Zaiyang Ma , Hengyue Li , Kai Zhang , Jin Wang , Songshan Yue , Yongning Wen , Guonian Lü , Min Chen
{"title":"在城市仿真计算过程中共同创造知识,实现更广泛的参与","authors":"Zaiyang Ma , Hengyue Li , Kai Zhang , Jin Wang , Songshan Yue , Yongning Wen , Guonian Lü , Min Chen","doi":"10.1016/j.scs.2024.105994","DOIUrl":null,"url":null,"abstract":"<div><div>Preparing knowledge on urban simulation computation is necessary to help participants build consensus, reduce expertise gaps, and guide participatory sustainable urban planning. Knowledge co-creation is an effective way to prepare the needed knowledge related to urban simulation computation. However, the procedural and operational information that can help instruct the implementation of urban simulation is extensively hidden in the implementation processes of urban simulation in various forms (e.g., dialog records, configuration parameters, and model operations). Difficulties remain in extracting this implicit information and synthesizing the related knowledge. Therefore, a strategy is proposed to support the co-creation of knowledge during the urban simulation computation. In this strategy, the structural knowledge expression methods are first designed to support information extraction and knowledge synthesis. Based on interaction tracking and natural language understanding techniques, the related information can be obtained from simulation computation processes. Using this information, four main types of knowledge can be generated, optimized and visualized to assist collaborative urban simulation practices. This strategy was implemented in an online collaboration prototype system and verified with two sustainable urban case studies involving the simulation of urban noise environments and solar radiation assessment of photovoltaic noise barriers in cities. The results show that the knowledge co-creation can be effectively implemented by using the information extracted from simulation computation processes, which can benefit broader collaboration in urban simulation and sustainable urban planning.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"118 ","pages":"Article 105994"},"PeriodicalIF":10.5000,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Knowledge co-creation during urban simulation computation to enable broader participation\",\"authors\":\"Zaiyang Ma , Hengyue Li , Kai Zhang , Jin Wang , Songshan Yue , Yongning Wen , Guonian Lü , Min Chen\",\"doi\":\"10.1016/j.scs.2024.105994\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Preparing knowledge on urban simulation computation is necessary to help participants build consensus, reduce expertise gaps, and guide participatory sustainable urban planning. Knowledge co-creation is an effective way to prepare the needed knowledge related to urban simulation computation. However, the procedural and operational information that can help instruct the implementation of urban simulation is extensively hidden in the implementation processes of urban simulation in various forms (e.g., dialog records, configuration parameters, and model operations). Difficulties remain in extracting this implicit information and synthesizing the related knowledge. Therefore, a strategy is proposed to support the co-creation of knowledge during the urban simulation computation. In this strategy, the structural knowledge expression methods are first designed to support information extraction and knowledge synthesis. Based on interaction tracking and natural language understanding techniques, the related information can be obtained from simulation computation processes. Using this information, four main types of knowledge can be generated, optimized and visualized to assist collaborative urban simulation practices. This strategy was implemented in an online collaboration prototype system and verified with two sustainable urban case studies involving the simulation of urban noise environments and solar radiation assessment of photovoltaic noise barriers in cities. The results show that the knowledge co-creation can be effectively implemented by using the information extracted from simulation computation processes, which can benefit broader collaboration in urban simulation and sustainable urban planning.</div></div>\",\"PeriodicalId\":48659,\"journal\":{\"name\":\"Sustainable Cities and Society\",\"volume\":\"118 \",\"pages\":\"Article 105994\"},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2024-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Cities and Society\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210670724008187\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724008187","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Knowledge co-creation during urban simulation computation to enable broader participation
Preparing knowledge on urban simulation computation is necessary to help participants build consensus, reduce expertise gaps, and guide participatory sustainable urban planning. Knowledge co-creation is an effective way to prepare the needed knowledge related to urban simulation computation. However, the procedural and operational information that can help instruct the implementation of urban simulation is extensively hidden in the implementation processes of urban simulation in various forms (e.g., dialog records, configuration parameters, and model operations). Difficulties remain in extracting this implicit information and synthesizing the related knowledge. Therefore, a strategy is proposed to support the co-creation of knowledge during the urban simulation computation. In this strategy, the structural knowledge expression methods are first designed to support information extraction and knowledge synthesis. Based on interaction tracking and natural language understanding techniques, the related information can be obtained from simulation computation processes. Using this information, four main types of knowledge can be generated, optimized and visualized to assist collaborative urban simulation practices. This strategy was implemented in an online collaboration prototype system and verified with two sustainable urban case studies involving the simulation of urban noise environments and solar radiation assessment of photovoltaic noise barriers in cities. The results show that the knowledge co-creation can be effectively implemented by using the information extracted from simulation computation processes, which can benefit broader collaboration in urban simulation and sustainable urban planning.
期刊介绍:
Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including:
1. Smart cities and resilient environments;
2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management;
3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management);
4. Energy efficient, low/zero carbon, and green buildings/communities;
5. Climate change mitigation and adaptation in urban environments;
6. Green infrastructure and BMPs;
7. Environmental Footprint accounting and management;
8. Urban agriculture and forestry;
9. ICT, smart grid and intelligent infrastructure;
10. Urban design/planning, regulations, legislation, certification, economics, and policy;
11. Social aspects, impacts and resiliency of cities;
12. Behavior monitoring, analysis and change within urban communities;
13. Health monitoring and improvement;
14. Nexus issues related to sustainable cities and societies;
15. Smart city governance;
16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society;
17. Big data, machine learning, and artificial intelligence applications and case studies;
18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems.
19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management;
20. Waste reduction and recycling;
21. Wastewater collection, treatment and recycling;
22. Smart, clean and healthy transportation systems and infrastructure;