This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, interlinked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph.
| Authors | Eibeck, A.; Lim, M. Q.; Kraft, M. |
|---|---|
| Year | 2020 |
| Venue | Data-Centric Engineering |
| DOI | 10.1017/dce.2020.6 |
| Source Database | Backtracking |
| Bridge-to-GNN | Category C |
| GNN Architecture | Knowledge Graph Embedding (inferred from title) |
| Graph Encoding | Knowledge Graph / Ontological Network (inferred from title) |
| AEC Task | Knowledge Graph Construction (inferred from title) |
| Cohort | Early Infrastructure (2020–2021) |
| Implementation Framework | OWL / SPARQL (heuristic — verify) |
|---|---|
| Primary Metric | Mean Average Precision (mAP) (heuristic — verify) |
| Key Finding | more specific technological choices made within the system to handle data serialization, storage, and communication protocols (heuristic — verify) |
| GNN architectures detected | Knowledge Graph Embedding (TransE/RotatE/DistMult) |
|---|---|
| Frameworks / libraries | RDF / OWL / SPARQL |
| Quality (heuristic, 6-flag) | 0/6 · rigor: Low Code/Data: —Benchmark: —Baseline: —CV/Split: —Ablation: —Reproducible: — |
Part of the GML/GNN in AEC Systematic Review (PRISMA 2020) — 112 papers, 2020–2026