Rome 1,2,4{d.simeone|s.cursi|um.coraglia}@aec-agency.com 3antonio.fioravanti@uniroma1. it Although HBIM is nowadays a common practice in processes and activities aimed at the investigation, documentation and conservation of architectural heritage, some doubts are emerging regarding its capabilities of fulfilling architectural heritage representation and semantics requirements. In this context, this work presents Open-ArcH, a digital approach for architectural heritage representation that relies on the integration of HBIM methodology with a knowledge base developed by means of graph databases, with two major objectives: 1) it supports the formalization of the complex semantics that it is necessary for a full comprehension of the artefact, currently poorly managed by HBIM application, and 2) the openness and flexibility ensured by the graph database technology allow for its adoption in heritage investigation and conservation processes by the different actors involved, providing them with the capability of collaborating to the construction of the knowledge base of the artefact.
| Authors | Davide Simeone and Stefano Cursi and Antonio Fioravanti and Ugo Maria Coraglia |
|---|---|
| Year | 2021 |
| Venue | Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe |
| DOI | 10.52842/CONF.ECAADE.2021.2.253 |
| Source Database | Seed (CumInCAD) |
| Bridge-to-GNN | Category Seed |
| GNN Architecture | Not yet extracted from PDF |
| Graph Encoding | Not yet extracted from PDF |
| AEC Task | Knowledge Graph Construction (inferred from title) |
| Cohort | Early Infrastructure (2020–2021) |
| Implementation Framework | Revit / Dynamo, Neo4j (heuristic — verify) |
|---|---|
| Primary Metric | Accuracy (heuristic — verify) |
| Quality Assessment | 1/6 · rigor: Low · Baseline: ✓ (heuristic — verify) |
| GNN architectures detected | Knowledge Graph Embedding (TransE/RotatE/DistMult) |
|---|---|
| Frameworks / libraries | Revit / Dynamo · Neo4j / Cypher · 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