Using SPIN to Formalise XBRL Accounting Regulations on the Semantic Web

The eXtensible Business Reporting Language (XBRL) has standardised consolidated financial reporting and through its machine readable format facilitates access to and consumption of financial figures contained within the report. Formalising XBRL as RDF facilitates the leveraging of XBRL with Open Financial Data. Previous XBRL to Semantic Web transformations have however concentrated on making the semantics of its logical model explicit to the exclusion of accounting regulatory validation rules and constraints found within the XBRL calculation linkbases. Using off-the-shelf Semantic Web technologies this paper investigates the use of the SPARQL Inferencing Notation (SPIN) with RDF to formalise these accounting regulations found across XBRL jurisdictional taxonomies. Moving beyond previous RDF to XBRL transformations we investigate how SPIN enhanced formalisation enables financial instrument fact inferencing and sophisticated consistency checking. SPIN formalisations are further used to evaluate the correctness of reported financial data against the calculation requirements imposed by accounting regulation. Our approach illustrated through the use of use case demonstrators outlines that SPIN usage meets central requirements for financial constraint regulatory modelling.