| id |
caadria2022_196 |
| authors |
Grisiute, Ayda, Shi, Zhongming, Chadzynski, Arkadiusz, Silvennoinen, Heidi, von Richthofen, Aurel and Herthogs, Pieter |
| year |
2022 |
| title |
Automated Semantic SWOT Analysis for City Planning Targets: Data-driven Solar Energy Potential Evaluations for Building Plots in Singapore |
| doi |
https://doi.org/10.52842/conf.caadria.2022.1.555
|
| source |
Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 555-564 |
| summary |
Singapore‚s urban planning and management is cross-domain in nature and need to be assessed using multi-domain indicators ‚ such as SDGs. However, urban planning processes are often confronted with data interoperability issues. In this paper, we demonstrate how a Semantic Web Technology-based approach combined with a SWOT analysis framework can be used to develop an architecture for automated multi-domain evaluations of SDG-related planning targets. This paper describes an automated process of storing heterogeneous data in a semantic data store, deriving planning metrics and integrating a SWOT framework for the multi-domain evaluation of on-site solar energy potential across plots in Singapore. Our goal is to form the basis for a more comprehensive planning support tool that is based on a reciprocal relationship between innovations in SWT and a versatile SWOT framework. The presented approach has many potential applications beyond the presented energy potential evaluation. |
| keywords |
Semantic Web, Knowledge Graphs, SWOT analysis, energy-driven urban design, SDG 11, SDG 7 |
| series |
CAADRIA |
| email |
|
| full text |
 file.pdf (800,469 bytes) |
| references |
Content-type: text/plain
|
Akroyd, J., Mosbach, S., Bhave, A. & Kraft, M. (2021)
 Universal Digital Twin—A Dynamic Knowledge Graph
, Data-Centric Engineering, 2
|
|
|
|
|
Chadzynski, A., Krdzavac, N., Farazi, F., Lim, M. Q., Li, S., Grisiute, A., Herthogs, P., et al. (2021)
Semantic 3D City Database—An enabler for a dynamic geospatial knowledge graph
, Energy and AI, 6, 100106
|
|
|
|
|
Chadzynski, A., Li, S., Grisiute, A., Farazi, F., Lindberg, C., Mosbach, S., Herthogs, P., et al. (2021)
Semantic 3D City Agents—An intelligent automation for Dynamic Geospatial Knowledge Graphs
, c4e-Preprint Series. Cambridge
|
|
|
|
|
Comino, E. & Ferretti, V. (2016)
Indicators-based spatial SWOT analysis: Supporting the strategic planning and management of complex territorial systems
, Ecological Indicators, 60, 1104–1117
|
|
|
|
|
Eibeck, A., Chadzynski, A., Lim, M. Q., Aditya, K., Ong, L., Devanand, A., Karmakar, G., et al. (2020)
A Parallel World Framework for scenario analysis in knowledge graphs
, Data-Centric Engineering, 1
|
|
|
|
|
Ervural, B. C., Zaim, S., Demirel, O. F., Aydin, Z. & Delen, D. (2018)
An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning
, Renewable and Sustainable Energy Reviews, 82, 1538–1550
|
|
|
|
|
Ghazinoory, S., Abdi, M. & Azadegan-Mehr, M. (2011)
SWOT methodology: A state-of-the-art review for the past, a framework for the future
, Journal of Business Economics and Management, 12(1), 24–48
|
|
|
|
|
Grisiute, A., Silvennoinen, H., Shi, Z., Chadzynski, A., Li, S., Lim, M. Q., Sielker, F., et al. (2021)
Creating multi-domain urban planning indicators using a knowledge graph: A district energy use case in Singapore
, Presented at the International Conference on Evolving Cities, Southampton, UK
|
|
|
|
|
Learned, E. P., Christensen, C., Andrews, R. S. & Guth, D. (1965)
Business policy: Text and cases
, Irwin Publishers
|
|
|
|
|
Massaro, E., Athanassiadis, A., Psyllidis, A. & Binder, C. R. (2020)
Ontology-Based Integration of Urban Sustainability Indicators
, C. R. Binder, E. Massaro, & R. Wyss (Eds.), Sustainability Assessment of Urban Systems (pp. 332–350). Cambridge University Press
|
|
|
|
|
Richthofen, A., Herthogs, P., Kraft, M. & Cairns, S. (2022)
Semantic City Planning Systems (SCPS): A Literature Review
, Journal of Planning Literature, 08854122211068526
|
|
|
|
|
Shi, Z., Fonseca, J. A. & Schlueter, A. (2017)
A review of simulation-based urban form generation and optimization for energy-driven urban design
, Building and Environment, 121, 119–129
|
|
|
|
|
Shi, Z., Fonseca, J. A. & Schlueter, A. (2021)
A parametric method using vernacular urban block typologies for investigating interactions between solar energy use and urban design
, Renewable Energy, 165, 823–841
|
|
|
|
|
Shi, Z., Herthogs, P., Li, S., Chadzynski, A., Lim, M. Q., Richthofen, A. V., Cairns, S., et al. (2021)
Land Use Type Allocation Informed by Urban Energy Performance: A Use Case for a Semantic-Web Approach to Master Planning
, The 26th International Conference of the Association for Computer-Aided Architectural Design Research in Asia, CAADRIA 2021 (Vol. 2, pp. 679–688)
|
|
|
|
|
Shi, Z., Hsieh, S., Fonseca, J. A. & Schlueter, A. (2020)
Street grids for efficient district cooling systems in high-density cities
, Sustainable Cities and Society, 60, 102224
|
|
|
|
|
White, T. H., de Melo Barros, Y., Develey, P. F., Llerandi-Román, I. C., Monsegur-Rivera, O. A. & Trujillo-Pinto, A. M. (2015)
Improving reintroduction planning and implementation through quantitative SWOT analysis
, Journal for Nature Conservation, 28, 149–159
|
|
|
|
|
Winkelhake, U. (2018)
The Digital Transformation of the Automotive Industry
, Springer International Publishing
|
|
|
|
|
Zhou, X., Eibeck, A., Lim, M. Q., Krdzavac, N. B. & Kraft, M. (2019)
An agent composition framework for the J-Park Simulator—A knowledge graph for the process industry
, Computers & Chemical Engineering, 130, 106577
|
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| last changed |
2022/07/22 07:34 |
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