Small molecule spectral libraries are also used as the basis of computational tool and resource development in metabolomics . For example, fragmentation patterns of acylcarnitines were derived from the NIST spectral library using the hybrid search strategy, which could then be used to extract and validate additional related acylcarnitine MS/MS spectra . The GNPS nearest neighbor suspect spectral library was created in a data-driven fashion by molecular networking of hundreds of millions of public MS/MS spectra on the GNPS repository in combination with reference MS/MS spectra in the GNPS community spectral libraries, and is a unique resource that provides insights into common modifications that molecules can undergo . Additionally, high-quality annotated MS/MS spectra in open spectral libraries are increasingly being used to train and validate machine learning methods in metabolomics . For example, they can be used to learn relationships between MS/MS patterns and molecular (sub)structures (e.g. MS2LDA , MESSAR ), develop machine learning-inspired spectrum similarity scores (e.g. Spec2Vec , MS2DeepScore , SIMILE ), simulate MS/MS spectra (e.g. CFM-ID (F. ), and predict spectrum annotations (e.g. CSI:FingerID , COSMIC (M. A. , MassGenie ).