To obtain as much information as possible on the thousands of chemicals that may be present in samples (e.g., biological or environmental), non-target analysis (NTA) utilizing liquid or gas chromatography (LC or GC) coupled with a high-resolution mass spectrometer (HRMS) is a commonly used technique. Here data-dependent analysis (DDA) and data-independent analysis (DIA) are often used to obtain the related MS2 information (i.e., fragments) for LC-HRMS. DDA data generally has less overlap and cleaner MS2 spectra but does not analyze all MS1 signals, as only ions of interest are further fragmented. On the other hand, DIA aims to analyze and fragment all MS1 signals, obtaining generally complex MS2 spectra that can come from overlapping compounds and could obscure low intensity compounds. Through data processing the information is generally extracted by performing feature detection, componentization where information from unique chemical constituents is grouped (i.e., parent, isotopologue, adduct, and (in-source) fragment ions), and identification. Besides the measurement parameters that influence the covered chemical space, adequate data processing techniques that can handle the complex data and do not further limit the detectable chemical space are required. For example, the algorithms should not be compound class specific as it is generally unknown what the sample is comprised of with NTA experiments.