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Pieter Herthogs
Singapore-ETH Centre, CREATE Tower, 1 Create Way, Singapore, 138602, Singapore

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Journal article
Published: 29 July 2021 in Energy and AI
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This paper presents a dynamic geospatial knowledge graph as part of The World Avatar project, with an underlying ontology based on CityGML 2.0 for three-dimensional geometrical city objects. We comprehensively evaluated, repaired and refined an existing CityGML ontology to produce an improved version that could pass the necessary tests and complete unit test development. A corresponding data transformation tool, originally designed to work alongside CityGML, was extended. This allowed for the transformation of original data into a form of semantic triples. We compared various scalable technologies for this semantic data storage and chose Blazegraph™ as it provided the required geospatial search functionality. We also evaluated scalable hardware data solutions and file systems using the publicly available CityGML 2.0 data of Charlottenburg in Berlin, Germany as a working example. The structural isomorphism of the CityGML schemas and the OntoCityGML Tbox allowed the data to be transformed without loss of information. Efficient geospatial search algorithms allowed us to retrieve building data from any point in a city using coordinates. The use of named graphs and namespaces for data partitioning ensured the system performance stayed well below its capacity limits. This was achieved by evaluating scalable and dedicated data storage hardware capable of hosting expansible file systems, which strengthened the architectural foundations of the target system.

ACS Style

Arkadiusz Chadzynski; Nenad Krdzavac; Feroz Farazi; Mei Qi Lim; Shiying Li; Ayda Grisiute; Pieter Herthogs; Aurel von Richthofen; Stephen Cairns; Markus Kraft. Semantic 3D City Database — An enabler for a dynamic geospatial knowledge graph. Energy and AI 2021, 6, 100106 .

AMA Style

Arkadiusz Chadzynski, Nenad Krdzavac, Feroz Farazi, Mei Qi Lim, Shiying Li, Ayda Grisiute, Pieter Herthogs, Aurel von Richthofen, Stephen Cairns, Markus Kraft. Semantic 3D City Database — An enabler for a dynamic geospatial knowledge graph. Energy and AI. 2021; 6 ():100106.

Chicago/Turabian Style

Arkadiusz Chadzynski; Nenad Krdzavac; Feroz Farazi; Mei Qi Lim; Shiying Li; Ayda Grisiute; Pieter Herthogs; Aurel von Richthofen; Stephen Cairns; Markus Kraft. 2021. "Semantic 3D City Database — An enabler for a dynamic geospatial knowledge graph." Energy and AI 6, no. : 100106.

Chapter
Published: 12 May 2020 in Smart and Sustainable Cities and Buildings
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Good public space is an inherent part of liveable cities. However, due to the complexity and ambiguity of the concept of public space quality, capturing essential characteristics to assess the quality of public space in a quantitative framework is not straightforward. In this paper, we introduce the Public Space Quality Index (PSQI), a Multi-Criteria Decision Analysis (MCDA) based framework to measure the quality of public space in a systematic manner. This paper discusses the development of our research methodology, which includes four key phases: criteria selection, criteria ranking and weighting, criteria quantification, and criteria aggregation. We also present the results of the first phase, and discuss the main findings from an expert workshop we conducted with Singapore-based urban design professionals, as a validation and learning moment for our past and future work, respectively.

ACS Style

Peijun He; Pieter Herthogs; Marco Cinelli; Ludovica Tomarchio; Bige Tunçer. A Multi-Criteria Decision Analysis Based Framework to Evaluate Public Space Quality. Smart and Sustainable Cities and Buildings 2020, 271 -283.

AMA Style

Peijun He, Pieter Herthogs, Marco Cinelli, Ludovica Tomarchio, Bige Tunçer. A Multi-Criteria Decision Analysis Based Framework to Evaluate Public Space Quality. Smart and Sustainable Cities and Buildings. 2020; ():271-283.

Chicago/Turabian Style

Peijun He; Pieter Herthogs; Marco Cinelli; Ludovica Tomarchio; Bige Tunçer. 2020. "A Multi-Criteria Decision Analysis Based Framework to Evaluate Public Space Quality." Smart and Sustainable Cities and Buildings , no. : 271-283.

Journal article
Published: 20 April 2019 in Buildings
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This paper presents an assessment method that uses weighted graphs to quantify a building’s capacity to support changes. The method is called Spatial Assessment of Generality and Adaptability (SAGA), and evaluates the generality (passive support for change) and adaptability (active support for change) of a building’s spatial configuration. We put forward that the generality and adaptability of a floor plan can be expressed in terms of graph permeability, and introduce a set of five quantitative indicators. To illustrate the method, we evaluate six representative plan layouts, and discuss how their generality and adaptability scores relate to their spatial configuration. We are developing the SAGA method for two areas of application. First, SAGA’s global graph indicators can be used to analyse and compare large sets of plan graphs, for example to map or plan adaptable capacity throughout a building or city. Second, the SAGA method can serve as a tool to inform design, allowing architects to improve the generality and adaptability of their plan layouts. While we conclude that the method has significant strengths and promising applications, the paper ends by discussing ways to make the assessment more robust and extend it beyond measuring spatial configuration.

ACS Style

Pieter Herthogs; Wim Debacker; Bige Tunçer; Yves De Weerdt; Niels De Temmerman. Quantifying the Generality and Adaptability of Building Layouts Using Weighted Graphs: The SAGA Method. Buildings 2019, 9, 92 .

AMA Style

Pieter Herthogs, Wim Debacker, Bige Tunçer, Yves De Weerdt, Niels De Temmerman. Quantifying the Generality and Adaptability of Building Layouts Using Weighted Graphs: The SAGA Method. Buildings. 2019; 9 (4):92.

Chicago/Turabian Style

Pieter Herthogs; Wim Debacker; Bige Tunçer; Yves De Weerdt; Niels De Temmerman. 2019. "Quantifying the Generality and Adaptability of Building Layouts Using Weighted Graphs: The SAGA Method." Buildings 9, no. 4: 92.