Floor plans are essential sources for morphological studies in architectural history, offering insight into design thinking while opening to quantitative analysis. Yet, key contextual dimensions still rely heavily on the researcher’s interpretation. This study proposes a hybrid method that integrates graph-based similarity measures with human judgment to evaluate typological similarities in floor plans. We demonstrate the approach using a dataset of Dutch cross buildings, a rarely examined building type that served as community care centres. Our findings indicate that computational algorithms can capture nuanced similarity that exceeds human perceptual precision, while also revealing outliers to serve particular historical interests. Additionally, a flow-based algorithm produced numerical results that align closely with the architect's typological interpretation based on circulation. Together, these results offer new ways to understand building types, suggesting that quantitative insights can substantiate historical arguments, prompt new research questions, and extend to other building categories shaped by distinct spatial orders and use patterns. ... Read more

Purpose
This paper aims to present data refinement and enrichment workflow to integrate building performance guidelines with existing semi-structured floor layout datasets. The goal is leveraging the application of architectural datasets in the built environment across data-driven methods as well as enabling informative visualizations and large-scale analyses.

Design/methodology/approach
The Swiss dwellings dataset is employed as the foundation in this study, which later undergoes a Python-based data refinement, feature engineering and attribute extension. The modified attributes cover spatial zoning (categorical), proxy indicators for daylight metrics and view layers (numerical), noise level (numerical), acoustic comfort (categorical) and window orientations (categorical).

Findings
The study presents an efficient workflow of turning textual data of the building performance guidelines into structured tabular data suitable for machine learning. Moreover, the visualizations of the structured floor layouts data reveal new insights as a result of analyzing the dataset. The Oriented Environmental Swiss Dwellings (O-ESD) dataset, as the main product of this study, brings data-driven learning opportunities from existing floor layout datasets towards environmental design automation. Moreover, O-ESD offers human-interpretability through the structured micro-climatic visualizations.

Originality/value
There has been no previous effort in the field for upgrading the existing architectural datasets in alignment with the building performance guidelines to expand their applicability in data-driven approaches. The proposed workflow not only gives insights into data refinement applications in the field but also results in an environmentally enriched floor layout dataset as the outcome. The resulting dataset, the workflow towards it and example visualizations are released publicly. ... Read more

Architecture extends far beyond the design of buildings and cities, engaging with environmental, technological, and societal challenges. As practice evolves, so must the research that supports it. This theme track examines architecture’s expanding role in collaboration, communication, and service, positioning it as a research-driven discipline and a tool for inquiry, innovation, and responsiveness to communities and stakeholders. Operating across systems, social processes, and technological infrastructures, architecture is increasingly understood as an interdisciplinary practice. The track strengthens Architectural Design Research by addressing its evolving methodologies and its role in knowledge production. Contributions explore co-creation, artificial intelligence, data as design material, and practice-based approaches, alongside theoretical reflections on design processes. Together, the papers frame architecture as an open, relational, and collective mode of inquiry, in which architects act not as sole authors but as participants in dynamic networks of actors, tools, and knowledge. ... Read more

In the 1960s, teaching machines were the drivers of a revolutionary movement in education, the repercussions of which are still being felt today. What began as an experiment in cybernetics in think tanks and research institutions soon spread worldwide. ... Read more

Recent advancements in machine learning (ML) in architectural design led to new developments in automated generation of floor plans. However, critical evaluation of ML-based generated floor plans has not progressed proportionally due to the subjectivity and complexity of the assessment, particularly for large and more complex floor plans. Accordingly, a hybrid (quantitative and qualitative) floor plan evaluation scheme is introduced in this study, focusing on multiple architectural aspects. To verify the effectiveness of the proposed framework, the evaluation scheme is applied on the generated floor plans resulting from two baseline computer vision models. The models have been trained on a newly introduced large-scale floor plan dataset called Modified Swiss Dwellings (MSD). The results showed that despite the progression of computer vision models for floor plan generation, they still have difficulty capturing the more complex architectural qualities. In addition, the prospect of floor plan generation and evaluation and possible future developments are discussed. ... Read more

In recent years, “data” has become one of the most important aspects of architectural design. With the advent of new technologies, architects are now able to collect and analyse data about everything from building materials to weather patterns. This data can be used to create more efficient and sustainable buildings. In some cases, data can even be used to create entire new neighbourhoods or cityscapes.’ The sentences sound like a quote, one that could have come from an interview about the history of digital culture or the interconnections between architecture and technology. But as authentic as this statement sounds, it was never said. Anyone who thinks they hear the voice of an architect, computer scientist or historian is mistaken. Strictly speaking, the words do not come from a human being, but from the language software Generative Pre-Trained Transformer, GPT-3 for short. The program is the third generation of artificial intelligence, considered one of the most impressive products our digital culture has produced to date. On a timeline of disruptive technologies, it currently occupies the most current position. GPT-3 is a text generator that can write poems and dramas, provide answers to complex questions on topics such as love or trust, discuss the weather or international climate policy with us—and that has also written the short statement on the subject of ‘data and architectural design’ mentioned above. The New York Times calls the program ‘amazing, spooky, humbling and more than a little terrifying‘. [...] ... Read more

In der Epoche der Kybernetik sahen sich die Architekten mit neuen operativen Möglichkeitsräumen in technischen Systemen konfrontiert: Gebäude wurden durch Schaltdiagramme errechnet, Kreativität und Phantasie wurde die technische Intelligenz von Denkmaschinen gegenübergestellt. Im Fadenkreuz der Kybernetik befand sich der Architekt selbst. Es ging es um nichts Geringeres als das Fortbestehen seiner Autorschaft in einer technologisch-wissenschaftlichen Welt. Heute erleben wir, wie die einst so schweren Rechenmaschinen an Gewicht verlieren, doch an Macht gewinnen, wie Computer die Umwelt bevölkern, sich eigene digitale Ökosysteme schaffen und Gesellschaftsformen und Existenzweisen entstehen, die sich ohne Big Data gar nicht mehr erzählen lassen. ... Read more