FIVE Analytics Framework: Framework for Interaction-derived Verifiable Evidence
The FIVE Analytics Framework is a domain-independent analytical framework for transforming interaction data into progressively deeper forms of verifiable evidence. It combines a three-function analytical core (observation, probabilistic estimation and causal explanation) with two mutually connected cross-cutting lenses: Semantic Intelligence and Trajectory Intelligence. Each function answers a different class of question, applies methods appropriate to that question, and carries its own validation requirements. The framework is designed so that higher analytical ambition does not erase uncertainty: every function must remain testable, auditable and open to rejection or revision. This document specifies version 1.0: a definition of verifiable evidence, the architecture, terminology, validation requirements per function, relation to existing approaches, governance principles and known limitations. It does not report empirical results.
Authors
- Sergei Naumenko (ORCID: https://orcid.org/0009-0008-8552-3973)
- Volodymyr Yefimov (ORCID: https://orcid.org/0009-0007-5589-0759)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-24
- DOI
- https://doi.org/10.5281/zenodo.22938539
- Primary Topic
- Bayesian Modeling and Causal Inference
- Type
- article
- Field-Weighted Citation Impact
- 0.00