Converting NCR2018 Descriptive Rules into RDF Data

Purpose: The purpose of this study is to confirm the feasibility of RDF data conversion by presenting necessary considerations and options and then identifying appropriate options, with the intention of converting NCR2018 descriptive rules into RDF data. Method: In order to be suitable for effective utilization as linked data (1) we considered possible options for expressing individual rules as an RDF class and expressing various relationships between the classes; (2) based on the choices adopted. the conversion to RDF data was performed for the rules in the three chapters; and (3) mutual references between the RDF-expressed NCR rules and metadata in line with the rules were examined. Results: (1) In addition to the RDF class being determined based on the rule numbers of NCR2018, it was appropriate to adopt a division unit corresponding to each instruction applied independently under a given rule. Each rule and division unit was given a URI as an RDF class, and various relationships between them were properly expressed including hierarchical relationships, reference relationships, those between a rule and its alternatives, etc. (2) RDF data from the three chapters of NCR2018 were prepared by performing mechanical conversion to RDF data with manual correction. It was confirmed that RDF data can be converted without major barriers using the adopted policy and choices. (3) It was shown that mutual references between the NCR rules and metadata created under the NCR rules can be implemented, leading to a possible utilization of RDF-expressed NCR rules.