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 District of Columbia government uses the Master Address Repository (MAR) to implement intelligent search functionality for finding and verifying addresses, place names, blocks and intersections.

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

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.

This dataset contains address points from the Countywide Address Management System, a collaborative program between the County’s Registrar/Recorder, Chief Information Officer, Public Works Department, Department of Regional Planning, and many local cities to manage addresses and street centerlines for the purposes of geocoding and cartography. More information about this layer can be found on the https://cams-lacounty.hub.arcgis.com/ What this data is (and isn’t)This dataset contains the best available information, with close to 3 million primary and secondary addresses in the County of Los Angeles. It does NOT include information about every unit, suite, building, and sub-address. With probably over 7 million addresses, we have a ways to go.DescriptionThis dataset includes over 2.9 million individual points for addresses in the County. Data has been compiled from best available sources, including city databases, LA County Assessor parcels, and the County’s House Numbering maps. Please see the Source field for information.Street Name information has been split into multiple fields to support the County’s specifically designed geocoders – please see the entry on LA County Specific Locators and Matching rules for more information.Multi-address ParcelsSome of our data sources (LA City, LA County, for example) have mapped each individual address in their city. These may also show unit information for an address point. A property with multiple addresses will show a point for each address. For some cities where this has not happened, the data source is the Assessor, where the primary address of the property may be the only address shown. We invite cities and sources with more detailed information to join the CAMS consortium to continue to improve the data.Legal vs. Postal CitiesMany users confuse the name the Post Office delivers main 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 zipcodes. To support useability and geocoding, we have attached the first 3 postal cities to each address, based upon its zipcocode.

This service provides a comprehensive address file containing a point for every addressable site within New Hanover County. Address points include all residential, commercial, and utility addresses. The RTYPE field is coded with the type of address. Other fields include: house number, street name, type, and direction, city, state, zip code, country, STYPE (Structure Type), unit, UTYPE (Unit Type), edit date, and source. GISOBJID and GlobalID are used for internal unique identifiers.

This dataset contains street centerlines for vehicular and foot traffic in Allegheny County. Street Centerlines are classified as Primary Road, Secondary Road, Unpaved Road, Limited Access Road, Connecting Road, Jeep Trail, Walkway, Stairway, Alleyway and Unknown. A Primary Road is a street paved with either concrete or asphalt that has two (2) or more lanes in each direction. A Secondary Road is a residential type hard surface road, or any hard surface road with only one (1) lane in each direction. An Unpaved Road is any road covered with packed dirt or gravel. A Limited Access Road is one that can only be accessed from a Connecting Road such as an Interstate Highway. A Connecting Road is a ramp connecting a Limited Access Road to a surface street. A Walkway is a paved or unpaved foot track that connects two (2) roads together. Walkways within College Campuses will also be shown. Recreational pedestrian trails and walkways through parks and wooded areas are not considered transportation and will not be digitized during this update. Walkways will not have an Edge of Pavement feature. A Stairway is a paved or wooden structure that connects two (2) roads together. Recreational pedestrian trails and walkways through parks and wooded areas are not considered transportation and will not be digitized during this update. An Alleyway is a road, usually narrower than a Secondary Road that runs between, but parallel to, two (2) Secondary Roads. Generally, Outbuildings will be adjacent to Alleyways. A Jeep Trail is a vehicular trail used for recreation. A Jeep Trail will not have an associated edge of pavement feature. A road coded as Unknown is a road, which in the judgment of the photogrammetrist, does not fall into any of the categories listed. Centerlines will be visually placed between the edges of pavement. One (1) centerline will be placed between each edge of pavement. Roads with medial strips, such as Limited Access Roads, will have two (2) centerlines for those portions of the road where the medial strip is present. For roads that terminate with a cul-de-sac, the centerline shall continue through the center of the cul-de-sac and stop at the edge of pavement. All attribute data will remain for all Street Centerlines that are not updated. For Street Centerlines that are new, the only attribute field that will be populated is the FeatureCode and UPDATE_YEAR. If a Street Centerline is graphically modified, the existing attribute data will remain and the UPDATE_YEAR will be set to 2004. The attribute values for 2004 Street Centerlines should be considered suspicious until verified. The ArcInfo Street Centerline coverage that is being updated has 800 segments of Paper Streets, 66 segments of Vacated Streets and 78 segments of Steps. Street Centerlines that are coded as Paper Streets in the OWNER field will remain unchanged in the updated dataset unless the area has been developed. In the event the area has been developed, the Street Centerlines will be modified to reflect the true condition of the visible roads. Street Centerlines that are coded as Vacated in the OWNER field will also remain unchanged in the updated dataset. In the event the area coinciding with the Vacated Streets has been developed, the Vacated Street Centerlines will be removed in order to reflect the true condition of the area. Street Centerlines that are coded as Steps in the OWNER field will be updated to reflect the current condition of the area. The Street Centerlines dataset consists of an external table that links to the supplied coverages and the Geodatabase created for this project using the "-ID" (UserID) field. In order to maintain the link to the external table and not loose valuable data the decision was made to keep all database information currently in the Street Centerline dataset. When a Street Centerline is modified during the update process, the field "UPDATE_YEAR" is set to 2004. All other database attributes will remain unchanged from the original values. All Street Centerline database data with an "UPDATE_YEAR" of 2004 should be verified before used. In some occasions the Street Centerline was divided into two (2) sections to allow for a new road intersection. Both sections of the resulting Street Centerline will have the same database attributes including Address Range. All new Street Centerlines will have zero (0) for "SystemID" and "UserID". This dataset was previously harvested from Allegheny County’s GIS data portal. The new authoritative source for this data is now the PASDA page (https://www.pasda.psu.edu/uci/DataSummary.aspx?dataset=1224), which includes links to historical versions of the shapefile representations of this data.

The purpose of the medication-assisted treatment (MAT) facility maps is to identify areas on a state-by-state basis that may be potentially underserved by existing treatment facilities. The maps are created with a methodology that seeks to include the highest potential need areas from individual counties so that county-level stakeholders are also informed. The maps are meant to be used as a tool for policy makers to determine potentially underserved areas—not as a definitive representation of these areas.

The NSW Address Location Service web service allows the user to enter an address and pinpoint the location of that address.\r \r The NSW Address Location Service is derived from the Geocoded Urban and Rural Address System (GURAS) database. \r \r This web service allows users to easily integrate NSW addressing information into spatial platforms and applications.\r \r The addressing web service provides users with a unique and unambiguous identification of an address site and its location within NSW. The ability to identify the location of an address supports a wide range of business functions including: the delivery of products and services, public safety, communication and socio-economic and demographic analysis.\r \r The GURAS database is the authoritative property addressing system for NSW.\r \r - - - \r NOTE: Please contact the Customer HUB https://customerhub.spatial.nsw.gov.au/ for advice on datasets access.\r - - -\r \r

The Addresses data is based on the public data of the SE Center of Registers, which were published in November of 2024. In order to get the actual Addresses data of the required territory, you need to contact the SE "Centre of Registers" which is the administrator of the Address Register. info@registrucentras.lt. The objects are shown at the scales between 1:1 000 and 1:50 000.

Count or zero-inflated count data is often collected in Ecological Momentary Assessment (EMA) studies where understanding the mechanisms of the change process serves as the primary research goal. Traditional methods often fail to capture the complexities inherent in EMA data, leading to discrepancies between empirical findings and theoretical expectations. To address these limitations, this study presents two novel approaches. The first integrates autoregressive effects individually, and the second utilizes a model framework to pinpoint autoregressive effects among groups. These approaches are extended for both count and zero-inflated count data. Through simulation studies and empirical applications, the proposed models show enhanced accuracy and interpretability at both individual and group levels. Furthermore, models tailored for zero-inflated data, referred to as ZIP-CAR, can distinguish zero patterns at both individual and group levels. The dissertation concludes with discussions on the practical implications, limitations, and future directions of the proposed methods. This work is expected to improve method development for EMA studies, ultimately enhancing the understanding of behavioral change processes in zero-inflated count data.

Social scientists often use ranking questions to study people's opinions and preferences. However, little is understood about the general nature of measurement errors in such questions, let alone their statistical consequences and what researchers can do about them. We introduce a statistical framework to improve ranking data analysis by addressing measurement errors in ranking questions. First, we characterize measurement errors from random responses---arbitrary and meaningless responses based on a wide range of random patterns. We then quantify bias due to random responses, show that the bias may change our conclusion in any direction, and clarify why item order randomization alone does not solve the statistical issue. Next, we introduce our methodology based on two key design-based considerations: item order randomization and the addition of an "anchor" ranking question with known correct answers. They allow researchers to (1) learn about the direction of the bias and (2) estimate the proportion of random responses, enabling our bias-corrected estimators. We illustrate our methods by studying the relative importance of people's partisan identity compared to their racial, gender, and religious identities in American politics. We find that about 30% of respondents offered random responses and that these responses may affect our substantive conclusions.

This document is the data model/metadata for all Allegheny County Addressing datasets and tables.

TrevorJS/us-addresses-synthetic-v3-llm dataset hosted on Hugging Face and contributed by the HF Datasets community

🇺🇸 미국

Address Points dataset current as of 2007. Structure Addressing (based on parcel map and building structure data).

This dataset contains the address points of the Grand-Duchy of Luxembourg. The dataset is structured according to the INSPIRE Annex I Theme - Addresses. The data has been derived from the Cadastral database. For every parcel, where an address is known, the address point is located on the entrance of the main building(s). The syntax of the addresses is compliant with the "CACLR" - database (https://www.services-publics.lu/caclr/index.action) These addresses are used for the geolocalisation in the Geoportal (http://map.geoportal.lu) They have been transposed into the INSPIRE data model and coordinate system. Description copied from catalog.inspire.geoportail.lu.

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

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