ComPara: A Corpus Linguistics Dataset of Computation in Architecture

A corpus linguistics built to study the language of computational architecture, or architecture which focuses on technology developments. The corpus includes: (1) the volume titles, titles of articles and introduction keywords for the journal Architectural Design (AD) to retrieve keynotes in theoretical discourse, and (2) titles and abstracts of winning and honourable mentions of the eVolo Skyscraper competition to retrieve words in conceptual project titles and their descriptions. This dataset has around 100.000 words and can serve as a basis for quantitative, qualitative or mixed method analysis of the language used in AD and the eVolo skyscraper competition between 2005 and 2019. As AD is recognized as one of the journals focusing on the 'digital turns' in architecture, and eVolo is a the most prestigious architectural competitions which focus on technological advances in architetcure, ComPara can be considered respresentative for the language of computational architecture over the last 15 years. It includes .txt and .csv files as well as .svg and wordclouds

ComPara: A Corpus Linguistics Dataset of Computation in Architecture

A corpus linguistics built to study the language of computational architecture, or architecture which focuses on technology developments. The corpus includes (1) the volume titles, titles of articles, and keywords associated with the Introduction article of the journal Architectural Design (AD) to retrieve the language in the theoretical discourse around computation in architecture, and (2) titles and abstracts of winning and honorable mentions of the eVolo Skyscraper competition to retrieve words in conceptual project titles and their descriptions. This dataset has around 100.000 words and can serve as a basis for quantitative, qualitative, or mixed-method analysis of the language used in AD and the eVolo skyscraper competition between 2005 and 2019. As AD is recognized as one of the journals focusing on the 'digital turns' in architecture, and eVolo is arguably the most prestigious architectural competition which focuses on technological advances in architecture, ComPara can be considered representative of the language of computational architecture between 2005 and 2019. It includes .txt and .csv files as well as .svg wordclouds

Annotated point clouds of buildings: a segmented dataset of single-family houses

The dataset contains 2.904 geometries of single-family houses in the form of annotated Point Clouds, and was developed in order to train 3D Generative Adversarial Networks. The geometries are segmented within 3 classes: wall, roof, floor. The points of the point clouds are saved in .pts files while their labels are saved in .seg files. The creation of the dataset was done in a semi-automated way that consists of two stages: a) creation of module geometries representing building components (done in Rhino3D) b) the conversion of the geometries into Point Clouds with the Cockroach plug-in. 25 wall modules and 35 roof modules were created. Each wall module was combined with each roof module. Data augmentation methods were applied to maximize the size of the dataset: the modules were scaled in 3 ranges, and rotated 90 degrees for a wider feature space. The dataset can be used to train 3D GANs with architecturally relevant data. Connected publication describing a use case of this dataset to follow