{"data":{"id":"10.4121/d8a5eb90-0269-4a4b-b672-f1dd9b351836","type":"dois","attributes":{"doi":"10.4121/d8a5eb90-0269-4a4b-b672-f1dd9b351836","prefix":"10.4121","suffix":"d8a5eb90-0269-4a4b-b672-f1dd9b351836","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Mostafavi, Fatemeh","nameType":"Personal","givenName":"Fatemeh","familyName":"Mostafavi","nameIdentifiers":[{"nameIdentifier":"0000-0002-8047-2168","nameIdentifierScheme":"https://orcid.org/"}],"affiliation":[]},{"name":"Khademi, Seyran","givenName":"Seyran","familyName":"Khademi","affiliation":[],"nameIdentifiers":[]},{"name":"Vrachliotis, Georg","givenName":"Georg","familyName":"Vrachliotis","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Oriented-Environmental Swiss Dwellings (O-ESD) - Data supporting the publication: Towards environmentally enriched floor layout datasets: a workflow for transitioning the existing data in the built environment"}],"publisher":"4TU.ResearchData","container":{},"publicationYear":2026,"subjects":[{"subject":"Building","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"1202"},{"subject":"FOS: Civil engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Architecture","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"1201"},{"subject":"Built Environment and Design","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"12"},{"subject":"Floor layout datasets"},{"subject":"Machine learning"},{"subject":"Generative AI"},{"subject":"Data refinement"},{"subject":"Building performance guidelines"},{"subject":"Environmental building design"},{"subject":"BREEAM"}],"contributors":[{"name":"TU Delft, Faculty of Architecture and the Built Environment, Department of Architecture, Building Knowledge","nameType":"Organizational","affiliation":[],"contributorType":"Other","nameIdentifiers":[]},{"name":"Archylise A.G","nameType":"Organizational","affiliation":[],"contributorType":"Other","nameIdentifiers":[]}],"dates":[{"date":"2026-04-20","dateType":"Issued"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1108/sasbe-10-2025-0684","relatedIdentifierType":"DOI"},{"relationType":"IsVersionOf","relatedIdentifier":"10.4121/d8a5eb90-0269-4a4b-b672-f1dd9b351836.v1","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["tabular (.csv)"],"version":"1","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The Oriented Environmental Swiss Dwellings (O-ESD) dataset is an enriched architectural dataset designed to support data-driven research in the built environment. It extends the Swiss Dwellings dataset by integrating building performance guidelines into a structured, machine-readable format through a reproducible data refinement and feature engineering workflow implemented in Python.The dataset contains floor layout data augmented with environmental and spatial attributes. These include:Spatial zoning classifications (categorical)Proxy indicators for daylight availability and view quality (numerical)Noise level indicators (numerical)Acoustic comfort categories (categorical)Window orientation attributes (categorical)These additions enable analysis of indoor environmental quality at the layout level and support applications in machine learning, architectural design automation, and large-scale spatial analysis.A central contribution of this dataset is the transformation of semi-structured and textual building performance guidelines into structured tabular data. This allows the dataset to be readily used in computational workflows while maintaining interpretability through derived environmental indicators and visualization-ready features. O-ESD can be reused in research on building performance, environmental design, machine learning in architecture, and urban analytics. It is particularly suitable for studies requiring structured representations of indoor environmental conditions or for developing predictive and generative design models.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[],"xml":"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