The dataset includes information on material characteristics, assay types, cell each containing a logical source, subject map, and one or more predicate-object maps. The logical source represents the input data source, which could be any dataset in one of the supported formats. The subject map describes how the subjects for each logical resource are generated, while the predicate-object map specifies the predicate ontological annotation to use and how the object is generated for each triple. YARRRML is already equipped with basic functions to help transform the source data. However, custom functions can be defined for more advanced transformations. The RDF generation process starts with converting the mapping rules file(s) from YARRRML syntax (YAML file) to RML syntax (turtle file) using YARRRML-parser . Next, RML-Mapper , an RML processor, is used to convert the dataset to RDF using the mapping turtle file(s). In this work, YARRRML-parser v1.5.4 and RML-mapper v4.15 were used. A java utility with helper functions needed to transform the data was developed and its functions were used in the mapping rules. The tools and the script made to run them were encapsulated in a Docker image, hosted on Docker Hub, for reproducibility and portability .