Back to Wiki

[41] Knowledge Graphs' Ontologies and Applications for Energy Efficiency in Buildings: A Review

EBSCO – Screened Energy Estimation & Digital Twins 2022

Paper Description extracted from PDF · abstract · 139 words

The Architecture, Engineering and Construction (AEC) industry has been utilizing Decision Support Systems (DSSs) for a long time to support energy efficiency improvements in the different phases of a building’s life cycle. In this context, there has been a need for a proper means of exchanging and managing of different kinds of data (e.g., geospatial data, sensor data, 2D/3D models data, material data, schedules, regulatory, financial data) by different kinds of stakeholders and end users, i.e., planners, architects, engineers, property owners and managers. DSSs are used to support various processes inherent in the various building life cycle phases including planning, design, construction, operation and maintenance, retrofitting and demolishing. Such tools are in some cases based on established technologies such Building Information Models, Big Data analysis and other more advanced approaches, including Internet of Things applications and semantic web technologies.

AuthorsLygerakis, Filippos and Kampelis, Nikos and Kolokotsa, Dionysia
Year2022
VenueEnergies (19961073)
DOI10.3390/en15207520
Source DatabaseEBSCO (Academic Search Ultimate)
Bridge-to-GNNCategory C
GNN ArchitectureGNN (heuristic — verify)
Graph EncodingKnowledge Graph / Ontological Network (inferred from title)
AEC TaskEnergy Estimation (inferred from title)
CohortPeak Adoption (2022)

Extracted Methodology heuristic — verify before citing

Dataset Size34 models (heuristic — verify)
Implementation FrameworkOWL / SPARQL (heuristic — verify)
Quality Assessment3/6 · rigor: Medium ·
Code/Data: ✓Benchmark: ✓Baseline: ✓ (heuristic — verify)

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

GNN architectures detectedKnowledge Graph Embedding (TransE/RotatE/DistMult)
Frameworks / librariesEnergyPlus · OpenStudio · RDF / OWL / SPARQL
Benchmark datasets referencedPubMed · CityGML
Code repositories found in texthttps://github.com/google/digitalbuildings
Dataset stats found34 models
Quality (heuristic, 6-flag)2/6 · rigor: Low
Code/Data: ✓Benchmark: ✓Baseline: —CV/Split: —Ablation: —Reproducible: —

Connected Papers Verification bibliometric (data/connected_papers_matches.json)

Bibliometrically related to other seedsThis paper appeared in the Connected Papers neighbourhood of these corpus seeds:

[3] 2023 · Zhao · Design-condition-informed shear wall layout design based…
[77] 2020 · Chang · Learning to Simulate and Design for Structural Engineering

Lineage Families

energy-digital-twin

Enabled By / Precursors

[36]

Extended By

None in corpus

Infrastructure Dependencies

BIM Knowledge Graph (RDF/OWL/SPARQL) (auto-suggested) EnergyPlus (detected from PDF) OpenStudio (detected from PDF) RDF / OWL / SPARQL (detected from PDF)

Research Frontier Tags

knowledge-graph energy-estimation

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