XBRL Markup Language for Cross-Context Calculation Validation
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Solution Overview
Problem
Current XBRL technologies cannot represent and validate calculation relationships that span multiple contexts, units of measure, or dimensional aggregations, leading to incomplete risk mitigation for calculation inconsistencies in financial reporting.
Innovation Solution
A computing device generates markup language to represent calculation relationships among specific XBRL facts, rather than concepts, using properties such as concept period type, balance type, and data type, and relationships like parent-child or definition relationships, to extend the XBRL taxonomy document and facilitate validation across different contexts and units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If XBRL uses concept-based calculation relationships to represent arithmetic relationships between metadata tags, then validation of facts can be performed, but calculation relationships spanning multiple contexts, units of measure, or dimensional aggregations cannot be represented
Solution Approach 1:
The patent segments the calculation relationship representation by introducing a new element type (calc:calculationArc) that operates at the fact level rather than the concept level. This allows the system to handle specific factual relationships across different contexts, units, and dimensions while maintaining the overall XBRL structure. The segmentation enables representation of relationships that were previously impossible under the concept-based model.
Solution Approach 2:
The patent adds a new dimension to XBRL by introducing the calc: namespace and calc:calculationArc elements that operate alongside the existing concept-based calculation relationships. This dimensional addition allows facts from different contexts, units of measure, and dimensional aggregations to be linked in calculation relationships without breaking the existing XBRL framework, thereby expanding the system's versatility while maintaining reliability.
2Stability of the object's composition
If XBRL follows strict concept-based relationships defined in taxonomy, then consistency is maintained, but inability to represent relationships across different contexts leads to incomplete risk mitigation
Solution Approach 1:
The patent introduces calc:calculationArc as an intermediary element that mediates between facts from different contexts, units of measure, and dimensional aggregations. This intermediary allows the system to maintain the stable XBRL structure while enabling representation of cross-context relationships, thereby providing complete risk mitigation without compromising structural consistency.
Solution Approach 2:
By adding the calc: namespace dimension, the patent creates a parallel layer that handles cross-context relationships while the original XBRL structure remains intact. This dimensional addition allows the system to maintain stability in the core structure while extending capability to handle previously unsupported relationship types, achieving both consistency and complete risk mitigation.
3Measurement precision
If XBRL validates facts against concept-based calculation relationships, then accuracy is improved for supported relationships, but relationships spanning multiple contexts remain unsupported
Solution Approach 1:
The patent segments validation into two layers: concept-based validation for traditional relationships and fact-based validation using calc:calculationArc for cross-context relationships. This segmentation allows the system to maintain high validation accuracy for supported relationships while extending coverage to previously unsupported relationship types spanning multiple contexts, units, and dimensions.
Solution Approach 2:
The calc:calculationArc element serves multiple functions: it validates facts across different contexts, handles relationships spanning multiple units of measure, and supports dimensional aggregations. This universal element type increases relationship coverage while maintaining validation accuracy through its ability to handle diverse relationship types within a unified framework.
Data Source
AI summary
One or more computing devices carry out a method for generating markup language to represent a calculation relationship among facts, wherein each fact is described by metadata whose characteristics are defined in an extensible business reporting language (XBRL) taxonomy document. In various implementations, the method includes: searching the document for a data item that contains an arithmetic formula, determining which other data items of the document are referenced by the arithmetic formula, determining which of the plurality of facts correspond to the referenced data items, based on the arithmetic formula, generating markup language that represents an arithmetic relationship among the facts corresponding to the referenced data items, and modifying the XBRL taxonomy document with the generated markup language.