The ENPKG workflow was designed to address these challenges. It aims to compile and streamline the various types of data and information generated by modern NPs metabolomics workflows into a unified KG, thereby effectively organizing and distilling the resulting knowledge. Thanks to reconciliation with external identifiers and semantic enrichment, newly generated data is matched and augmented with publicly shared knowledge. With this specific KG architecture, powerful interrogation strategies using the SPARQL, for example, can be harnessed to explore the gathered data, information, and knowledge. A conceptual overview of the ENPKG framework, using the Data, Information, Knowledge, and Wisdom (DIKW) pyramid is illustrated in Figure .