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Database for serialized authorship: The case of publicplan.

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Title: Database for serialized authorship: The case of publicplan.
Authors: Brullet, Nil1 (AUTHOR), Capomaggi, Julia2 (AUTHOR), Carrera, Laura3 (AUTHOR), Santacana, Amadeu1 (AUTHOR), Devesa, Ricardo4 (AUTHOR), Gonzalvo, Carlos2 (AUTHOR), Romero, Enrique3 (AUTHOR), Ortega, Lluís1 (AUTHOR) lluis.ortega@upc.edu
Source: International Journal of Architectural Computing. Jun2025, Vol. 23 Issue 2, p533-547. 15p.
Subjects: Public housing planning & development, Databases, Machine learning, Authorship collaboration, Generative artificial intelligence, Floor plans, Data libraries
Abstract: The surge in generative AI poses a twofold challenge for architecture: crafting specialized algorithms and curating top-tier databases for machine learning. This article presents PUBLICPLAN, a database featuring social housing floor plans from recent competitions. Architecturally curated databases transcend randomness, embodying coherent compilations with recurring patterns. Historical architectural series like Mies Van der Rohe's courtyard houses, John Hejduk's Diamond series, and William J. Mitchell's Palladian Grammar are explored, highlighting the relevance of systematic approaches. Despite digital nuances, both authorial series abstraction and automated learning converge, reshaping architectural authorship paradigms. Architectural databases for AI training tap into collective intelligence, contrasting individual architect authorship. An experiment suggests assessing AI-generated floor plans' authenticity using PUBLICPLAN, seeking expert input on their human-like quality. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Architectural Computing is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Database for serialized authorship: The case of publicplan.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Architectural+Computing%22">International Journal of Architectural Computing</searchLink>. Jun2025, Vol. 23 Issue 2, p533-547. 15p.
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  Data: <searchLink fieldCode="DE" term="%22Public+housing+planning+%26+development%22">Public housing planning & development</searchLink><br /><searchLink fieldCode="DE" term="%22Databases%22">Databases</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Authorship+collaboration%22">Authorship collaboration</searchLink><br /><searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Floor+plans%22">Floor plans</searchLink><br /><searchLink fieldCode="DE" term="%22Data+libraries%22">Data libraries</searchLink>
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  Data: The surge in generative AI poses a twofold challenge for architecture: crafting specialized algorithms and curating top-tier databases for machine learning. This article presents PUBLICPLAN, a database featuring social housing floor plans from recent competitions. Architecturally curated databases transcend randomness, embodying coherent compilations with recurring patterns. Historical architectural series like Mies Van der Rohe's courtyard houses, John Hejduk's Diamond series, and William J. Mitchell's Palladian Grammar are explored, highlighting the relevance of systematic approaches. Despite digital nuances, both authorial series abstraction and automated learning converge, reshaping architectural authorship paradigms. Architectural databases for AI training tap into collective intelligence, contrasting individual architect authorship. An experiment suggests assessing AI-generated floor plans' authenticity using PUBLICPLAN, seeking expert input on their human-like quality. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Architectural Computing is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Type: general
      – SubjectFull: Databases
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      – SubjectFull: Machine learning
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      – SubjectFull: Authorship collaboration
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      – SubjectFull: Generative artificial intelligence
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      – SubjectFull: Floor plans
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      – SubjectFull: Data libraries
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      – TitleFull: Database for serialized authorship: The case of publicplan.
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              Text: Jun2025
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