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Analysis of the proteins of the aqueous humor can help to elucidate the complex pathogenesis of primary open angle glaucoma. Thanks to advances in liquid chromatography tandem mass spectrometry (LC-MS/MS) it is now possible to identify hundreds of proteins in individual aqueous humor samples without the need to pool samples. We performed a systematic literature search to find publications that performed LC-MS/MS on aqueous humor samples of glaucoma patients and of non-glaucomatous controls. Of the seven publications that we found, we obtained the raw data of three publications. These three studies used glaucoma patients that were clinically similar (i.e. undergoing glaucoma filtration surgery) which prompted us to reanalyse and combine their data. Raw data of each study were analysed separately with the latest version of MaxQuant (version v1.6.11.0). Outcome files were exported to Microsoft Excel. Samples belonging to the same patient were averaged to obtain peptide expression values per individual. We compared the overlap of identified proteins using the VLOOKUP function of Excel and a publicly available Venn diagram software. For the peptide sequences that can belong to multiple proteins (usually of the same protein family), we initially included all possibly identified proteins. This ensured that we would not miss a potential overlap between the studies due to differences in identified peptide counts. Next, of those peptides of which we compared multiple proteins, only one unique protein was included in our analysis i.e. either the protein overlapping between studies or in case of no overlap, the protein that had the highest identified peptide count. This yielded 639 unique proteins detected in aqueous humor of either glaucoma patients or non-glaucomatous controls. In our manuscript entitled “The aqueous humor proteome of primary open angle glaucoma: An extensive review” [1] , we further analysed this dataset. The dataset was exported to Perseus (version 1.6.5.0). We removed contaminants and filtered for proteins detected with high confidence, i.e. in more than 70% of the samples of at least one study. This yielded 248 proteins of which we compared the expression in glaucoma patients against control patients. Gene ontology enrichment analysis and pathway analysis was used to interpret the results. The unfiltered dataset reported in this data article and the approach reported here to reanalyse and combine raw data of different studies can be applied by other glaucoma researchers to gain more insight in the pathogenesis of glaucoma.