This dataset is a compilation of address point data for the City of Tempe. The dataset contains a point location, the official address (as defined by The Building Safety Division of Community Development) for all occupiable units and any other official addresses in the City. There are several additional attributes that may be populated for an address, but they may not be populated for every address. Contact: Lynn Flaaen-Hanna, Development Services Specialist Contact E-mail Link: Map that Lets You Explore and Export Address Data Data Source: The initial dataset was created by combining several datasets and then reviewing the information to remove duplicates and identify errors. This published dataset is the system of record for Tempe addresses going forward, with the address information being created and maintained by The Building Safety Division of Community Development.Data Source Type: ESRI ArcGIS Enterprise GeodatabasePreparation Method: N/APublish Frequency: WeeklyPublish Method: AutomaticData Dictionary

Updated Continually

National Address DatabaseThis National Geospatial Data Asset (NGDA) dataset, shared as a U.S. Department of Transportation (USDOT) feature layer, displays address data in the United States. Per USDOT, "The U.S. Department of Transportation (USDOT) and its partners from all levels of government recognize the need for a National Address Database (NAD). Accurate and up-to-date addresses are critical to transportation safety and are a vital part of Next Generation 9-1-1. They are also essential for a broad range of government services, including mail delivery, permitting, and school siting. To meet this need, USDOT partners with address programs from state, local, and tribal governments to compile their authoritative data into the NAD."District of Columbia (DC) Residential AddressesData currency: Current federal service (Address Points from National Address Database)NGDAID: 196 (National Address Database (NAD))For more information: Getting to know the National Address Database (NAD); National Address DatabaseFor feedback, please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Transportation Theme Community. Per the Federal Geospatial Data Committee (FGDC), Transportation is defined as the "means and aids for conveying persons and/or goods. The transportation system includes both physical and non-physical components related to all modes of travel that allow the movement of goods and people between locations".For other NGDA Content: Esri Federal Datasets

This map shows site address points in the City of San José and provides tools to select and download address data. Addresses are part of the City's Master Address Database (MAD), which is a comprehensive database containing authoritative physical/site addresses. Mailing addresses may differ from site addresses.This map was created for the City of San José public maps gallery. The maps gallery is a collection of maps created and maintained by the Enterprise GIS team. Maps gallery maps showcase programs, projects, and spatial information derived from City data. The information in these maps is publicly shared for the purpose of transparency and accessibility. Many maps from the maps gallery are also embedded with the City website. Much of the data that supports these maps can be directly downloaded from the Open GIS Data Portal. City of San Jose Website: https://www.sanjoseca.gov/City of San Jose Maps Gallery: https://gis.sanjoseca.gov/apps/mapsgallery/City of San Jose Open GIS Data Portal: https://gisdata-csj.opendata.arcgis.com/

This is the domain table for Address Points (designated by the Chief Data Officer (CDO) per Mayor’s Order 2017-115). Districtwide domain tables are database tables designated by the CDO to provide a standard source of values to be used across District information systems and data transformations, as defined by the Open Data Policy. The source table for thisis the DCGIS.AddressPtlayer.https://octo.dc.gov/page/district-columbia-data-policy

A global self-hosted Market Research dataset containing all administrative divisions, cities, addresses, and zip codes for 247 countries. All geospatial data is updated weekly to maintain the highest data quality, including challenging countries such as China, Brazil, Russia, and the United Kingdom.

Use cases for the Global Zip Code Database (Market Research data)

• Address capture and validation

• Map and visualization

• Reporting and Business Intelligence (BI)

• Master Data Mangement

• Logistics and Supply Chain Management

• Sales and Marketing

Data export methodology

Our map data packages are offered in variable formats, including .csv. All geographic data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Product Features

• Fully and accurately geocoded

• Administrative areas with a level range of 0-4

• Multi-language support including address names in local and foreign languages

• Comprehensive city definitions across countries

For additional insights, you can combine the map data with:

• UNLOCODE and IATA codes

• Time zones and Daylight Saving Times

Why do companies choose our Market Research databases

• Enterprise-grade service

• Reduce integration time and cost by 30%

• Weekly updates for the highest quality

Note: Custom geographic data packages are available. Please submit a request via the above contact button for more details.

This dataset comes from the Open National Address Base project initiated by OpenStreetMap France.

For more information on this project: http://openstreetmap.fr/blogs/cquest/bano-banco

Origin of data

• OpenStreetMap
• data available in opendata
• address data collected on the cadastral site (source DGFiP 2014)

Distribution format

These files are available in shapefile format, in WGS84 projection (EPSG :4326) as well as in CSV format and experimentally as github project.

Description of content

For each address:

• id (unique): code_insee + codefantoir + number
• number: street number with suffix (e.g.: 1, 1BIS, 1D)
• street: street name
• post_code: 5-character postcode
• city: name of the municipality
• source: OSM = data directly from OpenStreetMap, OD = data from local opendata sources, CAD = data directly from the cadastre, C+O = cadastre data enriched by OSM (road name for example)
• lat: latitude in WGS84 decimal degrees
• lon: longitude in WGS84 decimal degrees

updates, corrections

To update and correct BANO data, simply make improvements directly in OpenStreetMap, they will be taken into account in the next update cycle.

A one-stop collaborative reporting/correction window will soon be set up to simplify the process of improving the content of the database. To participate in its co-construction, do not hesitate to contact us!

For any questions concerning the project or this dataset, you can contact bano@openstreetmap.fr

Welcome to Apiscrapy, your ultimate destination for comprehensive location-based intelligence. As an AI-driven web scraping and automation platform, Apiscrapy excels in converting raw web data into polished, ready-to-use data APIs. With a unique capability to collect Google Address Data, Google Address API, Google Location API, Google Map, and Google Location Data with 100% accuracy, we redefine possibilities in location intelligence.

Key Features:

Unparalleled Data Variety: Apiscrapy offers a diverse range of address-related datasets, including Google Address Data and Google Location Data. Whether you seek B2B address data or detailed insights for various industries, we cover it all.

Integration with Google Address API: Seamlessly integrate our datasets with the powerful Google Address API. This collaboration ensures not just accessibility but a robust combination that amplifies the precision of your location-based insights.

Business Location Precision: Experience a new level of precision in business decision-making with our address data. Apiscrapy delivers accurate and up-to-date business locations, enhancing your strategic planning and expansion efforts.

Tailored B2B Marketing: Customize your B2B marketing strategies with precision using our detailed B2B address data. Target specific geographic areas, refine your approach, and maximize the impact of your marketing efforts.

Use Cases:

Location-Based Services: Companies use Google Address Data to provide location-based services such as navigation, local search, and location-aware advertisements.

Logistics and Transportation: Logistics companies utilize Google Address Data for route optimization, fleet management, and delivery tracking.

E-commerce: Online retailers integrate address autocomplete features powered by Google Address Data to simplify the checkout process and ensure accurate delivery addresses.

Real Estate: Real estate agents and property websites leverage Google Address Data to provide accurate property listings, neighborhood information, and proximity to amenities.

Urban Planning and Development: City planners and developers utilize Google Address Data to analyze population density, traffic patterns, and infrastructure needs for urban planning and development projects.

Market Analysis: Businesses use Google Address Data for market analysis, including identifying target demographics, analyzing competitor locations, and selecting optimal locations for new stores or offices.

Geographic Information Systems (GIS): GIS professionals use Google Address Data as a foundational layer for mapping and spatial analysis in fields such as environmental science, public health, and natural resource management.

Government Services: Government agencies utilize Google Address Data for census enumeration, voter registration, tax assessment, and planning public infrastructure projects.

Tourism and Hospitality: Travel agencies, hotels, and tourism websites incorporate Google Address Data to provide location-based recommendations, itinerary planning, and booking services for travelers.

Discover the difference with Apiscrapy – where accuracy meets diversity in address-related datasets, including Google Address Data, Google Address API, Google Location API, and more. Redefine your approach to location intelligence and make data-driven decisions with confidence. Revolutionize your business strategies today!

The AIMS: Address data table contains details relating to the creation and updating of an address including the version of an address and is part of the AIMS: Street Address.

Refer to the NZ Addresses Data Dictionary for detailed metadata and information about this dataset.

Background

This dataset provides all allocated addresses as advised to Toitū Te Whenua LINZ by Territorial Authorities (TAs). Under the Local Government Act 1974 (section 319) it is the responsibility of the TAs to advise the Surveyor-General at Toitū Te Whenua LINZ of all allocated addresses in their district.

The dataset is maintained by Toitū Te Whenua LINZ in the Address Information Management System (AIMS) which is centralised database for the management of national addresses, including for electoral purposes. This dataset is updated weekly on the LINZ Data Service.

For a simplified version of the data contained within these tables see NZ Addresses

Connecticut address point dataset used for locating 9-1-1 calls. The address point feature class format is derived from National Emergency Number Association (NENA) and Federal Geographic Data Committee (FGDC) addressing standards. All address components, like address number, streets name and unit number, are broken up into their individual components to enable maximum flexibility for use. Fields within feature class should be able to accommodate all addresses within the state of Connecticut. The source for the addresses is primarily derived from municipal parcel data and other municipal sources.

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. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

Address Creation, LLC Whois Database, discover comprehensive ownership details, registration dates, and more for Address Creation, LLC with Whois Data Center.

Mail carriers routinely collect data on address no longer receiving mail due to vacancy. This vacancy data is reported quarterly at census tract geographies in the United States for residential, commercial, and industrial properties along with counts of total mailing addresses.

Preprocessing/Formatting

The data is split into separate tables because different decades of data use different US Census geographies (e.g., 2010 U.S. Census tracts).

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

Address points were developed to supplement the address information supplied by the CSCL centerline. Some computer aided dispatch systems use address points as the primary source for locating an address. For additional information and resources, please visit https://nycmaps-nyc.hub.arcgis.com/datasets/nyc::address-point/about

This dataset is an enrichment of the INSEE dataset (SIRENE database of enterprises and their establishments (SIREN, SIRET)) (https://www.data.gouv.fr/en/datasets/base-sirene-des-entreprises-et-de-leurs-etablissements-siren-siret/). This enriches the original base as follows: - Breakdown of the StockEstablishment file by geographical grid: departments and municipalities. - Addition of a number of columns relating to the geolocation of establishments based on the most relevant proximity score between the address indicated in the SIRENE database and the National Address Database or the Points of Interest of Openstreetmap. - Longitude field: longitude of the establishment - Field "latitude": Latitude of establishment - Field geo_score: Trust score returned by the addok geocoder (between 0 and 1, the higher the score, the more relevant the geocoding seems) - Field geo_type: type of address found - Field geo_address: wording of the address found - Field geo_id: identifier of this address in the source database where it was found (BAN or POI) - Field geo_line: which address line of the SIRENE database could be geocoded (G=geographical, D=declared, N=normalized) - Field geo_l4: line 4 to standard AFNOR address - Field geo_l5: line 5 to standard AFNOR address The processing allowing the production of this dataset is carried out by Etalab. It is largely inspired by the previous work of Christian Quest available here. This processing is based on the geocoder Addok. This dataset is used in the search engine of the business directory and in its API (https://api.gouv.fr/les-api/api-recherche-entreprises).

The pathway representation consists of segments and intersection elements. A segment is a linear graphic element that represents a continuous physical travel path terminated by path end (dead end) or physical intersection with other travel paths. Segments have one street name, one address range and one set of segment characteristics. A segment may have none or multiple alias street names. Segment types included are Freeways, Highways, Streets, Alleys (named only), Railroads, Walkways, and Bike lanes. SNDSEG_PV is a linear feature class representing the SND Segment Feature, with attributes for Street name, Address Range, Alias Street name and segment Characteristics objects. Part of the Address Range and all of Street name objects are logically shared with the Discrete Address Point-Master Address File layer. Appropriate uses include: Cartography - Used to depict the City's transportation network location and connections, typically on smaller scaled maps or images where a single line representation is appropriate. Used to depict specific classifications of roadway use, also typically at smaller scales. Used to label transportation network feature names typically on larger scaled maps. Used to label address ranges with associated transportation network features typically on larger scaled maps. Geocode reference - Used as a source for derived reference data for address validation and theoretical address location Address Range data repository - This data store is the City's address range repository defining address ranges in association with transportation network features. Polygon boundary reference - Used to define various area boundaries is other feature classes where coincident with the transportation network. Does not contain polygon features. Address based extracts - Used to create flat-file extracts typically indexed by address with reference to business data typically associated with transportation network features. Thematic linear location reference - By providing unique, stable identifiers for each linear feature, thematic data is associated to specific transportation network features via these identifiers. Thematic intersection location reference - By providing unique, stable identifiers for each intersection feature, thematic data is associated to specific transportation network features via these identifiers. Network route tracing - Used as source for derived reference data used to determine point to point travel paths or determine optimal stop allocation along a travel path. Topological connections with segments - Used to provide a specific definition of location for each transportation network feature. Also provides a specific definition of connection between each transportation network feature. (defines where the streets are and the relationship between them ie. 4th Ave is west of 5th Ave and 4th Ave does intersect with Cherry St) Event location reference - Used as source for derived reference data used to locate event and linear referencing.Data source is TRANSPO.SNDSEG_PV. Updated weekly.

The National Address Base is one of the nine public reference data service databases. It is the only address database officially recognized by the administration.

Digital service for shared use and basic infrastructure on which many public policies are based, it is part of the information system and communication of the State and is as such placed under the responsibility of the Prime Minister.

Its management is ensured by the Interministerial Digital Directorate (DINUM), which is responsible for define the terms of governance and operation (following a decision by the Prime Minister).

Its construction is ensured thanks to numerous partners, and primarily by the municipalities , the only competent authorities in terms of addressing.

This dataset shows the Address Points in Allegheny County. The Address Points were created by GDR for the Allegheny County CAD project, October 2008. Data is updated by County staff as changes and corrections are found, on a continuous basis. Updates are sent to PASDA monthly. The most authoritative source for this data is now the PASDA page (https://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=1219), which includes links to historical versions of the shapefile representations of this data.

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. The Address Ranges Feature Shapefile (ADDRFEAT.dbf) contains the geospatial edge geometry and attributes of all unsuppressed address ranges for a county or county equivalent area. The term "address range" refers to the collection of all possible structure numbers from the first structure number to the last structure number and all numbers of a specified parity in between along an edge side relative to the direction in which the edge is coded. Single-address address ranges have been suppressed to maintain the confidentiality of the addresses they describe. Multiple coincident address range feature edge records are represented in the shapefile if more than one left or right address ranges are associated to the edge. The ADDRFEAT shapefile contains a record for each address range to street name combination. Address range associated to more than one street name are also represented by multiple coincident address range feature edge records. Note that the ADDRFEAT shapefile includes all unsuppressed address ranges compared to the All Lines Shapefile (EDGES.shp) which only includes the most inclusive address range associated with each side of a street edge. The TIGER/Line shapefile contain potential address ranges, not individual addresses. The address ranges in the TIGER/Line Files are potential ranges that include the full range of possible structure numbers even though the actual structures may not exist.

This dataset contains a list of addresses with details such as names, streets, cities, states, and ZIP codes. The data appears to be formatted in CSV, capturing various individual and location entries.