The mapping between strings and ontology classes is provided through a TSV file the function can access (purple highlight in Figure ). This way, the values of each column can be annotated using the same function by specifying the right group to extract the annotations from. This is shown in the figure with colored boxes matching the dataset columns and the corresponding sections in the mapToIri.tsv file where the annotations will be looked up, light green for nanomaterial types, orange for assay types and blue for cell lines. The ontological annotations used in RDFizing the five selected datasets in this work is available online on GitHub . This design allows annotations to be separate from the mapping rules and thus minimizes the changes required to mapping files for new datasets. Most of the work when converting new datasets would be in annotating dataset column values and the changes to the mappings would be mainly the column names and the variables of the metadata elements which are defined at the top of each mapping file to facilitate the customization. The mappings of the five datasets along with instructions on how to execute the RDFization process is made available on GitHub and archived on Zenodo under CC-BY 4.0 open license .