OS Code-Point® Open is an OpenData postcode-level dataset providing a point location for all geographic postal codes in Great Britain. The gazetteer service allows geocoding and postcode searching against this dataset. It is ideal for a variety of uses including planning A to B journeys, performing analysis, managing assets (such as premises) or utilising postcode lookups. Attributes: Postcode units, eastings, northings, positional quality indicator, NHS® regional health authority code, NHS health authority code, country code, administrative county code, administrative district code and administrative ward code.Data Currency: February 2022
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Open Postcode Geo is a postcode dataset and API optimised for geocoding applications. You can use Open Postcode Geo to geocode a dataset, geocode user input, and therefore build a proximity search.
Data is derived from the ONS (Office for National Statistics) postcode database and is free to use, subject to including attributions to ONS, OS (Ordinance Survey) and Royal Mail.
Information is also provided on a range of topics, including education, health, crime, business, etc.
Postcodes can be entered at area, district, sector, and unit level - see Postcode map for the geographical relationship between these.
Postal codes are part of nearly every administrative and research data set, and postal code conversion using PCCF or PCCF+ and related tools is now the usual way of exploiting their rather impressive potential. The resulting small area geography and/or latitude-longitude coordinates have a wide variety of possible uses, even where individual measures of SES are also available on a data set. Familiarity with the methods (tools and techniques), as well as the strengths and limitations of dealing with postal coded data, will allow data service providers to help users to more meaningfully exploit their potential.
This data collection consists of UK postcodes with additional geospace fields including easting, northing, latitude, longitude, positional quality indicator, postcode area, postcode district, postcode sector, outcode, incode.
Designed for applications which require a dataset of addresses to be geocoded, or organised in a geographical hierarchy based on postcode.
Derived from the ONS Postcode Directory which is licensed under the Open Government Licence(see Related Resources). Updated quarterly.
Geoscape G-NAF is the geocoded address database for Australian businesses and governments. It’s the trusted source of geocoded address data for Australia with over 50 million contributed addresses distilled into 15.4 million G-NAF addresses. It is built and maintained by Geoscape Australia using independently examined and validated government data.
From 22 August 2022, Geoscape Australia is making G-NAF available in an additional simplified table format. G-NAF Core makes accessing geocoded addresses easier by utilising less technical effort.
G-NAF Core will be updated on a quarterly basis along with G-NAF.
Further information about contributors to G-NAF is available here.
With more than 15 million Australian physical address record, G-NAF is one of the most ubiquitous and powerful spatial datasets. The records include geocodes, which are latitude and longitude map coordinates. G-NAF does not contain personal information or details relating to individuals.
Updated versions of G-NAF are published on a quarterly basis. Previous versions are available here
Users have the option to download datasets with feature coordinates referencing either GDA94 or GDA2020 datums.
Changes in the February 2025 release
Nationally, the February 2025 update of G-NAF shows an overall increase of 47,284 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,706,733 of which 14,867,032 or 94.65% are principal.
In the February 2025 release of G-NAF, over 300 addresses in Morra, Western Australia have been updated. About 150 addresses have changed locations and 160 properties now have street numbers instead of lot numbers. Some properties are still using lot-numbers, resulting in two addressees. This issue will be resolved in the May 2025 update of G-NAF.
In the February release, Geoscape has re-classified geocode types of ‘Property Access Point Setback’ (PAPS) to be ‘Property Access Point’ (PAP) in South Australia where the geocode falls within a road casement as the geocode is not set back into a land parcel. This update has changed approximately 57,000 geocodes to PAP from their previous classification of PAPS, while there are some 14,000 PAPS geocodes that remain unchanged.
Geoscape has moved product descriptions, guides and reports online to https://docs.geoscape.com.au.
Further information on G-NAF, including FAQs on the data, is available here or through Geoscape Australia’s network of partners. They provide a range of commercial products based on G-NAF, including software solutions, consultancy and support.
Additional information: On 1 October 2020, PSMA Australia Limited began trading as Geoscape Australia.
Use of the G-NAF downloaded from data.gov.au is subject to the End User Licence Agreement (EULA)
The EULA terms are based on the Creative Commons Attribution 4.0 International license (CC BY 4.0). However, an important restriction relating to the use of the open G-NAF for the sending of mail has been added.
The open G-NAF data must not be used for the generation of an address or the compilation of an address for the sending of mail unless the user has verified that each address to be used for the sending of mail is capable of receiving mail by reference to a secondary source of information. Further information on this use restriction is available here.
End users must only use the data in ways that are consistent with the Australian Privacy Principles issued under the Privacy Act 1988 (Cth).
Users must also note the following attribution requirements:
Preferred attribution for the Licensed Material:
_G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the _Open Geo-coded National Address File (G-NAF) End User Licence Agreement.
Preferred attribution for Adapted Material:
Incorporates or developed using G-NAF © Geoscape Australia licensed by the Commonwealth of Australia under the Open Geo-coded National Address File (G-NAF) End User Licence Agreement.
G-NAF is a complex and large dataset (approximately 5GB unpacked), consisting of multiple tables that will need to be joined prior to use. The dataset is primarily designed for application developers and large-scale spatial integration. Users are advised to read the technical documentation, including product change notices and the individual product descriptions before downloading and using the product. A quick reference guide on unpacking the G-NAF is also available.
The Postal Code Conversion File (PCCF) is a digital file which provides a correspondence between the Canada Post Corporation (CPC) six-character postal code and Statistics Canada's standard geographic areas for which census data and other statistics are produced. Through the link between postal codes and standard geographic areas, the PCCF permits the integration of data from various sources. The Single Link Indicator provides one best link for every postal code, as there are multiple records for many postal codes. To obtain the postal code conversion file or for questions, consult the DLI contact at your educational institution. The geographic coordinates attached to each postal code on the PCCF are commonly used to map the distribution of data for spatial analysis (e.g., clients, activities). The location information is a powerful tool for planning, or research purposes. In April 1983, the Geography Division released the first version of the PCCF, which linked postal codes to 1981 Census geographic areas and included geographic coordinates. Since then, the file has been updated on a regular basis to reflect changes. For this release of the PCCF, the vast majority of the postal codes are directly geocoded to 2006 Census geography. This improves precision of the file over the previous conversion process used to align postal code linkages to new geographic areas after each census. About 94% of the postal codes were linked to geographic areas using the new automated process. A quality indicator for the confidence of this linkage is available in the PCCF.
Address ranges describe a label given to a unique collection of addresses that fall along a road or path. Address ranges provide a way of locating homes and businesses based on their street addresses when no other location information is available.Using a house number, street name, street side and ZIP code, address ranges can locate the address to the geographic area associated to that side of the street. Once geocoded, the U.S. Census Bureau can assign the address to a field assignment area or tabulate the data for that address. In addition, academics, researchers, professionals and government agencies outside of the Census Bureau use MAF/TIGER address ranges to transform tabular addresses into geographical datasets for decision-making and analytical purposes.Address ranges must be unique to geocode addresses to the correct location and avoid geocoding conflicts. Multiple elements in MAF/TIGER are required to make an address range unique including street names, address house numbers and street feature geometries, such as street centerlines. The address range data model is designed to maximize geocoding matches with their correct geographic areas in MAF/TIGER by allowing an unlimited number of address range-to-street feature relationships.The Census Bureau’s Geography Division devises numerous operations and processes to build and maintain high quality address ranges so that:Address ranges accurately describe the location of addresses on the ground.Address All possible city-style addresses are geocoded.Address ranges can handle all known address and street name variations.Address ranges conform with current U.S. Postal Service ZIP codes.Address ranges are reliable and free from conflicts.Automated software continually updates existing address ranges, builds new address ranges and corrects errors. An automated operation links address location points and tabular address information to street feature edges with matching street names in the same block to build and modify address ranges.Many business rules and legal value checks ensure quality address range data in MAF/TIGER. For example, business rules prevent adding or modifying address ranges that overlap another house number range with the same street name and ZIP code. Legal value checks verify that address ranges include mandatory attribute information, valid data types and valid character values.Some of the TIGER/Line products for the public include address ranges and give the public the ability to geocode addresses to MAF/TIGER address ranges for the user’s own purpose. The address range files are available for the nation, Puerto Rico and the U.S. Island Areas at the county level. TIGER/Line files require geographic information system (GIS) software to use.The Census Bureau Geocoder Service is a web service provided to the public. The service accepts up to 1,000 input addresses and, based on Census address ranges, returns the interpolated geocoded location and census geographies. Users can access the service a web interface or a representational state transfer (REST) application program interface (API) web service.Download: https://www2.census.gov/geo/tiger/TGRGDB24/tlgdb_2024_a_us_addr.gdb.zip
The Postal Code Project is responsible for linking the approximately 900,000 single postal codes in Canada to Statistics Canada’s Census dissemination geography, (presently 2021 Census geography). This process is performed by using data provided by Canada Post Corporation and linking to Census Dissemination geography via the process of geocoding. The result is the creation of the Postal Code Conversion File (PCCF) which provides a correspondence between the six character postal code and Statistics Canada’s standard geographical areas, and also the Postal Codes by Federal Ridings File (PCFRF) which provides a link between the six character postal code and Canada’s federal electoral districts.
This Africa Geocoding locator is a view of the World Geocoding Service constrained to search for places in the countries of Africa. The World Geocoding Service finds addresses and places in all supported countries around the world in a single geocoding service. The service can find point locations of addresses, cities, landmarks, business names, and other places. The output points can be visualized on a map, inserted as stops for a route, or loaded as input for a spatial analysis.The service is available as both a geosearch and geocoding service:Geosearch Services – The primary purpose of geosearch services is to locate a feature or point of interest and then have the map zoom to that location. The result might be displayed on the map, but the result is not stored in any way for later use. Requests of this type do not require a subscription or a credit fee. Geocoding Services – The primary purpose of geocoding services is to convert an address to an x,y coordinate and append the result to an existing record in a database. Mapping is not always involved, but placing the results on a map may be part of a workflow. Batch geocoding falls into this category. Geocoding requires a subscription. An ArcGIS Online subscription will provide you access to the World Geocoding service for batch geocoding.The service can be used to find address and places for many countries around the world. For detailed information on this service, including a data coverage map, visit the World Geocoding service documentation.
The Postal Code Project is responsible for linking the approximately 900,000 single postal codes in Canada to Statistics Canada’s Census dissemination geography, (presently 2021 Census geography). This process is performed by using data provided by Canada Post Corporation and linking to Census Dissemination geography via the process of geocoding. The result is the creation of the Postal Code Conversion File (PCCF) which provides a correspondence between the six character postal code and Statistics Canada’s standard geographical areas, and also the Postal Codes by Federal Ridings File (PCFRF) which provides a link between the six character postal code and Canada’s federal electoral districts.
https://www.ons.gov.uk/methodology/geography/licenceshttps://www.ons.gov.uk/methodology/geography/licences
This is the ONS Postcode Directory (ONSPD) for the United Kingdom as at November 2022 in Comma Separated Variable (CSV) and ASCII text (TXT) formats. This file contains the multi CSVs so that postcode areas can be opened in MS Excel. To download the zip file click the Download button. The ONSPD relates both current and terminated postcodes in the United Kingdom to a range of current statutory administrative, electoral, health and other area geographies. It also links postcodes to pre-2002 health areas, 1991 Census enumeration districts for England and Wales, 2001 Census Output Areas (OA) and Super Output Areas (SOA) for England and Wales, 2001 Census OAs and SOAs for Northern Ireland and 2001 Census OAs and Data Zones (DZ) for Scotland. It now contains 2021 Census OAs and SOAs for England and Wales. It helps support the production of area based statistics from postcoded data. The ONSPD is produced by ONS Geography, who provide geographic support to the Office for National Statistics (ONS) and geographic services used by other organisations. The ONSPD is issued quarterly. (File size - 234 MB)Please note that this product contains Royal Mail, Gridlink, LPS (Northern Ireland), Ordnance Survey and ONS Intellectual Property Rights.
Public Housing was established to provide decent and safe rental housing for eligible low-income families, the elderly, and persons with disabilities. Public housing comes in all sizes and types, from scattered single family houses to high-rise apartments for elderly families. There are approximately 1.2 million households living in public housing units, managed by over 3,300 housing agencies (HAs). HUD administers Federal aid to local housing agencies (HAs) that manage the housing for low-income residents at rents they can afford. HUD furnishes technical and professional assistance in planning, developing and managing these developments. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. Data Dictionary: DD_Public Housing Authorities Date Updated: 12/2024 Q3 2024
US Postal Service ZIP Code boundaries. This layer was created by Los Angeles County eGIS to align with parcel boundaries.ZIP is an acronym for Zone Improvement Plan.Legal vs. Postal Cities: Many users confuse the name the Post Office delivers mail to (e.g. Van Nuys, Hollywood) as a legal city (in this case Los Angeles), when they are a postal city. The County contains 88 legal cities, and over 400 postal names that are tied to the ZIP Codes. To support usability and geocoding, we have attached the first 3 postal cities to each address, based upon its ZIP Code.The US Postal Service is the authoritative source for ZIP Code data. See their website for more information.
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Previous studies mainly focus on socio-demographic variables and observable behavior.Our goal was to link these variables with information on lifestyles and personal characteristics. Consequently, the questionnaire revolved around the core research questions “Who is cycling?” and “Why are they cycling?” In order to answer these questions, we collected data in three different categories: personal, behavioral, and motivational.In total, 569 female, 501 male, and 3 non-binary participants completed the survey. The mean age of the participants was 42 years (σ = 12.75) with a range between 7 and 80 years.The age difference between female ( = 40.75, σ = 12.59) and male ( = 43.43, σ = 12.79) participants was highly significant (t = −3.45, p < 0.001). Participants with non-binary gender had an average age of 32 years (σ = 6.16).This subset dataset only includes those records that could be georeferenced using an Austrian ZIP Code.In terms of educational background, the dataset inclined towards highly educated persons; 60.34% of all participants had a university degree, whereas the percentage is 25.18% in the city of Salzburg and 17.0% in the surrounding district (Salzburg-Umgebung) according to official statistics [10]. Participants with compulsory school as highest degree were underrepresented in our sample (0.65% compared to 21.66% and 11.86%, respectively, in the two reference-districts).The majority of respondents were frequent cyclists and among them, 38.40% were using the bicycle more than once a day. In the survey, 2.80% of all participants were non-cyclists. Compared to national and regional modal split statistics, cyclists were overrepresented in the sample. The primary trip purpose of all the respondents was commuting to work, university, or school. Thus, we can conclude that the dataset represented the perspectives of mainly utilitarian cyclists.Further information is available: https://www.mdpi.com/2306-5729/4/4/140
Planning applications details for applications from 2010 to 2014. Locations have been geocoded based on postcode where available.
The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Face refers to the areal (polygon) topological primitives that make up MTDB. A face is bounded by one or more edges; its boundary includes only the edges that separate it from other faces, not any interior edges contained within the area of the face. The Topological Faces Shapefile contains the attributes of each topological primitive face. Each face has a unique topological face identifier (TFID) value. Each face in the shapefile includes the key geographic area codes for all geographic areas for which the Census Bureau tabulates data for both the 2020 Census and the annual estimates and surveys. The geometries of each of these geographic areas can then be built by dissolving the face geometries on the appropriate key geographic area codes in the Topological Faces Shapefile.
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Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian Improved Surname Geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the level of geography used in this process varies widely. Whereas some existing work makes use of geocoding to place individuals in precise census blocks, a substantial portion either skips geocoding altogether or relies on estimation using surname or county-level analyses. Presently, the tradeoffs of such variation are unknown. In this letter we quantify those tradeoffs through a validation of BISG on Georgia’s voter file using both geocoded and non-geocoded processes and introduce a new level of geography--ZIP codes--to this method. We find that when estimating the racial identification of White and Black voters, non-geocoded ZIP code-based estimates are acceptable alternatives. However, census blocks provide the most accurate estimations when imputing racial identification for Asian and Hispanic voters. Our results document the most efficient means to sequentially conduct BISG analysis to maximize racial identification estimation while simultaneously minimizing data missingness and bias.
OS Open Names is an OpenData dataset that includes place names, road names and numbers and postcode for Great Britain and includes 2.5 million locations. The OS Open Names locator allows geocoding and searching against postcodes, street names, road numbers and places all in a single locator.
For more information about the OS Open Names dataset visit the following link: https://www.ordnancesurvey.co.uk/business-and-government/products/os-open-names.htmlData currency : January 2022
HUD furnishes technical and professional assistance in planning, developing and managing these developments. Public Housing Developments are depicted as a distinct address chosen to represent the general location of an entire Public Housing Development, which may be comprised of several buildings scattered across a community. The building with the largest number of units is selected to represent the location of the development. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information (PII), the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. To learn more about Public Housing visit: https://www.hud.gov/program_offices/public_indian_housing/programs/ph/ Data Dictionary: DD_Public Housing Developments Date Updated: 12/2024 Q3 2024
A list of speed limiter centres where vehicles can have a speed limiter tested or repaired. Data includes addresses, postcodes and WGS84 Latitude, WGS84 Longitude
OS Code-Point® Open is an OpenData postcode-level dataset providing a point location for all geographic postal codes in Great Britain. The gazetteer service allows geocoding and postcode searching against this dataset. It is ideal for a variety of uses including planning A to B journeys, performing analysis, managing assets (such as premises) or utilising postcode lookups. Attributes: Postcode units, eastings, northings, positional quality indicator, NHS® regional health authority code, NHS health authority code, country code, administrative county code, administrative district code and administrative ward code.Data Currency: February 2022