https://github.com/aaronpeikert/fair-theory

Represent theories as digital objects, attach metadata and version control them, and you have a FAIR Theory.
https://github.com/aaronpeikert/fair-theory

Last synced: 2 months ago
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Represent theories as digital objects, attach metadata and version control them, and you have a FAIR Theory.

• Host: GitHub
• URL: https://github.com/aaronpeikert/fair-theory
• Owner: aaronpeikert
• Created: 2024-01-25T12:08:09.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-09-12T11:02:12.000Z (8 months ago)
• Last Synced: 2024-10-21T20:19:57.662Z (7 months ago)
• Language: TeX
• Homepage: https://aaronpeikert.github.io/FAIR-Theory/
• Size: 3.78 MB
• Stars: 0
• Watchers: 1
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# To be FAIR: Theory Development Needs an Update

We introduce the concept of FAIR theories, reimagining theories as

dynamic, evolving entities collaboratively developed and refined, thus

contributing to a more robust and interconnected body of scientific

knowledge. Theories help to structure and condense the existing

scientific knowledge, yet their development often lacks structure. We

propose FAIR theories, hoping that a more structured approach to theory

development enables more cumulative science. Central to our proposal is

representing theories as digital objects expressed in formal languages,

such as formulas, mathematical/statistical models, computer programs,

nomological networks, or operational definitions. However, digital

representation is not enough; in our framework, the theory’s history is

tracked using version control and semantic versioning, and the relation

between theories with universally unique identifiers. Combining these

identifiers with rich metadata makes a FAIR theory Findable; tracking it

via version control makes it Accessible; the formal language makes it

Interoperable; and well-defined procedures for changing and amending

theories make it Reusable. FAIR theories facilitate metascientific

insights into the evolution of theories and their empirical support,

ultimately enabling theory curation. Moving forward, we envision

theories undergoing “integration tests against reality”, paralleling

continuous integration in software development by continuously

evaluating the empirical foundations of theories, akin to living

meta-analyses. This presentation addresses the guiding principles of

FAIR theory and provides specific implementation examples.