Science of Governance
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Science of Governance is a field based on theoretical computing science and the vast experience of human interactions. It is necessary to be methodical[1] when tries to do science. For more detail, please see The Booklet. An interesting video on this subject using the language of computer science is presented by Joe Armstrong[2].
The Three Principles
There are three main principles that is necessary to set up The Science of Governance through self-administered Data.
- Improved Cycle Time of Accountable Data Refinement: Increased frequency of verification and validation for higher data resolution in spacetime, therefore high degree of trust-worthiness.
- Data-driven Accountability: All information sources have explicitly defined identity, including address information for Executable Contracts, Data Collecting Devices, and Data provisioning Agencies.
- Web-enabled Observability:Present Data COntent using one consistent data presentation and abstraction framework, so that data content can be presented using composable and reusable software components and networked display instruments, including Web3D, and Metaverse instruments with minimum application-specific engineering costs.
See Committee of Science of Governance
Formal Methods for SoG
Please see this page: Abstract Interpretation and the Science of Governance.
References
- ↑ Poincare, Henri; Maitland, Francis (2007). Combinatorial Physics. local page: New York : Cosimo Classics, ©. ISBN 9781602064485.
- ↑ Armstrong, Joe (Mar 26, 2021). "Systems that run forever self-heal and scale" by Joe Armstrong (2013). local page: Strange Loop Conference.
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