INDEX

Welcome to the human-readable and machine-readable knowledge graph for IFRS-FULL. This free open source resource enables software engineers to understand how to create supercharged software applications related to IFRS-FULL or other financial reporting schemes represented using XBRL. It is based on a proven, best-practices, global standard method.

XBRL taxonomy for International Financial Reporting Standards (IFRS) which is provided by the IASB.

For more information please see: https://www.ifrs.org/issued-standards/ifrs-taxonomy/ifrs-taxonomy-2021/

IFRS-FULL Knowledge Graph

This XBRL-based machine-readable information essentially forms a knowledge graph. The IFRS-FULL Knowledge Graph is a set of terms, structures, assocations, and rules that are used to build models and report facts per those models.

The following is a quick reference to information provided within this human-readable and machine-readable knowledge graph.

• XBRL Syntax Rules: (Human | Machine)
• Model Structure Rules: (Human | Machine)
• Fundamental Accounting Concept Rules: (Human | Machine)
• Disclosure Mechanics Rules: (Human | Machine)
• Reporting Checklist Rules: (Human | Machine)
• Type/Subtype Rules: (Human | Machine)
• Disclosures: (Human | Machine) The financial reporting scheme requires specific disclosures.
• Topics: (Human | Machine) Those disclosures can be organized within specific topics.
• Templates: (Human | Machine) Templates provide examples of those disclosures.
• Exemplars: (Human | Machine) Examples (exemplars) exist in the form of how other economic entities reported these same disclosures.
• Terms: (Human | Machine) Terms are used to represent disclosures in a machine-readable XBRL taxonomy.
• Structures: (Human | Machine) Reported disclosures are represented using XBRL networks, XBRL hypercubes, and logical blocks which form a model.
• Fundamental Concepts: (Human | Machine) High-level fundamental accounting concepts exist within the conceptual framework for IFRS-FULL
• Reporting Styles: (Human | Machine) Reporting styles are models of relations between fundamental accounting concepts that form an approach to creating a report.
• Consistency Rules: (Human | Machine) Consistency rules explain the relations between fundamental accounting concepts.
• Derivation Rules: (Human | Machine) When a fundamental accounting concept is not explicitly reported; derivation (a.k.a. impute) rules are used to use logical deduction to derive the value of the unreported high-level financial concept.
• Facts: (Human | Machine) Facts must be consistent with the permitted terms, structures, associations, and rules. When the statements and facts are consistent then the logical system is functioning properly (consistent, complete, precise).

Technical Basics

The following is important basic technical information that will help get software engineers started. For a good book see The XBRL Book: Simple, Precise, Techical.

• Machine-readable Knowledge Graph
• Profile
• Base Taxonomy Download
• Reference Implementation of Report
• Example Information Repository Dashboard
• Example Information Repository Extraction Prototype
• Example Information Repository Machine Readable RSS