42 datasets found
  1. F

    New Privately-Owned Housing Units Under Construction: Units in Buildings...

    • fred.stlouisfed.org
    json
    Updated Jun 18, 2025
    + more versions
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    (2025). New Privately-Owned Housing Units Under Construction: Units in Buildings with 5 Units or More [Dataset]. https://fred.stlouisfed.org/series/UNDCON5MUSA
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    jsonAvailable download formats
    Dataset updated
    Jun 18, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for New Privately-Owned Housing Units Under Construction: Units in Buildings with 5 Units or More (UNDCON5MUSA) from Jan 1970 to May 2025 about 5-unit structures +, construction, new, private, housing, and USA.

  2. p

    Apartment Complexes in United States - 94,269 Verified Listings Database

    • poidata.io
    csv, excel, json
    Updated Jul 24, 2025
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    Poidata.io (2025). Apartment Complexes in United States - 94,269 Verified Listings Database [Dataset]. https://www.poidata.io/report/apartment-complex/united-states
    Explore at:
    csv, excel, jsonAvailable download formats
    Dataset updated
    Jul 24, 2025
    Dataset provided by
    Poidata.io
    Area covered
    United States
    Description

    Comprehensive dataset of 94,269 Apartment complexes in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

  3. d

    Housing Database

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Jan 10, 2025
    + more versions
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    data.cityofnewyork.us (2025). Housing Database [Dataset]. https://catalog.data.gov/dataset/housing-database
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    Dataset updated
    Jan 10, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    The NYC Department of City Planning’s (DCP) Housing Database contains all NYC Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. It includes the three primary construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. Records in the Housing Database Project-Level Files are geocoded to the greatest level of precision possible, subject to numerous quality assurance and control checks, recoded for usability, and joined to other housing data sources relevant to city planners and analysts. Data are updated semiannually, at the end of the second and fourth quarters of each year. Please see DCP’s annual Housing Production Snapshot summarizing findings from the 21Q4 data release here. Additional Housing and Economic analyses are also available. The NYC Department of City Planning’s (DCP) Housing Database Unit Change Summary Files provide the net change in Class A housing units since 2010, and the count of units pending completion for commonly used political and statistical boundaries (Census Block, Census Tract, City Council district, Community District, Community District Tabulation Area (CDTA), Neighborhood Tabulation Area (NTA). These tables are aggregated from the DCP Housing Database Project-Level Files, which is derived from Department of Buildings (DOB) approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions. These files can be used to determine the change in legal housing units across time and space.

  4. Multifamily Properties

    • catalog.data.gov
    • datasets.ai
    Updated Mar 1, 2024
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    U.S. Department of Housing and Urban Development (2024). Multifamily Properties [Dataset]. https://catalog.data.gov/dataset/multifamily-properties
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    Dataset updated
    Mar 1, 2024
    Dataset provided by
    United States Department of Housing and Urban Developmenthttp://www.hud.gov/
    Description

    This dataset denotes HUD subsidized Multifamily Housing properties excluding insured hospitals with active loans. HUD’s Multifamily Housing property portfolio consist primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also include nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. HUD provides subsidies and grants to property owners and developers in an effort to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled. The portfolio can be broken down into two basic categories: insured, and assisted. The three largest assistance programs for Multifamily Housing are Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly, and Section 811 Supportive Housing for Persons with Disabilities. The Multifamily property locations represent the approximate location of the property. The locations of individual buildings associated with each property are not depicted here.

  5. d

    Real Estate Data | Property Listing, Sold Properties, Rankings, Agent...

    • datarade.ai
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    Grepsr, Real Estate Data | Property Listing, Sold Properties, Rankings, Agent Datasets | Global Coverage | For Competitive Property Pricing and Investment [Dataset]. https://datarade.ai/data-products/real-estate-property-data-grepsr-grepsr
    Explore at:
    .bin, .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    Grepsr
    Area covered
    Australia, Spain, Holy See, Malaysia, Congo (Democratic Republic of the), Iraq, South Sudan, Tonga, Kuwait, Kazakhstan
    Description

    Extract detailed property data points — address, URL, prices, floor space, overview, parking, agents, and more — from any real estate listings. The Rankings data contains the ranking of properties as they come in the SERPs of different property listing sites. Furthermore, with our real estate agents' data, you can directly get in touch with the real estate agents/brokers via email or phone numbers.

    A. Usecase/Applications possible with the data:

    1. Property pricing - accurate property data for real estate valuation. Gather information about properties and their valuations from Federal, State, or County level websites. Monitor the real estate market across the country and decide the best time to buy or sell based on data

    2. Secure your real estate investment - Monitor foreclosures and auctions to identify investment opportunities. Identify areas within special economic and opportunity zones such as QOZs - cross-map that with commercial or residential listings to identify leads. Ensure the safety of your investments, property, and personnel by analyzing crime data prior to investing.

    3. Identify hot, emerging markets - Gather data about rent, demographic, and population data to expand retail and e-commerce businesses. Helps you drive better investment decisions.

    4. Profile a building’s retrofit history - a building permit is required before the start of any construction activity of a building, such as changing the building structure, remodeling, or installing new equipment. Moreover, many large cities provide public datasets of building permits in history. Use building permits to profile a city’s building retrofit history.

    5. Study market changes - New construction data helps measure and evaluate the size, composition, and changes occurring within the housing and construction sectors.

    6. Finding leads - Property records can reveal a wealth of information, such as how long an owner has currently lived in a home. US Census Bureau data and City-Data.com provide profiles of towns and city neighborhoods as well as demographic statistics. This data is available for free and can help agents increase their expertise in their communities and get a feel for the local market.

    7. Searching for Targeted Leads - Focusing on small, niche areas of the real estate market can sometimes be the most efficient method of finding leads. For example, targeting high-end home sellers may take longer to develop a lead, but the payoff could be greater. Or, you may have a special interest or background in a certain type of home that would improve your chances of connecting with potential sellers. In these cases, focused data searches may help you find the best leads and develop relationships with future sellers.

    How does it work?

    • Analyze sample data
    • Customize parameters to suit your needs
    • Add to your projects
    • Contact support for further customization
  6. F

    New Privately-Owned Housing Units Started: Units in Buildings with 5 Units...

    • fred.stlouisfed.org
    json
    Updated Jul 18, 2025
    + more versions
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    (2025). New Privately-Owned Housing Units Started: Units in Buildings with 5 Units or More [Dataset]. https://fred.stlouisfed.org/series/HOUST5FNSA
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 18, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for New Privately-Owned Housing Units Started: Units in Buildings with 5 Units or More (HOUST5FNSA) from Aug 1963 to Jun 2025 about 5-unit structures +, housing starts, privately owned, housing, and USA.

  7. F

    Housing Inventory Estimate: Total Housing Units in the United States

    • fred.stlouisfed.org
    json
    Updated Apr 28, 2025
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    (2025). Housing Inventory Estimate: Total Housing Units in the United States [Dataset]. https://fred.stlouisfed.org/series/ETOTALUSQ176N
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Apr 28, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Housing Inventory Estimate: Total Housing Units in the United States (ETOTALUSQ176N) from Q2 2000 to Q1 2025 about inventories, housing, and USA.

  8. T

    United States Housing Starts

    • tradingeconomics.com
    • zh.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 18, 2025
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    TRADING ECONOMICS (2025). United States Housing Starts [Dataset]. https://tradingeconomics.com/united-states/housing-starts
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jul 18, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1959 - Jun 30, 2025
    Area covered
    United States
    Description

    Housing Starts in the United States increased to 1321 Thousand units in June from 1263 Thousand units in May of 2025. This dataset provides the latest reported value for - United States Housing Starts - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  9. d

    Home Ownership Data | USA Coverage | 74% Right Party Contact Rate |...

    • datarade.ai
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    BatchData, Home Ownership Data | USA Coverage | 74% Right Party Contact Rate | BatchData [Dataset]. https://datarade.ai/data-products/batchservice-home-ownership-data-us-87-million-property-o-batchservice
    Explore at:
    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    BatchData
    Area covered
    United States
    Description

    BatchData provides comprehensive home ownership data for 87 million owners of residential homes in the US. We specialize in providing accurate contact information for owners of specific properties, trusted by some of the largest real estate companies for our superior capabilities in accurately unmasking owners of properties that may be hidden behind LLCs and corporate veils.

    Our home ownership data is commonly used to fuel targeted marketing campaigns, generating real estate insights, powering websites/applications with real estate intelligence, and enriching sales and marketing databases with accurate homeowner contact information and surrounding intelligence to improve segmentation and targeting.

    Home ownership data that is linked to a given property includes: - Homeowner Name(s) - Homeowner Cell Phone Number - Homeowner Email Address - Homeowner Mailing Address - Addresses of Properties Owned - Homeowner Portfolio Equity - Total Number of Properties Owned - Property Characteristics of Properties Owned - Homeowner sales, loan, and mortgage information - Property Occupancy Status of Properties Owned - Property Valuation & ARV information of Properties Owned - Ownership Length - Ownership History - Homeowner Age - Homeowner Marital Status - Homeowner Income - and more!

    BatchService is both a data and technology company helping companies in and around the real estate ecosystem achieve faster growth. BatchService specializes in providing accurate B2B and B2C contact data for US property owners, including in-depth intelligence and actionable insights related to their property. Our portfolio of products, services, and go-to-market expertise help companies identify their target market, reach the right prospects, enrich their data, consolidate their data providers, and power their products and services.

  10. p

    Apartment Buildings in Minnesota, United States - 4,376 Available (Free...

    • poidata.io
    csv
    Updated Jun 19, 2025
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    Poidata.io (2025). Apartment Buildings in Minnesota, United States - 4,376 Available (Free Sample) [Dataset]. https://www.poidata.io/report/apartment-building/united-states/minnesota
    Explore at:
    csvAvailable download formats
    Dataset updated
    Jun 19, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Minnesota, United States
    Description

    This dataset provides information on 4,376 in Minnesota, United States as of June, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

  11. d

    DOF Condominium Comparable Rental Income in NYC

    • datasets.ai
    • data.cityofnewyork.us
    • +2more
    23, 40, 55, 8
    Updated Oct 8, 2024
    + more versions
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    City of New York (2024). DOF Condominium Comparable Rental Income in NYC [Dataset]. https://datasets.ai/datasets/dof-condominium-comparable-rental-income-in-nyc
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    55, 40, 8, 23Available download formats
    Dataset updated
    Oct 8, 2024
    Dataset authored and provided by
    City of New York
    Area covered
    New York
    Description

    The Department of Finance (DOF) is required by NY State law to value condominiums or cooperatives as if they were residential rental apartment buildings. DOF uses income information from rental properties similar in physical features and location to the condominiums or cooperatives. DOF applies this income data to the condominium or cooperative to determine its value in the same way DOF values rental apartment buildings. This report includes information at a condominium suffix level which represents a subdivision of the condominium since DOF values condominiums at a suffix level. A condominium may have more than one suffix.

    This data set contains the reports from 2012-2018.

  12. Model America - data for every U.S. building

    • zenodo.org
    • data.niaid.nih.gov
    Updated Mar 25, 2024
    + more versions
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    Brett Bass; Brett Bass; Joshua New; Joshua New; Andy Berres; Andy Berres; Nicholas Clinton; Mark Adams; Nicholas Clinton; Mark Adams (2024). Model America - data for every U.S. building [Dataset]. http://doi.org/10.5281/zenodo.6908189
    Explore at:
    Dataset updated
    Mar 25, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Brett Bass; Brett Bass; Joshua New; Joshua New; Andy Berres; Andy Berres; Nicholas Clinton; Mark Adams; Nicholas Clinton; Mark Adams
    Area covered
    United States
    Description

    DATA HAS BEEN MIGRATED TO https://data.ess-dive.lbl.gov/view/doi:10.15485/2283980

    The 5-year goal of the “Model America” concept was to generate a model of every building in the United States. This data repository delivers on that goal with "Model America v1".

    Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (bit.ly/AutoBEM).

    There were 125,715,609 buildings detected in the United States. Of this number, 122,146,671 (97.2%) buildings resulted in a successful generation and simulation of a building energy model. This dataset includes the full 125 million buildings. Future updates may include additional buildings, data improvements, or other algorithmic model enhancements in "Model America v2".

    1. Data, separated by state - minimalist list of each building (rows) for the following fields (columns)
      1. ID - unique building ID
      2. Footprint2D - lat/lon vertices of building footprint
      3. State_Abbrev - Abbreviation for the from which building is located
      4. Area - estimate of total conditioned floor area (ft2)
      5. Area2D - footprint area (ft2)
      6. CZ - ASHRAE Climate Zone designation
      7. Height - building height (ft)
      8. NumFloors - number of floors (above-grade)
      9. WWR_surfaces - percent of each facade (pair of points from Footprint2D) covered by fenestration/windows (average 14.5% for residential, 40% for commercial buildings)
      10. CZ - US climate zone designation
      11. BuildingType - DOE prototype building designation (IECC=residential) as implemented by OpenStudio-standards
      12. Standard - building vintage (determined by building age)

    This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), Biological and Environmental Research (BER), and National Nuclear Security Administration (NNSA).

  13. T

    United States Building Permits

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 25, 2025
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    TRADING ECONOMICS (2025). United States Building Permits [Dataset]. https://tradingeconomics.com/united-states/building-permits
    Explore at:
    csv, xml, json, excelAvailable download formats
    Dataset updated
    Jun 25, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1960 - Jun 30, 2025
    Area covered
    United States
    Description

    Building Permits in the United States increased to 1397 Thousand in June from 1394 Thousand in May of 2025. This dataset provides the latest reported value for - United States Building Permits - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  14. US National Property Listing Data | 50+ Property & Building Characteristics...

    • datarade.ai
    .csv, .xls, .txt
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    The Warren Group, US National Property Listing Data | 50+ Property & Building Characteristics | Pricing & Real Estate Agent Information [Dataset]. https://datarade.ai/data-products/us-national-property-listing-data-50-property-building-c-the-warren-group
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset authored and provided by
    The Warren Group
    Area covered
    United States of America
    Description

    Real estate is a dynamic and ever-evolving industry that relies heavily on data to make informed decisions. One of the fundamental aspects of this industry is real estate listing data. This data encompasses detailed information about properties that are available for sale or rent in a given market. It plays a pivotal role in assisting buyers, sellers, real estate professionals, and investors in making well-informed choices. In this data brief, we will provide an overview of what real estate listing data is and highlight five key industry use cases.

    Real Estate Listings Data Includes:

    • Property Location
    • 50+ Property and Building Characteristics
    • School District Information
    • List Date
    • Listing Price - Maximum, Minimum, Sold Price
    • Listing Status
    • Number of Days on Market
    • Listing Agent and Office
  15. End-Use Load Profiles for the U.S. Building Stock

    • data.openei.org
    • gimi9.com
    • +2more
    data, image_document +1
    Updated Oct 14, 2021
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    Eric Wilson; Andrew Parker; Anthony Fontanini; Elaina Present; Janet Reyna; Rajendra Adhikari; Carlo Bianchi; Christopher CaraDonna; Matthew Dahlhausen; Janghyun Kim; Amy LeBar; Lixi Liu; Marlena Praprost; Philip White; Liang Zhang; Peter DeWitt; Noel Merket; Andrew Speake; Tianzhen Hong; Han Li; Natalie Mims Frick; Zhe Wang; Aileen Blair; Henry Horsey; David Roberts; Kim Trenbath; Oluwatobi Adekanye; Eric Bonnema; Rawad El Kontar; Jonathan Gonzalez; Scott Horowitz; Dalton Jones; Ralph Muehleisen; Siby Platthotam; Matthew Reynolds; Joseph Robertson; Kevin Sayers; Qu Li; Eric Wilson; Andrew Parker; Anthony Fontanini; Elaina Present; Janet Reyna; Rajendra Adhikari; Carlo Bianchi; Christopher CaraDonna; Matthew Dahlhausen; Janghyun Kim; Amy LeBar; Lixi Liu; Marlena Praprost; Philip White; Liang Zhang; Peter DeWitt; Noel Merket; Andrew Speake; Tianzhen Hong; Han Li; Natalie Mims Frick; Zhe Wang; Aileen Blair; Henry Horsey; David Roberts; Kim Trenbath; Oluwatobi Adekanye; Eric Bonnema; Rawad El Kontar; Jonathan Gonzalez; Scott Horowitz; Dalton Jones; Ralph Muehleisen; Siby Platthotam; Matthew Reynolds; Joseph Robertson; Kevin Sayers; Qu Li (2021). End-Use Load Profiles for the U.S. Building Stock [Dataset]. http://doi.org/10.25984/1876417
    Explore at:
    data, website, image_documentAvailable download formats
    Dataset updated
    Oct 14, 2021
    Dataset provided by
    United States Department of Energyhttp://energy.gov/
    Open Energy Data Initiative (OEDI)
    National Renewable Energy Laboratory (NREL)
    Authors
    Eric Wilson; Andrew Parker; Anthony Fontanini; Elaina Present; Janet Reyna; Rajendra Adhikari; Carlo Bianchi; Christopher CaraDonna; Matthew Dahlhausen; Janghyun Kim; Amy LeBar; Lixi Liu; Marlena Praprost; Philip White; Liang Zhang; Peter DeWitt; Noel Merket; Andrew Speake; Tianzhen Hong; Han Li; Natalie Mims Frick; Zhe Wang; Aileen Blair; Henry Horsey; David Roberts; Kim Trenbath; Oluwatobi Adekanye; Eric Bonnema; Rawad El Kontar; Jonathan Gonzalez; Scott Horowitz; Dalton Jones; Ralph Muehleisen; Siby Platthotam; Matthew Reynolds; Joseph Robertson; Kevin Sayers; Qu Li; Eric Wilson; Andrew Parker; Anthony Fontanini; Elaina Present; Janet Reyna; Rajendra Adhikari; Carlo Bianchi; Christopher CaraDonna; Matthew Dahlhausen; Janghyun Kim; Amy LeBar; Lixi Liu; Marlena Praprost; Philip White; Liang Zhang; Peter DeWitt; Noel Merket; Andrew Speake; Tianzhen Hong; Han Li; Natalie Mims Frick; Zhe Wang; Aileen Blair; Henry Horsey; David Roberts; Kim Trenbath; Oluwatobi Adekanye; Eric Bonnema; Rawad El Kontar; Jonathan Gonzalez; Scott Horowitz; Dalton Jones; Ralph Muehleisen; Siby Platthotam; Matthew Reynolds; Joseph Robertson; Kevin Sayers; Qu Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    The United States is embarking on an ambitious transition to a 100% clean energy economy by 2050, which will require improving the flexibility of electric grids. One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High quality end-use load profiles (EULPs) provide this information, and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation. To help fill this gap, the U.S. Department of Energy (DOE) funded a three-year project, End-Use Load Profiles for the U.S. Building Stock, that culminated in this publicly available dataset of calibrated and validated 15-minute resolution load profiles for all major residential and commercial building types and end uses, across all climate regions in the United States. These EULPs were created by calibrating the ResStock and ComStock physics-based building stock models using many different measured datasets, as described in the "Technical Report Documenting Methodology" linked in the submission.

  16. d

    Commercial Real Estate Data | 52M+ POI | SafeGraph Property Dataset

    • datarade.ai
    .csv
    Updated Aug 22, 2024
    + more versions
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    SafeGraph (2024). Commercial Real Estate Data | 52M+ POI | SafeGraph Property Dataset [Dataset]. https://datarade.ai/data-products/commercial-real-estate-data-52m-poi-safegraph-property-d-safegraph
    Explore at:
    .csvAvailable download formats
    Dataset updated
    Aug 22, 2024
    Dataset authored and provided by
    SafeGraph
    Area covered
    Curaçao, Saint Martin (French part), El Salvador, Finland, Latvia, Kyrgyzstan, Gibraltar, Holy See, Ukraine, Yemen
    Description

    SafeGraph Places provides baseline location information for every record in the SafeGraph product suite via the Places schema and polygon information when applicable via the Geometry schema. The current scope of a place is defined as any location humans can visit with the exception of single-family homes. This definition encompasses a diverse set of places ranging from restaurants, grocery stores, and malls; to parks, hospitals, museums, offices, and industrial parks. Premium sets of Places include apartment buildings, Parking Lots, and Point POIs (such as ATMs or transit stations).

    SafeGraph Places is a point of interest (POI) data offering with varying coverage and properties depending on the country. Note that address conventions and formatting vary across countries. SafeGraph has coalesced these fields into the Places schema.

    SafeGraph provides clean and accurate geospatial datasets on 51M+ physical places/points of interest (POI) globally. Hundreds of industry leaders like Mapbox, Verizon, Clear Channel, and Esri already rely on SafeGraph POI data to unlock business insights and drive innovation.

  17. US National Building Permit Data | 200M+ Records | Residential Construction...

    • datarade.ai
    .csv, .xls, .txt
    Updated Nov 28, 2022
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    The Warren Group (2022). US National Building Permit Data | 200M+ Records | Residential Construction Data [Dataset]. https://datarade.ai/data-products/us-national-building-permit-data-construction-data-the-warren-group
    Explore at:
    .csv, .xls, .txtAvailable download formats
    Dataset updated
    Nov 28, 2022
    Dataset authored and provided by
    The Warren Group
    Area covered
    United States of America
    Description

    What is Building Permit Data?

    Building Permit Data is a detailed repository of records related to the permits issued by local authorities for various construction-related projects. These permits are mandatory for any significant building activity, ensuring that all developments comply with local zoning laws, safety standards, and building codes.

    This data typically includes a wealth of information such as:

    • Permit Types: Whether it’s a new construction, renovation, or demolition, the type of permit issued is recorded.
    • Issuance Dates: The date when the permit was issued, providing a timeline of construction activities.
    • Project Descriptions: Detailed descriptions of the construction or renovation work being undertaken.
    • Contractor Information: Information about the contractors responsible for the work, offering insights into the key players in local development.
    • Valuation Estimates: Estimated costs associated with the projects, crucial for understanding the scale and economic impact of the developments.

    This granular level of detail makes building permit data an indispensable resource for various applications.

  18. d

    Commercial Reference Building: Midrise Apartment

    • catalog.data.gov
    • data.openei.org
    • +1more
    Updated Apr 11, 2025
    + more versions
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    National Renewable Energy Laboratory (2025). Commercial Reference Building: Midrise Apartment [Dataset]. https://catalog.data.gov/dataset/commercial-reference-building-midrise-apartment-ed5e3
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    Dataset updated
    Apr 11, 2025
    Dataset provided by
    National Renewable Energy Laboratory
    Description

    Commercial reference buildings provide complete descriptions for whole building energy analysis using EnergyPlus (see "About EnergyPlus" resource link) simulation software. Included here is data pertaining to the reference building type "Midrise Apartment" for each of the 16 climate zones described on the Wiki page (see "OpenEI Wiki Page for Commercial Reference Buildings" resource link), and each of three construction categories: new (2004) construction, post-1980 construction existing buildings, and pre-1980 construction existing buildings. The dataset includes four key components: building summary, zone summary, location summary and a picture. Building summary includes details about: form, fabric, and HVAC. Zone summary includes details such as: area, volume, lighting, and occupants for all types of zones in the building. Location summary includes key building information as it pertains to each climate zone, including: fabric and HVAC details, utility costs, energy end use, and peak energy demand. In total, DOE developed 16 reference building types that represent approximately 70% of commercial buildings in the U.S.; for each type, building models are available for each of the three construction categories. The commercial reference buildings (formerly known as commercial building benchmark models) were developed by the U.S. Department of Energy (DOE), in conjunction with three of its national laboratories. Additional data is available directly from DOE's Energy Efficiency & Renewable Energy (EERE) website (see "About Commercial Buildings" resource link), including EnergyPlus software input files (.idf) and results of the EnergyPlus simulations (.html). Note: There have been many changes and improvements since this dataset was released. Several revisions have been made to the models and moved to a different approach to representing typical building energy consumption. For current data on building energy consumption please see the ComStock resource below.

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    Residential Data via API | USA Coverage | 74% Right Party Contact Rate |...

    • datarade.ai
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    BatchService, Residential Data via API | USA Coverage | 74% Right Party Contact Rate | BatchData [Dataset]. https://datarade.ai/data-products/batchservice-residential-real-estate-data-155-million-us-batchservice
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    .json, .xml, .csv, .xls, .sql, .txtAvailable download formats
    Dataset authored and provided by
    BatchService
    Area covered
    United States
    Description

    BatchData is used by lead generation, product, operations, and acquisitions teams to power websites, fuel applications, build lists, enrich data, and improve data governance. A suite of APIs and self-service list building platforms provide access to 150M+ residential properties.

    Residential Real Estate Data includes: - Property Address Information - Assessment Details - Building Characteristics - Demographics - Foreclosure - Occupancy/Vacancy - Involuntary Liens - MLS & Agent Arrays - Owner Names & Mailing Address - Property Owner Profiles - Current & Prior Sales - Tax Information - Valuation & Equity

    Real Estate Data APIs include: - Residential Property Search - Residential Property Lookup - Residential Address Verification - Residential Property Skip Trace - Geocoding

    BatchData's robust data science team curates over a dozen primary and secondary tier 1 data sources to offer unparalleled database depth, accuracy, and completeness.

  20. d

    Building Footprints

    • catalog.data.gov
    • opendata.dc.gov
    • +1more
    Updated Feb 4, 2025
    + more versions
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    Office of the Chief Technology Officer (2025). Building Footprints [Dataset]. https://catalog.data.gov/dataset/building-footprints-d97ff
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    Dataset updated
    Feb 4, 2025
    Dataset provided by
    Office of the Chief Technology Officer
    Description

    Building structures include parking garages, ruins, monuments, and buildings under construction along with residential, commercial, industrial, apartment, townhouses, duplexes, etc. Buildings equal to or larger than 9.29 square meters (100 square feet) are captured. Buildings are delineated around the roof line showing the building "footprint." Roof breaks and rooflines, such as between individual residences in row houses or separate spaces in office structures, are captured to partition building footprints. This includes capturing all sheds, garages, or other non-addressable buildings over 100 square feet throughout the city. Atriums, courtyards, and other “holes” in buildings created as part of demarcating the building outline are not part of the building capture. This includes construction trailers greater than 100 square feet. Memorials are delineated around a roof line showing the building "footprint."Bleachers are delineated around the base of connected sets of bleachers. Parking Garages are delineated at the perimeter of the parking garage including ramps. Parking garages sharing a common boundary with linear features must have the common segment captured once. A parking garage is only attributed as such if there is rooftop parking. Not all rooftop parking is a parking garage, however. There are structures that only have rooftop parking but serve as a business. Those are captured as buildings. Fountains are delineated around the base of fountain structures.

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(2025). New Privately-Owned Housing Units Under Construction: Units in Buildings with 5 Units or More [Dataset]. https://fred.stlouisfed.org/series/UNDCON5MUSA

New Privately-Owned Housing Units Under Construction: Units in Buildings with 5 Units or More

UNDCON5MUSA

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jsonAvailable download formats
Dataset updated
Jun 18, 2025
License

https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

Description

Graph and download economic data for New Privately-Owned Housing Units Under Construction: Units in Buildings with 5 Units or More (UNDCON5MUSA) from Jan 1970 to May 2025 about 5-unit structures +, construction, new, private, housing, and USA.

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