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[96] Open-ArcH: An open knowledge-based system for architectural heritage representation

Seed Paper Seed Paper (General / Unclassified) 2021

Paper Description extracted from PDF · intro excerpt · 146 words

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.

AuthorsDavide Simeone and Stefano Cursi and Antonio Fioravanti and Ugo Maria Coraglia
Year2021
VenueProceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe
DOI10.52842/CONF.ECAADE.2021.2.253
Source DatabaseSeed (CumInCAD)
Bridge-to-GNNCategory Seed
GNN ArchitectureNot yet extracted from PDF
Graph EncodingNot yet extracted from PDF
AEC TaskKnowledge Graph Construction (inferred from title)
CohortEarly Infrastructure (2020–2021)

Extracted Methodology heuristic — verify before citing

Implementation FrameworkRevit / Dynamo, Neo4j (heuristic — verify)
Primary MetricAccuracy (heuristic — verify)
Quality Assessment1/6 · rigor: Low ·
Baseline: ✓ (heuristic — verify)

Detected Technical Stack auto-detected from PDF · regex catalogue match

GNN architectures detectedKnowledge Graph Embedding (TransE/RotatE/DistMult)
Frameworks / librariesRevit / Dynamo · Neo4j / Cypher · RDF / OWL / SPARQL
Quality (heuristic, 6-flag)0/6 · rigor: Low
Code/Data: —Benchmark: —Baseline: —CV/Split: —Ablation: —Reproducible: —

Lineage Families

None assigned

Enabled By / Precursors

None tracked

Extended By

None in corpus

Infrastructure Dependencies

Revit / Dynamo (detected from PDF) Neo4j / Cypher (detected from PDF) RDF / OWL / SPARQL (detected from PDF)

Research Frontier Tags

graph-ml-aec

Part of the GML/GNN in AEC Systematic Review (PRISMA 2020) — 112 papers, 2020–2026