The previously generated set of data and information are then semantically enriched to construct a KG structure; for this, the next steps require the representation of data as subject-predicate-object (RDF triple) and reconciliation with external identifiers (WD chemical structures, for example) when possible (Figure ). Data representation as triples implies, for example, linking a given LC-MS feature to its corresponding SIRIUS annotation by a predicate (see a visual representation of the triple). In Figure , some representative examples illustrate how predicates link different subjects and objects to form a KG. To incorporate MS 2 information into the KG, each LC-MS feature's MS 2 fragmentation spectrum is formatted as a document containing peaks and neutral losses using the spec2vec package . This incorporation of spectral data is innovative and of great interest as it enables the interlinking of all entities of the KG, such as spectra, but also molecular structure or extracts, through sub-spectral features (peaks, losses, or groups thereof). This particular alignment is fully independent of the chromatographic conditions and allows the realization of powerful queries regarding the spectral relatedness of features originating from different samples (see, for example, Table , query 6 and query 9). The spectral annotations (non-stereochemically defined chemical structures identified by their 2D InChiKeys) are then linked, if present, with their stereochemically defined counterparts in WD (identified by their complete InChIKeys). This reconciliation allows the user to run federated SPARQL queries over ENPKG and WD to retrieve, for example, among a given sample's structural annotations, the ones already reported in the same taxon (see Table , query 4). Additionally, all chemical structures are classified using the NPClassifier chemical taxonomy (at the pathway, superclass, and class levels) . The chemical structures can also be enriched with their reported bioactivity against a selected biological target in ChEMBL.