{"title":"用于构建已发布BIM文章的本体和关联数据","authors":"Karim Farghaly","doi":"10.35490/EC3.2019.143","DOIUrl":null,"url":null,"abstract":"In the last decade, Building Information Modeling (BIM) has been of broad and great interest in both the academia and industry. Massive amounts of BIM researches have been published in academic journals, books and conference proceedings. However, more than half of the published researches are not cited, and some researches with similar questions and outputs are published. In this research, the Linked Data paradigm is utilized with ontologies to provide a structured database of the different articles of BIM and mapped to different BIM aspects in a semantically meaningful format. The proposed ontologies and Linked Data can accelerate and enhance systematic reviews and metadata analysis for future BIM studies. Also, it can assist young researchers to define the gaps that need to be filled in BIM studies and avoid repetitive researches.","PeriodicalId":126601,"journal":{"name":"Proceedings of the 2019 European Conference on Computing in Construction","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Ontologies and Linked Data for structuring published BIM articles\",\"authors\":\"Karim Farghaly\",\"doi\":\"10.35490/EC3.2019.143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the last decade, Building Information Modeling (BIM) has been of broad and great interest in both the academia and industry. Massive amounts of BIM researches have been published in academic journals, books and conference proceedings. However, more than half of the published researches are not cited, and some researches with similar questions and outputs are published. In this research, the Linked Data paradigm is utilized with ontologies to provide a structured database of the different articles of BIM and mapped to different BIM aspects in a semantically meaningful format. The proposed ontologies and Linked Data can accelerate and enhance systematic reviews and metadata analysis for future BIM studies. Also, it can assist young researchers to define the gaps that need to be filled in BIM studies and avoid repetitive researches.\",\"PeriodicalId\":126601,\"journal\":{\"name\":\"Proceedings of the 2019 European Conference on Computing in Construction\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 European Conference on Computing in Construction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35490/EC3.2019.143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 European Conference on Computing in Construction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35490/EC3.2019.143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ontologies and Linked Data for structuring published BIM articles
In the last decade, Building Information Modeling (BIM) has been of broad and great interest in both the academia and industry. Massive amounts of BIM researches have been published in academic journals, books and conference proceedings. However, more than half of the published researches are not cited, and some researches with similar questions and outputs are published. In this research, the Linked Data paradigm is utilized with ontologies to provide a structured database of the different articles of BIM and mapped to different BIM aspects in a semantically meaningful format. The proposed ontologies and Linked Data can accelerate and enhance systematic reviews and metadata analysis for future BIM studies. Also, it can assist young researchers to define the gaps that need to be filled in BIM studies and avoid repetitive researches.
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