Blockchain Data Validation for Reporting Consistency
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Solution Overview
Problem
Different organizations often disagree on data reporting due to favorable reporting practices, leading to miscommunication, conflicts, and lack of trust, especially in globalized environments where slight changes in metrics or display formats can cause confusion.
Innovation Solution
A distributed ledger system, such as a blockchain, is used to store data analysis and visualization parameters in a mutually agreed format, ensuring consistency and transparency by enforcing pre-determined rules and allowing for dispute resolution if parameters are not compliant.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations use favorable reporting practices to present data in a positive light, then organizational interests are protected, but data consistency and trust among parties deteriorate
Solution Approach 1:
The system performs preliminary validation of data analysis and visualization parameters against pre-determined rules before storing them in the distributed ledger. This advance checking ensures that only compliant parameters are recorded, preventing future inconsistencies while maintaining organizational flexibility within established boundaries.
Solution Approach 2:
The system provides feedback by validating reported parameters against pre-determined rules and performing corrective actions when inconsistencies are detected. This feedback mechanism ensures data consistency across organizations while allowing each organization to maintain its reporting flexibility within the agreed-upon framework.
2Adaptability or versatility
If data analysis and visualization parameters are allowed to vary by organization, then organizational autonomy is maintained, but data consistency and transparency worsen
Solution Approach 1:
The system segments the reporting framework into two distinct layers: pre-determined rules stored in the distributed ledger that ensure consistency and transparency, and organizational-specific data analysis and visualization parameters that maintain autonomy. This segmentation allows each organization to operate independently while adhering to common standards.
Solution Approach 2:
The distributed ledger acts as an intermediary that stores pre-determined rules and validates organizational parameters. This intermediary ensures transparency and consistency without restricting organizational autonomy, as it merely checks compliance rather than controlling the actual reporting parameters.
3Reliability
If pre-determined rules are enforced in a distributed ledger, then data consistency is improved, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically validating data analysis and visualization parameters against pre-determined rules stored in the distributed ledger. This automated validation reduces the need for manual intervention and complex coordination mechanisms, thereby improving data consistency without proportionally increasing system complexity.
Data Source
AI summary
In an approach to achieving consistent reporting, one or more processors receive a request to include a set of data analysis and visualization parameters in a distributed ledger, such as the blockchain fabric distributed ledger. One or more processors may determine whether the set of data analysis and visualization parameters is consistent with a set of pre-determined rules recorded in the distributed ledger. One or more processors may additionally perform a corrective action for the set of data analysis and visualization parameters responsive to determining that the set of data analysis and visualization parameters is not consistent with the set of pre-determined rules recorded in the distributed ledger. One or more processors may further store the set of data analysis and visualization parameters in the distributed ledger and generate a report of a first dataset based on the set of data analysis and visualization parameters.


