This dataset contains geocoded data for Ebola financing commissioned by USAID to clinics in Sub-Saharan Africa.

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 Street_and_Address_Composite will return a geographic coordinate when a street address is entered. A user can enter an address either manually or by bulk input from a database or other source.The geocoder returns a coordinate pair and standardized address for each input address it is able to match. The NYS ITS Geospatial Services geocoder uses a series of combinations of reference data and configuration parameters to optimize both the likelihood of a match and the quality of the results. The reference data supporting the geocoder is stored in Federal Geographic Data Committee (FGDC) standard.The first composite locator (Street_and_Address_Composite) is made up of the following set of locators which are most likely to return a high quality hit. The locators are listed in the order in which they will be accessed along with a brief description of the locator's source data. These six locators will generate the majority of the results when geocoding addresses.Locator NameSource DataDescription1A_SAM_AP_ZipNameSAM Address PointsSAM address points using the postal zip code name for the city name in the locator.1B_SAM_AP_CTNameSAM Address PointsSAM address points. The city or town name is used for the city name in the locator.1C_SAM_AP_PlaceNameSAM Address PointsSAM address points. The city name is populated using the NYS Villages and Indian Reservations, the Census Designated Places and Alternate Acceptable Zip Code Names from the USPS. These names do not exist everywhere so there will be a limited number of points in this locator.3A_SS_ZipNameNYS Street SegmentsNYS Street Segments dataset using the postal zip code name for the city name in the locator. The location is interpolated from an address range on the street segment. The city name can be different for the left and right sides of the streets.3B_SS_CTNameNYS Street SegmentsNYS Street Segments using the city or town name for the city name in the locator. The location is interpolated from an address range on the street segment.3C_SS_PlaceNameNYS Street SegmentsNYS Street Segments using an alternate place name for the city field. This field is populated using the NYS Villages and Indian Reservations, the Census Designated Places and Alternate Acceptable Zip Code Names from the USPS. These areas do not exist everywhere so there will be a limited number of segments with this attribute. The location is interpolated from an address range on the street segment.For more information about the geocoding service, please visit: https://gis.ny.gov/address-geocoder.For documentation on how to add these locators to ArcGIS, please reference Adding the Statewide Geocoding Web Service. If you would like these locators to be your default locators in ArcGIS, copy DefaultLocators.xml to C:\Users<username>\AppData\Roaming\ESRI\Desktop10.X\Locators, where

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 May 2025 release

• Nationally, the May 2025 update of G-NAF shows an overall increase of 47,194 addresses (0.30%). The total number of addresses in G-NAF now stands at 15,753,927 of which 14,909,770 or 94.64% are principal.

• At some locations, there are unit-numbered addresses that appear to be duplicate addresses. Geoscape is working to identify these locations and include these addresses as separate addresses in G-NAF. To facilitate this process, some secondary addresses have had the word RETAIL added to their building names. In the first instance, this process is being progressively rolled out to identified locations, but it is expected that the requirement for this will become ongoing.

• There is one new locality in G-NAF: Keswick Island, QLD.

• The source data used for generating G-NAF STREET_LOCALITY_POINT data in New South Wales has an updated datum and changed from GDA94 to GDA2020. This has resulted in updates to the STREET_LOCALITY_POINT geometry for approximately 91,000 records, however, more than 95% of these have moved less than a metre.

• 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.

License Information

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.

What to Expect When You Download G-NAF

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.

A comprehensive self-hosted geospatial database of street names, coordinates, and address data ranges for Enterprise use. The address data are georeferenced with industry-standard WGS84 coordinates (geocoding).

All geospatial data are provided in the official local languages. Names and other data in non-Roman languages are also made available in English through translations and transliterations.

Use cases for the Global Address Database (Geospatial data)

• Address capture and validation

• Parcel delivery

• Master Data Management

• Logistics and Shipping

• Sales and Marketing

Additional features

• Fully and accurately geocoded

• Multi-language support

• Address ranges for streets covered by several zip codes

• Comprehensive city definitions across countries

• Administrative areas with a level range of 0-4

• International Address Formats

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

• UNLOCODE and IATA codes (geocoded)

• Time zones and Daylight Saving Time (DST)

• Population data: Past and future trends

Data export methodology

Our location data packages are offered in CSV format. All geospatial data are optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more.

Why companies choose our location databases

• Enterprise-grade service

• Reduce integration time and cost by 30%

• Frequent, consistent updates for the highest quality

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

The growing popularity of location-based services has resulted in the enhancement of resources for producing geographical data and the development of the amount of data kept in geographic databases. The big data stored in databases is valuable for advanced geospatial analysis in several fields, including emergency responses, crime and traffic management, disease surveillance, and more. Geocoding, a crucial preprocessing step in geospatial data analysis, involves retrieving textual descriptions of locations into geographic identifiers. Nevertheless, geocoding outcomes delivered by worldwide service providers neglect various constraints related to textual data, including misspellings, abbreviations, and non-standard names. To overcome this issue, we propose a new approach for enhancing the quality of online geocoding services through the utilization of feature selection techniques. The proposed method is based on text similarity algorithms that are utilized to match the retrieved addresses. Compared to conventional geocoding outcomes, there is potential for an improvement of approximately 10% to 25% in the address-matching procedures employed in online geocoding services. The improvement was accomplished through the utilization of two feature selection methods, specifically mutual information feature selection and minimum redundancy maximum relevance, out of a total of fourteen approaches. Furthermore, the findings indicate that it is appropriate to prioritize character-based text similarity algorithms when comparing addresses retrieved from online geocoding services.

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.

This data asset contains geocoding foreign aid information and programmatic development data that is made available through a wide range of donor, recipient, and other stakeholder-based sources. The geocoded data pertain to clinics receiving financing commissioned by USAID for the purpose of treating Ebola. Data are primarily from Sierra Leone, Liberia, and Guinea.

The ArcGIS 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, or ArcGIS Location Platform Subscription, will provide you access to the ArcGIS 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 ArcGIS World Geocoding service documentation.

Vermont composite geocoding service built with VT E911 data. This service can be used by ArcGIS Pro 2.8.x+ to batch geocode addresses stored in a table. It also can be used as a geocoder with most ArcGIS Online apps, as well as QGIS. [How To Use The Vermont Geocoding Service]This ArcGIS Online item utilizes the ArcGIS Server geocoding service at this REST Endpoint: https://maps.vcgi.vermont.gov/arcgis/rest/services/EGC_services/GCS_E911_COMPOSITE_SP_v2/GeocodeServer

Address Points dataset current as of 2011. Address point database built to support geocoding and spatial 911 CAD.

The most accurate and up-to-date database for point addressing, with over 270 million precise point addresses in 70 countries.

Geocoding available in 196 countries, with high-precision mapping of display or navigable positions. Input a structured or free-form address to get results ranked by relevance or proximity.

Reverse Geocoding: Get a physical address from a set of geocoordinates. Use heading information to understand direction of movement, and get addresses, landmarks or area information around a position.

Search data: Search a rich database of ~120M POIs/places, that is updated daily, and interact with Places rich attributes covering information from name and category, to price range, contact and URLs.

Autosuggest: Get better suggestions with fewer strokes for places, addresses, chain queries or category queries, as well as provide search text matches with or without spatial filters.

This geocoding service provides the ability to perform tabular geocoding, reverse geocoding, and identifying results for locations that contain sub-addresses. This service and the supporting data are provided by the AddressNC program.A geocoding locator file is also available for users of ArcGIS Pro or ArcGIS Desktop in an offline/disconnected environment.

Please refer to the README file.

The datasets presented here enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes and a geocoded population (at the property unit level) for this area for the time period 1813-1914. The population is a subset of the Scanian Economic Demographic Database (SEDD). The geographic information includes the following feature types: property units, wetlands, buildings, roads and railroads. The property units and wetlands are stored in object-lifeline time representations (information about creation, changes and ends of objects are recorded in time), whereas the other feature types are stored as snapshots in time. Thus, the datasets present one of the first opportunities to study historical spatio-temporal patterns at the micro-level.

The file geoc_inv.txt contains identifiers for patent first filings (corresponding to appln_id in PATSTAT), latitude, longitude, city, region, and country of the inventor. Missing coordinates have been imputed from equivalents and other second filings or from information on the location of applicants. The file also contains a variable indicating the source of information ('source'): 1: information comes from the first filing itself 2: information comes from direct equivalent 3: information comes from other subsequent filings 4: information comes from the applicant’s location in first filings 5: information comes from the applicant’s location in the equivalent 6: information comes from the applicant’s location in other subsequent filings; the column 'coord_source' indicates the source of coordinates (whether they come from geolocalisation services, from geonames, or from PatentsView). It is possible to select certain types of first filings based on column 'type'. For example, Paris Convention priority filings can be retrieved by specifying type=priority. The file geoc_app.txt contains location information of applicants. Sources of information (first filings, equivalents, etc.) are thus browsed in reverse order. A detailed data description can be found in de Rassenfosse, Kozak, Seliger 2019: Geocoding of worldwide patent data, published in 'Scientific Data' and available at https://doi.org/10.1038/s41597-019-0264-6. Please note the following: The files geoc_inv_person.txt and geoc_app_person.txt contain person IDs for inventors and applicants, respectively, whenever the location information comes from PATSTAT. If not, the person_id is = 0. These files are not described in the paper. They have been made accessible to improve interoperability with PATSTAT data. Some files had to be zipped in order to upload them to Harvard Dataverse.

List of crashes involving motor vehicles, bicycles and/or pedestrians reported in the City of Cambridge from January 2010 through June 2016. Please refer to the dataset "Police Department Crash Data - Updated" for more recent and comprehensive crash data. Please Note: addresses are approximate. Rows for years 2010-2013 were geocoded as part of the MIT Public Safety Data Challenge. Any Latitude/Longitude with a value of 0 indicates that the location was not found though their geocoding efforts. Please see attachment for more details.

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 GeoPinpoint Suite software attaches geographic coordinates to records in a client database by means of matching certain database fields against a DMTI proprietary geo-reference database. The geo- reference database is comprised of digital street geometry, street address ranges, postal coordinates, point of interest and other reference databases to ensure that data is “geocoded” as accurately as possible. When data is “geocoded”, co-ordinates can be transferred into a Geographic Information Systems (GIS) such as MapInfo, ArcInfo, ArcView and other software systems that support the importation of geographic co-ordinate locations. GeoPinpointTM Suite positions your data using a powerful and innovative geo-location process called geocoding. GeoPinpoint Suite attaches X and Y coordinates to your facility, customer or prospect address data for map visualization, analysis or location based applications. The GeoPinpoint Suite takes advantage of a new modular design that allows the software to encompass future module enhancements without jeopardizing its performance or usability. Based on the nationwide precision and the robust street address content of CanMap® Streetfiles, GeoPinpoint Suite has been engineered to geocode your data with a high degree of accuracy.

Abstract: The Database on Ideology, Money in Politics, and Elections (DIME) is intended as a general resource for the study of campaign finance and ideology in American politics. The database was developed as part of the project on Ideology in the Political Marketplace, which is an on-going effort to perform a comprehensive ideological mapping of political elites, interest groups, and donors using the common-space CFscore scaling methodology (Bonica 2014). Constructing the database required a large-scale effort to compile, clean, and process data on contribution records, candidate characteristics, and election outcomes from various sources. The resulting database contains over 130 million political contributions made by individuals and organizations to local, state, and federal elections spanning a period from 1979 to 2014. A corresponding database of candidates and committees provides additional information on state and federal elections. The DIME+ data repository on congressional activity extends DIME to cover detailed data on legislative voting, lawmaking, and political rhetoric. (See http://dx.doi.org/10.7910/DVN/BO7WOW for details.) The DIME data is available for download as a standalone SQLite database. The SQLite database is stored on disk and can be accessed using a SQLite client or queried directly from R using the RSQLite package. SQLite is particularly well-suited for tasks that require searching through the database for specific individuals or contribution records. (Click here to download.) Overview: The database is intended to make data on campaign finance and elections (1) more centralized and accessible, (2) easier to work with, and (3) more versatile in terms of the types of questions that can be addressed. A list of the main value-added features of the database is below: Data processing: Names, addresses, and occupation and employer titles have been cleaned and standardized. Unique identifiers: Entity resolution techniques were used to assign unique identifiers for all individual and institutional donors included in the database. The contributor IDs make it possible to track giving by individuals across election cycles and levels of government. Geocoding: Each record has been geocoded and placed into congressional districts. The geocoding scheme relies on the contributor IDs to assign a complete set of consistent geo-coordinates to donors that report their full address in some records but not in others. This is accomplished by combining information on self-reported address across records. The geocoding scheme further takes into account donors with multiple addresses. Geocoding was performed using the Data Science Toolkit maintained by Pete Warden and hosted at http://www.datasciencetoolkit.org/. Shape files for congressional districts are from Census.gov (http://www.census.gov/rdo/data). Ideological measures: The common-space CFscores allow for direct distance comparisons of the ideal points of a wide range of political actors from state and federal politics spanning a 35 year period. In total, the database includes ideal point estimates for 70,871 candidates and 12,271 political committees as recipients and 14.7 million individuals and 1.7 million organizations as donors. Corresponding data on candidates, committees, and elections: The recipient database includes information on voting records, fundraising statistics, election outcomes, gender, and other candidate characteristics. All candidates are assigned unique identifiers that make it possible to track candidates if they campaign for different offices. The recipient IDs can also be used to match against the database of contribution records. The database also includes entries for PACs, super PACs, party committees, leadership PACs, 527s, state ballot campaigns, and other committees that engage in fundraising activities. Identifying sets of important political actors: Contribution records have been matched onto other publicly available databases of important political actors. Examples include: Fortune 500 directors and CEOs: (Data) (Paper) Federal court judges: (Data) (Paper} State supreme court justices: (Data) (Paper} Executives appointees to federal agencies: (Data) (Paper) Medical professionals: (Data) (Paper)