Generating variety and insight from 4D networked relationships
P.A. Galwas · Zenodo (CERN European Organization for Nuclear Research) · 2022
This note collates three abstracts of papers that explore approaches to develop variety and insight arising by combining manual, semi-manual and automated analysis and transformations of network representations that conform to 4-dimensional (4D) modelling principles. We present a unified approach that can be used to model a wide range of situations and scenarios, including influence graphs (IGs), signalling & messaging, financial transactions, historic networks (e.g. provenance, family trees, audit information), plans and procedures, and legal rights on assets (e.g. for IP licensing). We build on a unified set of formal entities that can be applied across broad classes of network representations that conform to 4-dimensional modelling principles. We describe a range of semi-automated network transformations and analysis approaches, and we illustrate automating the discovery of emergent properties in such networks.