An impediment to identification and annotation of the unknown features in untargeted metabolomics data is the inconsistency between analytical methods and instrumentation used by different labs. To address this challenge, we will work with other labs in the NIH metabolomics consortium to generate an inter-laboratory dataset using consensus polar metabolomics methods and common samples. These data will facilitate alignment and identification of unknown features in current and future untargeted metabolomics data. Aim 1: A working group (based on the existing ULWG and ISWG, but also welcoming additional participants) will convene to discuss strategies to assess inter-laboratory overlap of unknown polar metabolites in untargeted metabolomics data. We will discuss and agree upon common samples, internal standards (to be derived from of ISWG efforts), chromatography, mass spec parameters, and data processing methods. Aim 2: We will distribute a sample set decided upon in Aim 1 and each participating laboratory will perform sample analysis according to the defined methods. For comparative purposes, labs will also be requested to perform a second round of data acquisition on the same samples using their own standard operating procedures for untargeted polar metabolomics. Aim 3: Data from participating labs will be processed through a common feature detection and alignment pipeline to align known and unknown features. Data will be contributed to an unknown compound database currently under development to house the unknown lipidomics data.