对现有建筑进行数字化建模的新兴本体论:对京都锦市场的考察

Mike Christenson
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引用次数: 0

摘要

目的 本项目研究现有建筑的数字建模策略。在此背景下,它旨在质疑有关几何精度需求和预定义本体有效性的假设。作为对现行数字建模策略的反驳,该项目提出了一种使用特定项目的新兴本体的数字建模方法。新兴本体建模过程中引入了一套初始的最小操作,包括适用于表面的基本折叠和修剪操作。随着模型的迭代发展,会遇到现有规则不足以应对的新情况。结果在 Nishiki Market 测试案例中执行的新兴本体方法能够表现特定的建筑质量,突出现实世界特征的数字模型元素之间的语义区别。建模方法产生了项目特定的知识,为学科理解提供了信息。本体论的出现使语义关系得以披露和新构建。原创性/价值该项目提出了一种新颖的方法论,使用本体论对现有建筑进行数字化建模。模型制作者的主观决定决定了模型的持续发展,而不是局限于预定义的本体。这种解释性方法允许生成针对特定项目的知识,同时对现有建筑数字模型的准确性和一致性提出了挑战。
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An emergent ontology for digitally modeling existing buildings: examining Kyoto’s Nishiki market
PurposeThis project examines digital modeling strategies for existing buildings. In this context, it aims to question assumptions about the need for geometric accuracy and the efficacy of predefined ontologies. As a counterpoint to prevailing digital modeling strategies, this project proposes a digital modeling approach using a project-specific, emergent ontology.Design/methodology/approachNishiki Market, in Kyoto, Japan, is studied as a test case. The emergent-ontology modeling process is introduced with an initial minimal set of operations including basic fold and trim operations applicable to surfaces. As the model develops iteratively, new situations are encountered for which existing rules are insufficient. In response, the model maker’s subjective judgment is invoked to introduce new operations, and ontological rules are allowed to expand.FindingsThe emergent-ontology approach, when executed on the Nishiki Market test case, enables representation of specific architectural qualities, highlighting semantic distinctions between digitally modeled elements of real-world features. The modeling approach generated project-specific knowledge, informing disciplinary understanding. Ontological emergence enabled semantic relationships to be disclosed and newly constructed.Originality/valueThe project proposes a novel methodology using an emergent ontology for digitally modeling existing buildings. Instead of remaining within the limitations a predefined ontology, the model maker’s subjective decisions shape the model’s ongoing development. This interpretive approach allows project-specific knowledge generation while challenging prevailing assumptions about accuracy and consistency in digital models of existing buildings.
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