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

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-24
DOI
https://doi.org/10.5281/zenodo.22938538
Primary Topic
Bayesian Modeling and Causal Inference
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

FIVE Analytics Framework: Framework for Interaction-derived Verifiable Evidence

Sergei Naumenko, Volodymyr Yefimov
Zenodo (CERN European Organization for Nuclear Research)
Bayesian Modeling and Causal Inference
article

FIVE Analytics Framework: Framework for Interaction-derived Verifiable Evidence

Sergei Naumenko, Volodymyr Yefimov
article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 9%
Bayesian Modeling and Causal Inference
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.