Medium Article | Kaggle Kernel | Github Repo

Context

I was curious about the Finnish Architectural market as a whole and its most efficient actors.

Content

The Dataset represents the financial and geospatial information of architectural offices registered in Finland.

Acknowledgements

The Data was provided by Fonecta and Statistics Finland.

An Open Context "subjects" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Structure" record is part of the "Architecture and Urbanism at Seyitömer Höyük, Turkey" data publication.

The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, access rules will allow the authorized user to edit the dataset over the network. Established rules will ensure that the attribute and topological integrity is maintained, so that key fields are not left blank and that the block group boundaries stay within tract boundaries. Metadata will automatically be updated showing who edited the dataset and when they did in the event any questions arise. Currently, a functioning prototype Multi-User Database has been developed for BES at the University of Vermont Spatial Analysis Lab, using Arc SDE and IBM's DB2 Enterprise Database as a back end architecture. This database, which is currently only accessible to those on the UVM campus network, will shortly be migrated to a Linux server where it will be accessible for database connections over the Internet. Passwords can then be handed out to all interested researchers on the project, who will be able to make a database connection through the Geographic Information Systems software interface on their desktop computer. This database will include a very large number of thematic layers. Those layers are currently divided into biophysical, socio-economic and imagery categories. Biophysical includes data on topography, soils, forest cover, habitat areas, hydrology and toxics. Socio-economics includes political and administrative boundaries, transportation and infrastructure networks, property data, census data, household survey data, parks, protected areas, land use/land cover, zoning, public health and historic land use change. Imagery includes a variety of aerial and satellite imagery. See the readme: http://96.56.36.108/geodatabase_SAL/readme.txt See the file listing: http://96.56.36.108/geodatabase_SAL/diroutput.txt

An Open Context "media" dataset item. Open Context publishes structured data as granular, URL identified Web resources. This "Document media" record is part of the "Architecture and Urbanism at Seyitömer Höyük, Turkey" data publication.

🏗️ FloorPlanCAD Dataset FloorPlanCAD is a large-scale dataset of rasterized and annotated 2D floorplan CAD drawings curated for architectural object detection, layout analysis, and spatial understanding tasks. It supports the development of multimodal and computer vision systems in the architecture and construction domains.

📦 Dataset Overview Total Drawings: 15,285

Image Format: Rasterized PNG (640×640) from vector-based CAD (.svg)

Annotations: Approximately 11,352 images include bounding box annotations spanning 28 architectural object categories (with more annotation coming - work in progress). License: CC BY-NC 4.0

Primary Use Cases:

Architectural symbol detection

Layout understanding

Training AI/ML models for design automation

🔍 Object Categories (28) Includes:

Doors (single, double, sliding)

Windows (regular, bay, blind)

Furniture (sofa, bed, table, chair, etc.)

Fixtures (sink, toilet, bath)

Utilities (gas stove, fridge, washer)

Circulation elements (stairs, elevator, escalator)

Others (wardrobe, TV cabinet, cabinets, etc.)

📊 Format Images: .png format at 640x640 resolution

Annotations: YOLOv8 format or JSON/CSV (bounding boxes + class labels)

Metadata (if applicable): Image ID, room types, file origin

💡 Applications Object detection and segmentation in floorplans

Room layout reconstruction

Multimodal RAG systems for architecture

Training models for design assistance and document understanding

🔗 Citation

@InProceedings{Fan_2021_ICCV, author = {Fan, Zhiwen and Zhu, Lingjie and Li, Honghua and Zhu, Siyu and Tan, Ping}, title = {FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, year = {2021}

Archaeology, as the discipline that searches to explain the development of society by means of material remains, has been avoiding the big issues involved with its research agenda. The topic of social evolution is concealed by anxiety about previous paradigmatic malpractice and the primary archaeological division of the world in culture areas still suffers from the archaic methods by which it was established. Archaeological inference of developing societies is weighed down by its choice of particularism within agency approaches and overtly reductionist due to the prevalence of statistical, classificatory and biological approaches.This book addresses these issues through a perspective on the spatial analysis of the built environment. As one of the principal properties of our dataset, as well as being the first materialisation of sociality, such spatialities are suggested to be a fundamental key for enabling an understanding of the developing social identity of places, regions and areas. In order to arrive at a truly social inference of spatial datasets, archaeology’s usual analysis working from material remains towards socio-cultural interpretations needs to be inverted. The vantage point of this study consists of aprioristic social theory. It constructs its arguments through an epistemological foundation comprising a selection of essential ideas regarding the three constitutive axes of developing societies: time, human action and human space. As it recognises the inherent position of these axes combined in the discipline of human geography, a historical comparison of these two disciplines presents the angle from which plausible theoretical advancements can be made. The core of the book explores selected works of human geographers Allan Pred, Benno Werlen and Andreas Koch against the backdrop of theories like structuration or systems theory, phenomenology, action theory, and to a lesser extent Actor Network Theory and autopoiesis. From this follows its own theoretical proposal called the social positioning of spatialities. On this basis hypotheses for methodological opportunities are discussed, establishing a research agenda.Firmly placing its efforts in current paradigmatic debates in the discipline, this study offers archaeological theorists an incentive to leave the safety of materially bound science and adapt an alternative perspective. It is an attempt to put archaeology back in the forefront of the social theoretical debates it should contribute to. Date Submitted: 2010-01-18 Copyrights apply. The printed version of this book is available directly from Sidestone Press' online book store: http://www.sidestone.nl/ . Also available from Oxbow books: http://www.oxbowbooks.com/ and Amazon: http://www.amazon.co.uk/ .

The Reality and Spatial Modeling Software market is poised for significant expansion, projected to reach a market size of approximately $5,500 million by 2025, with a robust Compound Annual Growth Rate (CAGR) of 21.5% anticipated throughout the forecast period of 2025-2033. This substantial growth is primarily fueled by the increasing adoption of reality modeling and 3D scanning technologies across diverse industries. Key drivers include the escalating demand for digital twins, enhanced visualization capabilities in architecture and engineering, and the need for more accurate spatial data for planning and infrastructure development. The Architecture and Engineering segments are expected to lead the market, driven by professionals leveraging these tools for design, simulation, and construction management. The growing prevalence of cloud-based solutions, offering enhanced accessibility, scalability, and collaboration, is a significant trend reshaping the market landscape, with local deployment options continuing to cater to specific security and operational needs. The market's momentum is further bolstered by advancements in AI and machine learning, enabling more sophisticated data processing and automated modeling. As industries increasingly embrace digital transformation, the need for precise digital representations of the physical world becomes paramount. This trend is particularly evident in sectors like construction, urban planning, and asset management. Despite the positive outlook, potential restraints include the high initial investment costs for sophisticated hardware and software, as well as the need for specialized skill sets to effectively operate these complex platforms. However, the clear benefits in terms of reduced project risks, improved efficiency, and enhanced decision-making are steadily outweighing these challenges. Leading players like Bentley Systems, Virtuosity, Orion Spatial Solutions, and CTTEC are actively innovating and expanding their offerings to capture a larger share of this dynamic and evolving market, particularly within key regions like North America and Europe. This report delves into the dynamic Reality and Spatial Modeling Software market, providing an in-depth analysis of its current state and future trajectory. Leveraging extensive research across the Historical Period (2019-2024), the Base Year (2025), and projecting through the Forecast Period (2025-2033), this study offers crucial insights for stakeholders. The Study Period spans from 2019 to 2033, ensuring a holistic view of market evolution.

These files comprise Appendix C of the thesis "The Intelligent Machine in Urban Open Space, Sensing Urban Data and Performing Architectural Behaviour" and include the algorithms (established for Design Experiment 2 and Design Development). The files can be opened using Rhino 6 and Grasshopper. In the algorithms, weather API ID needs to be updated (obtained from the following website: https://www.worldweatheronline.com/developer). In the Grasshopper files, the texts and numbers in the CSV files, established for the categorisation, are saved in the panels and connected to the architectural model’s data processing. The Grasshopper files can be opened and run independently without requesting any file paths associated with a laptop. The non-book component of the algorithms presents the actual systems (that can be run by the software) established for the real-time simulations described in sections 4.4. Design Experiment 2 and 5.7. Real-Time Simulation

In order to improve the capacity of storage, exploration and processing of sensor data, a spatial DBMS was used and the Aquopts system was implemented.

In field surveys using different sensors on the aquatic environment, the existence of spatial attributes in the dataset is common, motivating the adoption of PostgreSQL and its spatial extension PostGIS. To enable the insertion of new data sets as well as new devices and sensing equipment, the database was modeled to support updates and provide structures for storing all the data collected in the field campaigns in conjunction with other possible future data sources. The database model provides resources to manage spatial and temporal data and allows flexibility to select and filter the dataset.

The data model ensures the storage integrity of the information related to the samplings performed during the field survey in an architecture that benefits the organization and management of the data. However, in addition to the storage specified on the data model, there are several procedures that need to be applied to the data to prepare it for analysis. Some validations are important to identify spurious data that may represent important sources of information about data quality. Other corrections are essential to tweak the data and eliminate undesirable effects. Some equations can be used to produce other factors that can be obtained from the combination of attributes. In general, the processing steps comprise a cycle of important operations that are directly related to the characteristics of the data set. Considering the data of the sensors stored in the database, an interactive prototype system, named Aquopts, was developed to perform the necessary standardization and basic corrections and produce useful data for analysis, according to the correction methods known in the literature.

The system provides resources for the analyst to automate the process of reading, inserting, integrating, interpolating, correcting, and other calculations that are always repeated after exporting field campaign data and producing new data sets. All operations and processing required for data integration and correction have been implemented from the PHP and Python language and are available from a Web interface, which can be accessed from any computer connected to the internet. The data access cab be access online (http://sertie.fct.unesp.br/aquopts), but the resources are restricted by registration and permissions for each user. After their identification, the system evaluates the access permissions and makes available the options of insertion of new datasets.

The source-code of the entire Aquopts system are available at: https://github.com/carmoafc/aquopts

The system and additional results were described on the official paper (under review)

These files comprise Appendix D of the thesis "The Intelligent Machine in Urban Open Space, Sensing Urban Data and Performing Architectural Behaviour" and include the animations of data visualisation, architectural models’ behaviours, and real-time simulations. The animations can be seen in a PDF file or via MP4 files. Via the animations of D.1.1. and D.1.2., the data of NYC Permitted Event Information depicted on the map of Manhattan and Bryant Park can be seen through timeframes. Those two animations were conducted to confirm whether the sensing algorithms could read the data within territorial conditions through the use of timeframes.The animations of D.2.1., D.2.2. and D.2.3. show the early model of kinetic structures and skins, as described in section 4.3. Design Experiment 1. The tests (shown in those three animations) focused on enabling folding structures that could enclose an area within the park, connecting with the data (tested using the past data) and simulating in real time. The animations of D.3.1., D.3.2., D.3.3. and D.3.4. show the second model of kinetic structures and skins that was tested using categorised data, as described in section 4.4. Design Experiment 2. The tests (shown in those four animations) verified that the algorithm could regulate both digital and physical models’ behaviours in real time. The following animations (i.e. D.4.1., D.4.2., D.4.3., D.4.4., D.4.5. and D.4.6.) show the recorded real-time simulation activated by the algorithm established for Design Development. Selected moments from the animations are described in section 5.7. Real-Time Simulation.

Abstract Geography and architecture are two areas of knowledge whose respective subject corpora apparently focus on the same object – space. This is the starting point of these theoretical notes, the objective of which is to draw attention to certain epistemological distinctions between the above-mentioned areas. Therefore, in the first part, it is noted that it was only in the 1970s that the concept of space became a key concept of geography. Moreover, possible differentiations of this concept are announced in comparison with the theoretical formulation of architectonic space. In the second part, the theoretical and methodological specificities that define architectural space are indicated. It is hoped that the reflections presented in this article will contribute to minimize possible instances of epistemological confusion.

The level of constructedness of archaeological sites can provide insight into the amount of planning, labor and time invested into building structures. Further understanding into the time, labor and planning invested into architecture can allow for inferences to made on the residential mobility of the population, intensity of surrounding land use and social importance assigned to each pueblo (Cameron 1999). This paper will explore and compare the architectural constructedness of small sites located around the larger pueblos of Pueblo la Plata and Pueblo Pato. Pueblo la Plata and Pueblo Pato are both located within the boundaries of Agua Fria National Monument on Perry Mesa in central Arizona. Agua Fria National Monument covers over 71,000 acres and is located approximately 40 miles north of Phoenix. According to previously performed archaeological research, there exists approximately 450 prehistoric sites within the boundaries, including Pueblo la Plata and Pueblo Pato (BLM 2006). The purpose of this paper is to explore the level of constructedness of the small sites around these two large pueblos and attempt to draw some conclusions about the social organization of these sites during their occupation.

In order to carry out a comprehensive design description of the specific architectural model of AI, the auxiliary model of AI and architectural spatial intelligence is deeply integrated, and flexible design is carried out according to the actual situation. AI assists in the generation of architectural intention and architectural form, mainly supporting academic and working theoretical models, promoting technological innovation, and thus improving the design efficiency of the architectural design industry. AI-aided architectural design enables every designer to achieve design freedom. At the same time, with the help of AI, architectural design can complete the corresponding work faster and more efficiently. With the help of AI technology, through the adjustment and optimization of keywords, AI automatically generates a batch of architectural space design schemes. Against this background, the auxiliary model of architectural space design is established through the literature research of the AI model, the architectural space intelligent auxiliary model, and the semantic network and the internal structure analysis of architectural space. Secondly, to ensure compliance with the three-dimensional characteristics of the architectural space from the data source, based on the analysis of the overall function and structure of space design, the intelligent design of the architectural space auxiliary by Deep Learning is carried out. Finally, it takes the 3D model selected in the UrbanScene3D data set as the research object, and the auxiliary performance of AI’s architectural space intelligent model is tested. The research results show that with the increasing number of network nodes, the model fitting degree on the test data set and training data set is decreasing. The fitting curve of the comprehensive model shows that the intelligent design scheme of architectural space based on AI is superior to the traditional architectural design scheme. As the number of nodes in the network connection layer increases, the intelligent score of space temperature and humidity will continue to rise. The model can achieve the optimal intelligent auxiliary effect of architectural space. The research has practical application value for promoting the intelligent and digital transformation of architectural space design.

TerraMetrics, Inc., proposes a Phase II R/R&D program to implement the TerraBlocks^TM Server architecture that provides geospatial data authoring, storage and delivery capabilities. TerraBlocks enables successful deployment, display and visual interaction of diverse, massive, multi-dimensional science datasets within popular web-based geospatial platforms like Google Earth and NASA World Wind.

TerraBlocks is a wavelet-encoded data storage technology and server architecture for NASA science data deployment into widely available web-based geospatial applications. The TerraBlocks approach provides dynamic geospatial data services with an emphasis on 1) server and data storage efficiency, 2) maintaining server-to-client science data integrity and 3) offering client-specific delivery of large Earth science geospatial datasets. The TerraBlocks approach bridges the gap between inflexible, but fast, pre-computed tile delivery approaches and highly flexible, but slower, map services approaches.

The pursued technology exploits the use of a network-friendly, wavelet-compressed data format and server architecture that extracts and delivers appropriately-sized blocks of multi-resolution geospatial data to geospatial client applications on demand and in interactive real time.

The Phase II project objective is to provide a complete and fully-functional prototype TerraBlocks data authoring and server software package delivery to NASA and simultaneously set the stage for commercial availability. The Phase III objective is to commercially deploy the TerraBlocks technology, with the collaboration of our commercial and government partners, to provide the enabling basis for widely available third-party data authoring and web-based geospatial application data services.

The data presents results of work within the studies of the conditions of the district in the context of the city, Lower Sopot (Dolny Sopot) district, study proposal no 3, from February 2021. The goal of the research process was to present the functional and spatial structure analysis of the area located in Lower Sopot (Dolny Sopot) district in the context of the city of Sopot. The aim of the study was to understand the current condition and the potential for redevelopment of the chosen area taking in consideration development of the entire city. The dataset presents functional and spatial structure analysis in the form of sensation path, survey among residents, mental maps, land use analysis, series of diagrams and schemes. The dataset presents the study work of students of the Faculty of Architecture, Gdańsk University of Technology (FA Gdańsk Tech) - 6th semester of the Bachelor Studies (undergraduate studies) at the FA Gdańsk Tech coordinated by Weronika Mazurkiewicz PhD. The preparatory process and studies were conducted during February 2021. The study results in the dataset are the effect of the course of urban planning IV at the Faculty of Architecture, Gdańsk University of Technology 2020/2021 academic year. The study results in dataset form the basis for the design proposal developed during the course as well as further research and development studies of the district.

Lengthy waiting times for ophthalmology appointments in the UK National Health Service (NHS) increased further in the immediate aftermath of the Covid-19 pandemic, necessitating a different approach to triaging patients safely and at speed. Moorfields Eye Hospital NHS Trust therefore opened an additional diagnostic hub designed with a linear spatial layout and patient flow system, which is analyzed in this paper in comparison to an existing clinic. We integrate direct observations of patient flows, and an architectural layout analysis based on space syntax methods with queuing simulations from operations research and show that the two clinics operate differently and that both clinics have their advantages and disadvantages. The newly opened clinic with a lane system supports flows and coordination by line of sight between stations, which contrasts with a lack of sightlines in the existing clinic. The latter layout with clusters of stations compensates by enabling a more organic flow, es..., Fieldwork was undertaken in June and July 2021 in two outpatient clinics of Moorfield Eye Hospital NHS Trust, the Cayton Street clinic and the Hoxton Hub. Two main data sets were collected for each clinic: 1) an up-to-date floor plan of each clinic including the locations and types of all diagnostic equipment marked up, and 2) direct observations of glaucoma patient flows, recorded on tablets, including exact time stamps of entry and exit of the clinic as well as start and end times for all diagnostic tests. For the observations, patients received a sticker with a study ID number at the reception desk, which was recorded by observers as an identifier. Over the course of ten days of observations, participant observers captured nine 4-hour shifts in the period from 8:30 to 17:00 in Hoxton, and six 4-hour day shifts and seven 3-hour evening shifts between 8:30 and 20:00 in Cayton Street. 14 patients at Cayton Street and 11 patients at Hoxton were shadowed for the entirety of their journey ..., , # Lanes, Clusters, Lines of Sight: Modelling diagnostic eyecare clinics to improve patient flow

https://doi.org/10.5061/dryad.m0cfxppdj

Description of the data and file structure

Data and analysis description

To replicate our analysis, the following three pieces of work need to be completed: first, the spatial analysis of the layout; second, the analysis of the observational data on patient flows and timings; and third, the simulation of patient flow, which provides an indication of the ideal type and number of required machines. The following steps in each piece of work need to be completed.

Spatial analysis

1) Perform VGA and Step Depth Analysis

Prepare a dxf file of a floor plan following the instructions in the Depthmap_VGA_HowToGuide.pdf, using the floor plan we have provided in the VGA model folder as an example.

Download DepthmapX to run Visibility Graph Analysis (VGA) and visual Step Depth (SD) from the same...

Historic components on St Helena Island, Moreton Bay, Queensland, have been represented by vector features in Arc Map. The database uses a GCS_WGS_1984 coordinate reference system. The database consists of ESRI ArcGIS database and digital versions of historic maps and was created using AutoCad and ESRI ArcGIS software in file formats gdb, mxd, dwg, lyr. The data base was created as part of the Representation and Authenticity of Historic Landscapes in Australia and China project.

The data found in this repository contain the basis for the historical, architectural, and geo-spatial analyses discussed in the dissertation entitled: CITADEL – Computation Investigation of the Topographical and Architectural Designs in an Evolving Landscape. These data include the following categories. 1. Photogrammetric Data: all photos, calibration information, and Agisoft Metashape projects for the four sites. All post-processed 3D models of the photogrammetric process and their associated perspectives from which orthophotos were generated for the construction research. 2. Laserscan Data: all raw data and calibration information pertaining the four sites as recorded by the Riegl VZ-400 laser scanner, and all post-processed 3D models of the sites. 3. GIS Data: all historical maps that were geo-referenced in the project, the entire QGIS project file with all associated layers, all raster and vector data saved as individual files, and all shapefiles saved as individual files. 4. Graph Database: all spreadsheets containing the base information drawn from the charters provided by online and analog sources. The entire Cypher Script as well as instruction for importing the data into Neo4j. The rubric outlining how the status and administration positions of the individuals in the charters were ranked relative to one another. The cognitive development of the database’s structure represented by graph schemas over time. 5. Architectural Plans: the roombook outlining every wall, architectural element, and building phase of the four sites. All 76 architectural plans of the construction research using orthophotos of the photogrammetric models.

The market for Reality and Spatial Modeling Software is projected to reach $XXX million by 2033, expanding at a CAGR of XX% from 2025 to 2033. The growth of this market is primarily driven by the increasing adoption of virtual reality (VR) and augmented reality (AR) technologies in various industries, including architecture, engineering, and construction (AEC). Additionally, the growing demand for immersive experiences in entertainment and gaming is contributing to the market's growth. The market is segmented by type (cloud-based and local deployment), application (architecture, engineering, and others), and region (North America, Europe, Asia Pacific, and Rest of the World). Cloud-based solutions are gaining popularity due to their scalability, cost-effectiveness, and accessibility. The AEC sector is the largest application segment, followed by the manufacturing and healthcare industries. North America holds the largest market share, followed by Europe and Asia Pacific. The market is dominated by a few key players, including Bentley Systems, Virtuosity, Orion Spatial Solutions, and CCTTEC. Intense competition and technological advancements are expected to shape the market's growth over the forecast period.