The DC Office of the Chief Financial Officer (OCFO), Office of Tax and Revenue (OTR), Real Property Tax Administration (RPTA) values all real property in the District of Columbia. This public interactive Real Property Assessment map application accompanies the OCFO MyTax DC and OTR websites. Use this mapping application to search for and view all real property, assessment valuation data, assessment neighborhood areas and sub-areas, detailed assessment information, and many real property valuation reports by various political and administrative areas. View by other administrative areas such as DC Wards, ANCs, DC Squares, and by specific real property characteristics such as property type and/or sale date. If you have questions, comments, or suggestions regarding the Real Property Assessment Map, contact the Real Property Assessment Division GIS Program at (202) 442-6484 or maps.title@dc.gov.

Property and parcel data is a critical layer to any city or statewide data holdings. In our city's complex urban environment, this includes numerous geographies that identify federal government lands, reservations, District lands, personal property and so much more. Use this application to query and identify boundaries including,Property LotsLot DimensionsCondo DataTax AssessmentsZoningSquaresThe District's Vector Property Mapping (VPM) project works daily to capture property lot transactions so that city planners, business development leaders and residents stay current.

Abstract

Historical tax assessment data for all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C. Each table represents a previous edition of CoreLogic's tax assessment data.

The CoreLogic Smart Data Platform (SDP) Historical Property data was formerly known as the CoreLogic Tax History data. The CoreLogic SDP Historical Property data is an enhanced version of the CoreLogic Tax History data. The CoreLogic SDP Historical Property data contains almost all of the variables that were included in the CoreLogic Tax History data, as well as additional property-level characteristics.

Methodology

In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

To fill researchers’ needs for uniform parcel data, CoreLogic collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. CoreLogic augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from CoreLogic’s parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

Usage

Each table contains an archived snapshot of the property data, roughly corresponding to the following assessed years:

• Historical Property 1 = 2022-2023
• Historical Property 2 = 2021-2022
• Historical Property 3 = 2020-2021
• Historical Property 4 = 2019-2020
• Historical Property 5 = 2018-2019
• Historical Property 6 = 2017-2018
• Historical Property 7 = 2016-2017
• Historical Property 8 = 2015-2016
• Historical Property 9 = 2014-2015
• Historical Property 10 = 2013-2014
• Historical Property 11 = 2012-2013
• Historical Property 12 = 2011-2012
• Historical Property 13 = 2010-2011
• Historical Property 14 = 2009-2010
• Historical Property 15 = 2008-2009

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Users can check theASSESSED_YEAR variable to confirm the year of assessment.

Roughly speaking, the tables use the following census geographies:

• 2020 Census Tract: Historical Property 1-2
• 2010 Census Tract: Historical Property 3 – 12
• 2000 Census Tract: Historical Property 13 – 15

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The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

For more information about included variables, please see **core_logic_sdp_historical_property_data_dictionary_2024.txt **and Historical Property_v3.xlsx.

Under Supporting files, users can also find record counts per FIPS code for each edition of the Historical Property data.

For more information about how the CoreLogic Smart Data Platform: Historical Property data compares to legacy data, please see core_logic_legacy_content_mapping.pdf.

Bulk Data Access

Data access is required to view this section.

Air right lots reflect a party’s right to construct an improvement above an existing area of land that is not owned by the constructor. They are a type of development right in real estate referring to the empty space about a property. These tax lot numbers start at 7000. There are approximately 704 air rights lots. Non-contiguous Air Rights Lots numbered in 8000 series can either be District owned Multifamily rental units or Existing Development Mixed (residential and commercial).Multifamily 8000 series lots can be proposed development projects that are inclusive of the Mayor’s Office Affordable/Public Housing Initiatives. Additionally, they can either be development sites that are owned by the District and the site is leased to developer. Due to financing and legal requirements, each set of government funded units are required to have separate parcel ID’s (SSL’s). All the units are rentals, none of the units will be for sale.Existing Development Mixed Use 8000 series lots are residential owner(s) that own both residential and commercial portions. The Lot split is done to ensure each party pays the appropriate real estate taxes assessed to each specific use. There is a master covenant lease outlining property access-rights-use between residential and commercial owner and lease holders. There is also a master lease related to the commercial space where the residential owner is the lease holder.

Abstract

Tax assessment data for all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C., as of June 2024.

The CoreLogic Smart Data Platform (SDP) Property data was formerly known as the CoreLogic Tax data. The CoreLogic SDP Property data is an enhanced version of the CoreLogic Tax data. The CoreLogic SDP Property data contains almost all of the variables that were included in the CoreLogic Tax data, and its records are augmented with additional property-level characteristics.

Methodology

In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

To fill researchers’ needs for uniform parcel data, CoreLogic collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. CoreLogic augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from CoreLogic’s parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

Usage

The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

Census tracts are based on the 2020 census.

For more information about included variables, please see **core_logic_sdp_property_data_dictionary_2024.txt **and Property_v3.xlsx.

For a count of records per FIPS code, please see core_logic_sdp_property_counts_2024.txt.

For more information about how the CoreLogic Smart Data Platform: Property data compares to legacy data, please see core_logic_legacy_content_mapping.pdf.

Bulk Data Access

Data access is required to view this section.

The District of Columbia offers several interactive online visualizations highlighting data and information from various fields of interest such as crime statistics, public school profiles, detailed property information and more. The web visualizations in this group present data coming from agencies across the Government of the District of Columbia. Click each to read a brief introduction and to access the site. This app is embedded in https://opendata.dc.gov/pages/dashboards.

SurDocs, commonly known as Surveyor Document System, is the District of Columbia’s Department of Consumer & Regulatory Affairs (DCRA) land records management system. DCRA’s Office of the Surveyor maintains the legal records of all land plats and subdivisions of private and District government property within the District of Columbia. The existing records cover a period of more than two centuries. In the past, individuals were only able to access records by visiting DCRA’s Surveyors Office. Now people can skip the trip and find documents online without having to visit the agency. DCRA is one of very few municipalities that actually preserve field survey records. Having this service obliges the public’s desire to have easy access with a simple process. SurDocs has over 10,000 electronic copies of original district land records stored and accessible.

The Industrial Revenue Bond program (IRB) provides access to tax-exempt financing to help businesses and non-profit organizations renovate and build new construction, make tenant improvements, and purchase capital by securing interest rates up 4% lower than a traditional commercial loan. IRBs can be used to finance, refinance, and reimburse the costs of acquiring, constructing, restoring, rehabilitating, expanding, improving, equipping, or furnishing real property and related subordinate facilities. More than $9.5 billion has been issued through Washington, DC's IRB program since 1994.

Abstract

The Owner Transfer and Mortgage data covers over 450 million properties, and includes over 50 years of sales history. The tables were generated in June 2024, and cover all U.S. states, the U.S. Virgin Islands, Guam, and Washington, D.C.

The Owner Transfer data provides historical information about property sales and ownership-related transactions, including full, nominal, and quitclaim transactions (involving a change in title/ownership). It contains comprehensive property and transaction information, such as property characteristics, current ownership, transaction history, title company, cash purchase/foreclosure/resale/short sale indicators, and buyer information.

The Mortgage data provides historical information at the mortgage level, including purchase, refinance, equity, as well as details associated with each transaction, such as lender, loan amount, loan date, interest rate, etc. Mortgage details include mortgage amount, type of loan (conventional, FHA, VHA), mortgage rate type, mortgage purpose (cash out first, consolidation, standalone subordinate), mortgage ARM features, and mortgage indicators such as fixed-rate, conforming loan, construction loan, and private party. The Mortgage data also includes subordinate mortgage types, rate details, and lender details (NMLS ID, Loan Company, Loan Officers).

The CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data was formerly known as the CoreLogic Deed data. The CoreLogic Deed data contained both owner transfer and mortgage information. In the CoreLogic Smart Data Platform (SDP), this data was separated into two tables: Owner Transfer and Mortgage. Between the two tables, the CoreLogic Smart Data Platform (SDP) Owner Transfer and Mortgage data contains almost all of the variables that were included in the CoreLogic Deed data. Further, each CoreLogic Smart Data Platform (SDP) table is augmented with additional owner transfer and mortgage characteristics.

Methodology

In the United States, parcel data is public record information that describes a division of land (also referred to as "property" or "real estate"). Each parcel is given a unique identifier called an Assessor’s Parcel Number or APN. The two principal types of records maintained by county government agencies for each parcel of land are deed and property tax records. When a real estate transaction takes place (e.g. a change in ownership), a property deed must be signed by both the buyer and seller. The deed will then be filed with the County Recorder’s offices, sometimes called the County Clerk-Recorder or other similar title. Property tax records are maintained by County Tax Assessor’s offices; they show the amount of taxes assessed on a parcel and include a detailed description of any structures or buildings on the parcel, including year built, square footages, building type, amenities like a pool, etc. There is not a uniform format for storing parcel data across the thousands of counties and county equivalents in the U.S.; laws and regulations governing real estate/property sales vary by state. Counties and county equivalents also have inconsistent approaches to archiving historical parcel data.

To fill researchers’ needs for uniform parcel data, CoreLogic collects, cleans, and normalizes public records that they collect from U.S. County Assessor and Recorder offices. CoreLogic augments this data with information gathered from other public and non-public sources (e.g., loan issuers, real estate agents, landlords, etc.). The Stanford Libraries has purchased bulk extracts from CoreLogic’s parcel data, including mortgage, owner transfer, pre-foreclosure, and historical and contemporary tax assessment data. Data is bundled into pipe-delimited text files, which are uploaded to Data Farm (Redivis) for preview, extraction and analysis.

For more information about how the data was prepared for Redivis, please see CoreLogic 2024 GitLab.

Usage

The Property, Mortgage, Owner Transfer, Historical Property and Pre-Foreclosure data can be linked on the CLIP, a unique identification number assigned to each property.

Mortgage records can be linked to a transaction using the MORTGAGE_COMPOSITE_TRANSACTION_ID.

For more information about included variables, please see:

• core_logic_sdp_owner_transfer_data_dictionary_2024.txt
• core_logic_sdp_mortgage_data_dictionary_2024.txt
• Mortgage_v3.xlsx
• Owner Transfer_v3.xlsx

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For a count of records per FIPS code, please see core_logic_sdp_owner_transfer_counts_2024.txt and core_logic_sdp_mortgage_counts_2024.txt.

For more information about how the CoreLogic Smart Data Platform: Owner Transfer and Mortgage data compares to legacy data, please see core_logic_legacy_content_mapping.pdf.

Bulk Data Access

Data access is required to view this section.

Metropolitan Police Department (MPD) Police Service Areas (PSA). The dataset contains polygons representing of MPD PSA, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Police jurisdictions were initially created selecting street arcs from the planimetric street centerlines and street polygons, water polygons, real property boundaries and District of Columbia boundaries.2019 Boundary Changes:Periodically, MPD conducts a comprehensive assessment of our patrol boundaries to ensure optimal operations. This effort considers current workload, anticipated population growth, development, and community needs. The overarching goals for the 2019 realignment effort included: optimal availability of police resources, officer safety and wellness, and efficient delivery of police services. These changes took effect on 01/10/2019. On 03/27/2019, this boundary was modified to adjust dispatching of North Capitol Street’s northwest access roads to be more operationally efficient.

Data source is the Office of Tax and Revenue’s Computer-Assisted Mass Appraisal (CAMA) system. The CAMA system is used by the Assessment Division (AD) within the Real Property Tax Administration to value real estate for ad valorem real property tax purposes.The intent of this data is to provide a sale history for active properties listed among the District of Columbia’s real property tax assessment roll. This data is updated daily. The AD constantly maintains sale data, adding new data and updating existing data. Daily updates represent a “snapshot” at the time the data was extracted from the CAMA system, and data is always subject to change.

🇺🇸 미국 English Metropolitan Police Department (MPD) Police Service Areas (PSA). The dataset contains polygons representing of MPD PSA, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Police jurisdictions were initially created selecting street arcs from the planimetric street centerlines and street polygons, water polygons, real property boundaries and District of Columbia boundaries.2019 Boundary Changes:Periodically, MPD conducts a comprehensive assessment of our patrol boundaries to ensure optimal operations. This effort considers current workload, anticipated population growth, development, and community needs. The overarching goals for the 2019 realignment effort included: optimal availability of police resources, officer safety and wellness, and efficient delivery of police services. These changes took effect on 01/10/2019. On 03/27/2019, this boundary was modified to adjust dispatching of North Capitol Street’s northwest access roads to be more operationally efficient.

🇺🇸 미국 English Metropolitan Police Department (MPD) Police Districts. The dataset contains polygons representing of MPD Districts, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Police jurisdictions were initially created selecting street arcs from the planimetric street centerlines and street polygons, water polygons, real property boundaries and District of Columbia boundaries.2019 Boundary Changes:Periodically, MPD conducts a comprehensive assessment of our patrol boundaries to ensure optimal operations. This effort considers current workload, anticipated population growth, development, and community needs. The overarching goals for the 2019 realignment effort included: optimal availability of police resources, officer safety and wellness, and efficient delivery of police services. These changes took effect on 01/10/2019.On 03/27/2019, this boundary was modified to adjust dispatching of North Capitol Street’s northwest access roads to be more operationally efficient.

The US luxury residential market, encompassing apartments, condominiums, villas, and landed houses, is a dynamic sector exhibiting robust growth. Driven by factors such as increasing high-net-worth individuals, a preference for upscale amenities and locations in prime cities like New York, Los Angeles, and San Francisco, and a sustained demand for second homes and investment properties, the market is projected to maintain a compound annual growth rate (CAGR) exceeding 3% from 2025 to 2033. While rising construction costs and interest rates pose challenges, the inherent resilience of the luxury segment, fueled by a limited supply of high-end properties and consistent demand from affluent buyers, mitigates these constraints. The segment's performance is geographically concentrated, with major metropolitan areas capturing the lion's share of market activity. Prominent developers like Toll Brothers Inc. and D.R. Horton are major players, contributing significantly to the market's supply. However, the market also faces challenges such as regulatory changes affecting construction and zoning, which could influence future growth. Furthermore, fluctuating global economic conditions and shifts in investor sentiment can impact demand in the luxury sector. The market segmentation highlights a strong preference for apartments and condominiums in urban centers, reflecting the lifestyle choices of many high-net-worth individuals. Villas and landed houses remain popular in suburban and rural areas, catering to a different segment of buyers prioritizing privacy and space. The regional analysis indicates that North America, particularly the US, dominates the luxury residential market, although international investment continues to play a significant role. The robust pipeline of luxury projects underway suggests continued growth, driven by sophisticated design, advanced technology integration in homes, and an increasing focus on sustainability. The market's performance will depend on the interplay of economic indicators, evolving consumer preferences, and the effective management of regulatory and infrastructural challenges. Understanding these dynamics is crucial for investors and developers aiming to navigate this lucrative yet complex market segment. Recent developments include: October 2021: Toll Brothers Inc. - the country's leading builder of luxury homes, through its Toll Brothers Campus Living Division and CanAm Capital Partners - the private equity affiliate of CanAm enterprises and a leading provider of project-level structured debt and equity solutions, announced the formation of a new joint venture. This joint venture will develop Lapis, a 1086-bed 293-unit luxury student housing community at Florida International University (FIU) in Miami, Florida. The community will offer luxury amenities, multiple study lounges, high-speed internet throughout the community, a resort-style pool, fitness center, bike storage, club room, outdoor kitchens, business center, and secured garage., November 2021: Toll Brothers Inc. - the nation's leading builder of luxury homes, through its Toll Brothers Apartment Living rental division and Sundance Bay - a leading private real estate investment and operating firm, announced the formation of a new joint venture to develop Broad & Noble. It is a 344-unit mixed-use rental apartment community in Philadelphia, Pa. This 18-story high-rise building will feature high-end luxury finishes, a fitness center, music, media, and podcast rooms; a conservatory and private dining rooms; a yoga and cycling studio, sky lounge with an outdoor deck area. Additionally, it will consist landscaped plaza, private storage areas, an access-controlled garage with bike storage, and a pet spa.. Notable trends are: Home Automation Becoming a Pre-requisite for Luxury Real Estate.

The DC Basemap provides a reference map for the District of Columbia projected in Web Mercator. Access the ArcGIS Rest endpoint. The basemap utilizes the most current planimetric and reference data available and represents the real world with foundation map layers derived from base data collection done in 2023.The service is provided by the Office of the Chief Technology Officer.

Akridge and Stars Investments Ltd (SIL) is undertaking to build an office complex in Washington, the US.The project envisages the construction of a 9,290m2 office building. It includes the construction of meeting rooms, conference facilities, a cafeteria, parking and related facilities.Akridge and SIL plans to turn the office buildings at 1101 and 1111 16th St., N.W., into a single property.In July 2016, Akridge was partnered with SIL to acquire the American Beverage Association (ABA) and the American Association of University Women (AAUW) headquarters buildings.As of September 2016, construction works on the development has been commenced.Hellmuth, Obata + Kassabaum(HOK) has been appointed as the architect.In June 2017, City commissioners voted to support a public space application by Akridge for streetscape improvements as part of its new development at 1101 16th St. NW.Construction works are underway and scheduled for completion by late 2018. Read More

Metropolitan Police Department (MPD) Police Districts. The dataset contains polygons representing of MPD Districts, created as part of the DC Geographic Information System (DC GIS) for the D.C. Office of the Chief Technology Officer (OCTO) and participating D.C. government agencies. Police jurisdictions were initially created selecting street arcs from the planimetric street centerlines and street polygons, water polygons, real property boundaries and District of Columbia boundaries.2019 Boundary Changes:Periodically, MPD conducts a comprehensive assessment of our patrol boundaries to ensure optimal operations. This effort considers current workload, anticipated population growth, development, and community needs. The overarching goals for the 2019 realignment effort included: optimal availability of police resources, officer safety and wellness, and efficient delivery of police services. These changes took effect on 01/10/2019.On 03/27/2019, this boundary was modified to adjust dispatching of North Capitol Street’s northwest access roads to be more operationally efficient.

This map displays quarter-mile hexagons that show concentrations of public charging market demand from electric vehicles (EVs) estimated to lack home charging and nearby public charging within 2 miles. Additional layers can be toggled on and off to view locations of low-income or disadvantaged communities, urban or rural areas, and federally recognized tribal lands*.Results are based off model estimates from the SB 1000 assessment. See the 2025 SB 1000 Staff Report for a full description of data sources and methodology.While EVs without home charging may access charging in a variety of ways, this map shows market demand for two types of near-home public charging:Nearby charging: Public Level 2 or direct-current (DC) fast charging within two miles of households that can be used for short-duration charging. Walking-distance charging: Public Level 2 charging within an eighth of a mile of households that can be used for long-duration charging such as overnight charging. While the above scenarios are used for this assessment, staff note that the availability of near-home public charging is subject to many variables, potentially including existing land use, zoning, and local permitting.Two utilization options for public charging capacity are available:Under the high utilization option, a public Level 2 charger that is located within an eighth of a mile of households (walking distance) can adequately serve 5 EVs without home charging - 3 EVs overnight on separate nights and 2 EVs during the day. A public DC fast charger located within 2 miles of households (within the neighborhood) can adequately serve 30 EVs without home charging, all during the day since DC fast chargers would not be used for long-duration charging, such as overnight charging.Under the low utilization option, a public Level 2 charger located within an eighth of a mile of households can adequately serve 3 EVs without home charging - 2 EVs overnight on separate nights and 1 EV during the day. A public DC fast charger located within 2 miles of households can adequately serve 20 EVs without home charging during the day.Navigate Layers, Legends, and Basemaps The default map layer shows market demand for public nearby charging from EVs in 2024. EVs contribute to market demand if they are estimated to lack home charging and do not have sufficient existing public Level 2 or DC fast charging within 2 miles of home (in the high utilization option). To view additional layers, click on the Layers icon, which can be found in the left sidebar menu. All layers can be turned on and off. To turn a layer on or off, click on the eye icon to the right of the layer name. To view market demand for other utilization options or demand for other types of charging, turn off the default layer and turn on a different market demand layer. To view concentrations of 2024 EVs without home charging and EVs in a 100% EV future without home charging, turn off the Public Nearby (2-miles) Charging Demand From EVs Without Home Charging layer and turn on the 2024 EVs Without Home Charging or the EVs in a 100% EV Future Without Home Charging layer. Zoom into the map to view public charging station locations as of March 2025 and click on the stations to view additional charger information.Turn on the Low-income or Disadvantaged Community, Urban or Rural, or Federally Recognized Tribal Lands layer to see how these communities overlap with model estimates of market demand and EVs without home charging. Click on the Legend icon, which can be found in the left sidebar menu, to see legends for the layers turned on. Click on the Basemap icon to change the map backdrop. Identify Potential Sites If the goal is to see market demand for public nearby charging within low-income or disadvantaged community areas, turn on the Low-income or Disadvantaged Community layer and Public Nearby (2-miles) Charging Demand From EVs Without Home Charging (high or low utilization option) layer. Alternatively, if the goal is to see market demand for public walking-distance charging within an urban or rural area, turn on the Urban or Rural layer and Public Walking-Distance (1/8th mile) Level 2 Charging Demand From EVs Without Home Charging (high or low utilization option) layer. Click on the magnifying glass on the bottom right of the map, type in an address, and press enter to see if the site is within the layers of interest. *The CEC purchased property and parcel boundary data from CoreLogic, Incorporated that includes information on parcel location, ownership, tax assessment, and property characteristics. This data was used to estimate home charging barriers and likeliness of not having a home charger. In general, tribal lands are exempt from local and state taxation, including property taxes. Therefore, property data to assess barriers to having a home charger may be sparse in federally recognized tribal lands. CoreLogic, Inc. and/or its subsidiaries retain all ownership rights in the data, which end user agree is proprietary to CoreLogic. All Rights Reserved. The data is provided AS IS; end user assumes all risk on any use or reliance on the data.