Regarding the Dual-Track Design Conception for Data Asset Recognition on Financial Statements

This paper focuses on the core dilemma of data asset recognition on financial statementsthe conflict between lagging legal rights confirmation and advanced accounting standards. The current legal system exhibits "affirmation in principle but lack of specific rules" regarding data ownership ,e.g., Civil Code, resulting in ambiguous ownership reliant on case-by-case remedies ,e.g., "Sina Weibo v. MoMo case". Concurrently, International Financial Reporting Standards (IFRS) require assets to meet "identifiability" and "control" criteria. However, data's non-excludability, replicability, and uncertainty of future benefits ,e.g., medical data make traditional standards difficult to apply, creating "recognition implies violation" risks.To resolve this paradox, this paper proposes a framework for "Reconstructing the Legal-Accounting Collaborative Governance Mechanism," establishing a "dual-track" approach:Legal Confirmation Track: Adopts "layered rights determination by lifecycle + contextual ownership allocation." Based on the data lifecycle : raw/derivative/product data, it grants layered rights to users, enterprises, and society, with differential regulation via a "type-scenario" matrix.Accounting Confirmation Track:Introduces the "Dynamic Abacus" model. It dynamically assesses value from three dimensions: data quality, application scenario, and risk deduction, distinguishing "public welfare data assets" (cost method) from "operational data assets" (income method), utilizing blockchain verification to ensure authenticity and legitimate ownership.Cases like "MoMo case," "Luckin Coffee incident," and "diagnostic data cases" validate the dual-track's feasibility. The core contribution lies in deconstructing institutional tensions and constructing a collaborative framework, providing theoretical justification and a practical pathway for compliant data asset recognition on financial statements.