Difference between revisions of "A computable framework for accountable data assets"
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=Synoposis= | =Synoposis= | ||
This article prescribes an algebraic approach to manipulate | This article prescribes an algebraic approach to manipulate data content in a unifying data abstraction framework. For non-mathematicians, this computational framework can be thought of as an accounting system that can be formally extended to serve a wide range of applications. | ||
=Introduction= | =Introduction= | ||
Revision as of 05:06, 12 May 2022
Synoposis
This article prescribes an algebraic approach to manipulate data content in a unifying data abstraction framework. For non-mathematicians, this computational framework can be thought of as an accounting system that can be formally extended to serve a wide range of applications.
Introduction
The goal of our computational framework is to automate the decision procedures for the following activities:
- Decide how to classify the data collected and send the collected data to relevant data processing workflows.
- Whether a given data set is considered admissible or not. This is judged in terms of its data formats and legal value ranges.
- Whether a transaction process is allowable, or not. This include whether a given transaction is feasible, in relevant operational/business logics.
Ownership associated with Accounts
Data Content that represent Decision Procedures
The Control Structure(If/Then/Else)
Computable Data Types
It is been defined axiomatically that all computable data types are Partially-ordered sets.