To enrich the data with semantically well-defined concepts, we employ the recently developed ontology Battery Interface Ontology (BattINFO). BattINFO describes thousands of concepts related to electrochemistry and batteries. Concepts are linked to each other adhering to logically consistent relationships, thus rendering meaning machinereadable . The connections among data and concepts must be encoded using a standard method. In this work, JSON for Linked Data (JSON-LD) is used to link the results from the conductivity and EOL tasks to ontology concepts in BattINFO and Schema.org. BattINFO describes measurement fields related to batteries and electrochemistry, while the Schema.org vocabulary describes tenant metadata, software resources and other nonelectrochemical concepts. For example, we enrich the descriptions of the request/result posting tenant with the ORCID of the responsible person linked to the schema:author type, and ROR-ID for the organisation linked to schema:creator type. These choices improve data consistency, since they avoid reliance on other identifiers (such as email addresses) that are subject to change. EOL and conductivity results in this study are all expressed in JSON-LD files mapped to ontology concepts. Details and an example of the semantic implementation of experimental results can be found in section SI-2.6 of the SI. Development of the knowledge graph representation of the data was done subsequently to the data collection. The graphs were therefore uploaded to the archive entries after the optimisation phases had been completed.