaging experiments. This resulted in 3844 distinct peptide sequences, at a false discovery rate of 1%, for the entire cohort and an average of 982 distinct peptide sequences per sample. From this, a total of 840 proteins and, on average, 297 proteins per sample could be inferred. To support the efforts of the Chromosome-centric Human Proteome Project Consortium, we have annotated these proteins with their respective chromosome location. In the presented work, the benefit of using a large cohort of data sets was exemplified by correct identification of several m/z species observed in a MALDI imaging experiment. The tryptic peptide data sets generated will facilitate peptide identification in future MALDI imaging studies on ovarian cancer.