Digital Twins for Energy Sovereignty: How Graph Databases and VR Training Compress Skill Transfer

Position paper proposing digital twins as instruments for energy sovereignty, combining graph database knowledge management with VR-based training to compress expertise transfer timelines. Examines how energy infrastructure digital twins can reduce dependency on foreign expertise while accelerating workforce development in renewable energy operations.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-21
DOI
https://doi.org/10.5281/zenodo.19683074
Primary Topic
Graph Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Digital Twins for Energy Sovereignty: How Graph Databases and VR Training Compress Skill Transfer

Nicolas Waern
Zenodo (CERN European Organization for Nuclear Research)
Graph Theory and Algorithms
article

Digital Twins for Energy Sovereignty: How Graph Databases and VR Training Compress Skill Transfer

Nicolas Waern
article en

Abstract

Position paper proposing digital twins as instruments for energy sovereignty, combining graph database knowledge management with VR-based training to compress expertise transfer timelines. Examines how energy infrastructure digital twins can reduce dependency on foreign expertise while accelerating workforce development in renewable energy operations.

Zenodo (CERN European Organization for Nuclear Research)
Association of British Orchestras (GB)
Affordable and clean energy
Openalex Percentile: Top 8%
Graph Theory and Algorithms
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.