This dataset contains measures of socioeconomic and demographic characteristics by US ZIP code tabulation area (ZCTA) for the years 2008-2017. Example measures include population density; population distribution by race, ethnicity, age, and income; and proportion of population living below the poverty level, receiving public assistance, and female-headed families. The dataset also contains a set of index variables to represent neighborhood disadvantage and affluence.A curated version of this data is available through ICPSR at http://dx.doi.org/10.3886/ICPSR38528.v1.

Abstract

ADI: An index of socioeconomic status for communities. Dataset ingested directly from BigQuery.

Documentation

The Area Deprivation Index (ADI) can show where areas of deprivation and affluence exist within a community. The ADI is calculated with 17 indicators from the American Community Survey (ACS) having been well-studied in the peer-reviewed literature since 2003, and used for 20 years by the Health Resources and Services Administration (HRSA). High levels of deprivation have been linked to health outcomes such as 30-day hospital readmission rates, cardiovascular disease deaths, cervical cancer incidence, cancer deaths, and all-cause mortality. The 17 indicators from the ADI encompass income, education, employment, and housing conditions at the Census Block Group level.

The ADI is available on BigQuery for release years 2018-2020 and is reported as a percentile that is 0-100% with 50% indicating a "middle of the nation" percentile. Data is provided at the county, ZIP, and Census Block Group levels. Neighborhood and racial disparities occur when some neighborhoods have high ADI scores and others have low scores. A low ADI score indicates affluence or prosperity. A high ADI score is indicative of high levels of deprivation. Raw ADI scores and additional statistics and dataviz can be seen in this ADI story with a BroadStreet free account.

Dataset source: https://help.broadstreet.io/article/adi/

NYC Neighborhoods polygons and correlated data with their respective Postal Codes, Assembly Districts, Community Districts, Congressional Districts, Council Districts and State Senate Districts created by Ontodia. There are hundreds of neighborhoods in New York City's five boroughs, each with unique characteristics and histories. Many historical neighborhood names are derived from the names of the previously independent villages, towns, and cities that were incorporated into into the City of New York in the consolidation of 1898. Other neighborhood names have been introduced by real estate developers and urban planners, sometimes contentiously. Boundaries of neighborhoods are notoriously fuzzy, although many boundaries are widely agreed upon. Complicating the definition of neighborhood further, boundaries may overlap, some neighborhoods may function as a micro-neighborhood within another neighborhood, or a larger district which can be made up of multiple neighborhoods. Names and boundaries of neighborhoods shift over time; they are determined by the collective conscious of the people who live, work, and play in these places. There is never an official version of neighborhoods, but the concept is deeply meaningful to many people. In many cases a New Yorker is just as proud to claim identity with a particular neighborhood, and visitors plan their trips around visits to specific neighborhoods. To display data about neighborhoods on NYCpedia we created our own neighborhood boundaries, 264 in all. In order to display a continuous map with no overlap some boundaries have been stretched or shrunk, and neighborhoods have been omitted in this version. We intend to expand our work developing neighborhood polygon files (all released with open source license) and also to collect and organize as many meaningful alternative versions of neighborhood boundaries as possible. If you are a map geek or software developer who builds apps about New York City you can find the shapefile and geoJSON of the NYCpedia neighborhoods on Data Wrangler. Drop us a line if you see any errors, or if you have suggestions for how to improve our conception of NYC geography.

IntroductionThe goal of these studies was to investigate the reliability and validity of virtual systematic social observation (virtual SSO) using Google Street View in a Swedish neighborhood context.MethodsThis was accomplished in two studies. Study 1 focused on interrater reliability and construct validity, comparing ratings conducted in-person to those done using Google Street View, across 24 study sites within four postal code areas. Study 2 focused on criterion validity of virtual SSO in terms of neighborhoods with low versus high income levels, including 133 study sites within 22 postal code areas in a large Swedish city. In both studies, assessment of the neighborhood context was conducted at each study site, using a protocol adapted to a Swedish context.ResultsScales for Physical Decay, Neighborhood Dangerousness, and Physical Disorder were found to be reliable, with adequate interrater reliability, high consistency across methods, and high internal consistency. In Study 2, significantly higher levels of observed Physical Decay, Neighborhood Dangerousness, and signs of garbage or litter were observed in postal codes areas (site data was aggregated to postal code level) with lower as compared to higher income levels.DiscussionWe concluded that the scales within the virtual SSO with Google Street View protocol that were developed in this series of studies represents a reliable and valid measure of several key neighborhood contextual features. Implications for understanding the complex person-context interactions central to many theories of positive development among youth were discussed in relation to the study findings.

Please note: this data is live (updated nightly) to reflect the latest changes in the City's systems of record.Overview of the Data:This dataset is a polygon feature layer with the boundaries of all tax parcels owned by the City of Rochester. This includes all public parks, and municipal buildings, as well as vacant land and structures currently owned by the City. The data includes fields with features about each property including property type, date of sale, land value, dimensions, and more.About City Owned Properties:The City's real estate inventory is managed by the Division of Real Estate in the Department of Neighborhood and Business Development. Properties like municipal buildings and parks are expected to be in long term ownership of the City. Properties such as vacant land and vacant structures are ones the City is actively seeking to reposition for redevelopment to increase the City's tax base and economic activity. The City acquires many of these properties through the tax foreclosure auction process when no private entity bids the minimum bid. Some of these properties stay in the City's ownership for years, while others are quickly sold to development partners. For more information please visit the City's webpage for the Division of Real Estate: https://www.cityofrochester.gov/realestate/Data Dictionary: SBL: The twenty-digit unique identifier assigned to a tax parcel. PRINTKEY: A unique identifier for a tax parcel, typically in the format of “Tax map section – Block – Lot". Street Number: The street number where the tax parcel is located. Street Name: The street name where the tax parcel is located. NAME: The street number and street name for the tax parcel. City: The city where the tax parcel is located. Property Class Code: The standardized code to identify the type and/or use of the tax parcel. For a full list of codes, view the NYS Real Property System (RPS) property classification codes guide. Property Class: The name of the property class associated with the property class code. Property Type: The type of property associated with the property class code. There are nine different types of property according to RPS: 100: Agricultural 200: Residential 300: Vacant Land 400: Commercial 500: Recreation & Entertainment 600: Community Services 700: Industrial 800: Public Services 900: Wild, forested, conservation lands and public parks First Owner Name: The name of the property owner of the vacant tax parcel. If there are multiple owners, then the first one is displayed. Postal Address: The USPS postal address for the vacant landowner. Postal City: The USPS postal city, state, and zip code for the vacant landowner. Lot Frontage: The length (in feet) of how wide the lot is across the street. Lot Depth: The length (in feet) of how far the lot goes back from the street. Stated Area: The area of the vacant tax parcel. Current Land Value: The current value (in USD) of the tax parcel. Current Total Assessed Value: The current value (in USD) assigned by a tax assessor, which takes into consideration both the land value, buildings on the land, etc. Current Taxable Value: The amount (in USD) of the assessed value that can be taxed. Tentative Land Value: The current value (in USD) of the land on the tax parcel, subject to change based on appeals, reassessments, and public review. Tentative Total Assessed Value: The preliminary estimate (in USD) of the tax parcel’s assessed value, which includes tentative land value and tentative improvement value. Tentative Taxable Value: The preliminary estimate (in USD) of the tax parcel’s value used to calculate property taxes. Sale Date: The date (MM/DD/YYYY) of when the vacant tax parcel was sold. Sale Price: The price (in USD) of what the vacant tax parcel was sold for. Book: The record book that the property deed or sale is recorded in. Page: The page in the record book where the property deed or sale is recorded in. Deed Type: The type of deed associated with the vacant tax parcel sale. RESCOM: Notes whether the vacant tax parcel is zoned for residential or commercial use. R: Residential C: Commercial BISZONING: Notes the zoning district the vacant tax parcel is in. For more information on zoning, visit the City’s Zoning District map. OWNERSHIPCODE: Code to note type of ownership (if applicable). Number of Residential Units: Notes how many residential units are available on the tax parcel (if applicable). LOW_STREET_NUM: The street number of the vacant tax parcel. HIGH_STREET_NUM: The street number of the vacant tax parcel. GISEXTDATE: The date and time when the data was last updated. SALE_DATE_datefield: The recorded date of sale of the vacant tax parcel (if available). Source: This data comes from the department of Neighborhood and Business Development, Bureau of Real Estate.

Dataset SummaryPlease note: this data is live (updated nightly) to reflect the latest changes in the City's systems of record.About this data:The operational purpose of the vacant land dataset is to facilitate the tracking and mapping of vacant land for the purposes of promoting redevelopment of lots to increase the City's tax base and spur increased economic activity. These properties are both City owned and privately owned. The vast majority of vacant lots are the result of a demolition of a structure that once stood on the property. Vacant lots are noted in the official tax parcel assessment records with a class code beginning with 3, which denotes the category vacant land.Related Resources:For a searchable interactive mapping application, please visit the City of Rochester's Property Information explorer tool. For further information about the city's property tax assessments, please contact the City of Rochester Assessment Bureau. To access the City's zoning code, please click here.Data Dictionary: SBL: The twenty-digit unique identifier assigned to a tax parcel. PRINTKEY: A unique identifier for a tax parcel, typically in the format of “Tax map section – Block – Lot". Street Number: The street number where the tax parcel is located. Street Name: The street name where the tax parcel is located. NAME: The street number and street name for the tax parcel. City: The city where the tax parcel is located. Property Class Code: The standardized code to identify the type and/or use of the tax parcel. For a full list of codes, view the NYS Real Property System (RPS) property classification codes guide. Property Class: The name of the property class associated with the property class code. Property Type: The type of property associated with the property class code. There are nine different types of property according to RPS: 100: Agricultural 200: Residential 300: Vacant Land 400: Commercial 500: Recreation & Entertainment 600: Community Services 700: Industrial 800: Public Services 900: Wild, forested, conservation lands and public parks First Owner Name: The name of the property owner of the vacant tax parcel. If there are multiple owners, then the first one is displayed. Postal Address: The USPS postal address for the vacant landowner. Postal City: The USPS postal city, state, and zip code for the vacant landowner. Lot Frontage: The length (in feet) of how wide the lot is across the street. Lot Depth: The length (in feet) of how far the lot goes back from the street. Stated Area: The area of the vacant tax parcel. Current Land Value: The current value (in USD) of the tax parcel. Current Total Assessed Value: The current value (in USD) assigned by a tax assessor, which takes into consideration both the land value, buildings on the land, etc. Current Taxable Value: The amount (in USD) of the assessed value that can be taxed. Tentative Land Value: The current value (in USD) of the land on the tax parcel, subject to change based on appeals, reassessments, and public review. Tentative Total Assessed Value: The preliminary estimate (in USD) of the tax parcel’s assessed value, which includes tentative land value and tentative improvement value. Tentative Taxable Value: The preliminary estimate (in USD) of the tax parcel’s value used to calculate property taxes. Sale Date: The date (MM/DD/YYYY) of when the vacant tax parcel was sold. Sale Price: The price (in USD) of what the vacant tax parcel was sold for. Book: The record book that the property deed or sale is recorded in. Page: The page in the record book where the property deed or sale is recorded in. Deed Type: The type of deed associated with the vacant tax parcel sale. RESCOM: Notes whether the vacant tax parcel is zoned for residential or commercial use. R: Residential C: Commercial BISZONING: Notes the zoning district the vacant tax parcel is in. For more information on zoning, visit the City’s Zoning District map. OWNERSHIPCODE: Code to note type of ownership (if applicable). Number of Residential Units: Notes how many residential units are available on the tax parcel (if applicable). LOW_STREET_NUM: The street number of the vacant tax parcel. HIGH_STREET_NUM: The street number of the vacant tax parcel. GISEXTDATE: The date and time when the data was last updated. SALE_DATE_datefield: The recorded date of sale of the vacant tax parcel (if available). Source: This data comes from the department of Neighborhood and Business Development, Bureau of Business and Zoning.

The Canadian Active Living Environments (Can-ALE) database is a geographic-based set of measures that represents the active living friendliness of Canadian communities. The primary envisioned use for Can-ALE is research and analysis of the relationship between the way communities are built and the physical activity levels of Canadians. Each of the measures was selected from fourteen potential measures identified by a literature review. Several considerations were weighed in deriving the Canada-wide set of measures, including: (1) the suitability of each measure across different Canadian regions and built areas (e.g., urban, suburban, rural areas); (2) the incorporation of high-quality, open and free-to-use data sources; and (3) the strength of the association between the derived measures with walking rates and active transportation (i.e., walking, cycling, and public transit use). Public transit use is included in the definition of active transportation, as public transit is shown to generate physical activity via walking to and from transit stops.The Can-ALE data were developed by Dr. Nancy Ross, Thomas Herrmann and William Gleckner, with funding from the Public Health Agency of Canada. Can-ALE measures have been developed for 2006 and 2016 census dissemination areas. Users are discouraged from performing longitudinal analyses using data from both the 2006 and 2016 datasets, as the derivation methodologies and census geographies changed between the reference years. ArcGIS was used by CANUE staff to associate the single link DMTI Spatial postal codes to the Statistics Canada dissemination areas boundary files, and then join the Access to Employment data to the postal codes, using dissemination area unique identifiers. There may be many postal codes within a single dissemination area - these will have the same index values and may not be suitable for summation, etc. Please refer to the Supporting Documentation.

Residential Complaint Housing and Community Environment Inspection Reports posted to this web site include owner and tenant occupied dwellings with or without health code violations. The reports are based on visual inspection by Allegheny County Health Department (ACHD) inspectors. The primary basis for the inspections are the rules and regulations contained in “Article VI, Houses and Community Environment”. The entire health and housing code can be found at: http://www.achd.net/housing/pubs/pdf/hrules.pdf.

All ownership data listed on the inspection reports is collected from multiple sources, and is subject to change at any time. Changes in ownership may not be reflected on the posted reports. The following terms, definitions, and descriptions will be useful as you review the ACHD inspection reports.

Property Locations: A property location is typically a street address for a parcel of land which may or may not include a structure. Each location is associated with a city, borough, or township, state, and ZIP code, with geographic divisions by 2010 census tract.

Service Requests, Types of Service Requests, and Inspection Reports: A service request is a recorded instance, created when a complaint is made about a specific property. Each case has a unique service request number and cites a specific property location in violation.

Inspection Report and Violation Details: Each inspection report cites the sections of Article VI for which a property is found to be in violation. These citations are known as Violations. The nature of the violation is described in the inspection report. Each inspection report lists the property address or location, the date of inspection, a service request number, service request type, and a narrative description of the violation with a suggested remedy. It is possible that a property address may have more than one service request, particularly when multiple apartments at the same location or address have been inspected.

Note: All ACHD inspection reports and data posted on this web site are subject to errors and/or omissions. The cited violations are valid only as of the date of the inspection report. Inspection reports are uploaded monthly during the first week of the month and the upload includes new inspections up to the end of the preceding month.

Data is in three relational resources with the common field of Inspection ID.

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

A dataset listing the richest zip codes in New Jersey per the most current US Census data, including information on rank and average income.

Report Volume Data The report counts in this data set are broken down by activity sector, report type, the year and month of receipt, and reporting entity location. The reporting entity location is represented by the forward sortation area (FSA) component of the Canadian postal code (i.e. the first three characters of the Canadian postal code, e.g. “K1P”) that designates the postal district where the reporting entity is located. The Financial Transactions and Reports Analysis Centre of Canada (FINTRAC) is engaged in a multi-year initiative to implement important changes to its reporting forms. Part of this modernization now allows reporting entities to submit reports containing transactions from multiple locations, increasing efficiency and reducing burden. This will change how FINTRAC publishes statistics for reports that have been modernized. FINTRAC implemented the new Large Cash Transaction Report in October 2023. As such, reporting volume statistics for the Large Cash Transaction Report will be published at a national level for quarters 3 and 4 of 2023-2024 (from October to December, and January to March, respectively). ##Protecting the Identity of Reporting Entities By law, FINTRAC must protect the identity of the persons and entities that are required to submit financial transaction reports to the Centre under the Proceeds of Crime (Money Laundering) and Terrorist Financing Act. In keeping with this responsibility to protect information, FINTRAC cannot provide more specific geographic data than is contained in this data set. Whenever possible, the data set includes the full FSA to identify the location of reporting entities submitting reports to FINTRAC. However, in any case where a certain location contains fewer than five reporting entities, or fewer than five reports submitted, only partial characters of the FSA are shown. This means that certain FSAs may contain only one or two characters (e.g., K or K1) instead of the standard three characters (e.g., K1P). In rare cases, it was not possible to provide a reporting entity location or report count without risking revealing the identity of reporting entities in a given activity sector or identifying a specific report, and so the data is provided at a national level only. All FSA levels are hierarchically inclusive. This means, for example, that the total number of report counts for K1 includes all reports submitted within all FSAs that start with K1 (i.e. K1A, K1B, K1C), including those that may not be visible because they include fewer than five reporting entities in a given activity sector. E&OE

The CLB is available to children born on or after January 1, 2004, who are from low-income families or getting benefits under the Children’s Special Allowance Act. The CLB provides an initial payment of $500, and $100 for each year of eligibility up to age 15 (to a maximum of $2,000) and is retroactive. This means CLB payments can be requested for years the beneficiary was eligible, even for years before they were named in an RESP. Personal contributions are not required to receive the CLB. The table consists of quarterly data beginning with the period ending on December 31, 2006. The first column presents the number of children who have ever received the CLB, the second column presents the number of eligible children in the given Forward Sortation Area (sourced from the Canada Revenue Agency), and the third column presents the participation rate or the proportion of children receiving the CLB in relation to the eligible population. All population counts of 30 or below are censored due to privacy issues. ********************************************************* A methodological note on the cumulative CLB file - as of March 14, 2024 The cumulative CLB file is an update of the CLB data from consecutive editions of the Quarterly National CLB report by Forward Sortation Area (FSA). The current file is updated using CLB data from the last four quarters (Q1 2024 through to Q4 2024) that can be found in the Q4 2023 National CLB report. The Q4 2024 report also contains the updated FSA values from the December 2024 release of Statistics Canada’s Postal Code Conversion File. In this edition one new FSA value (V4Y) was created and no FSA values were removed. Updates of the historical and recent CLB data, in the cumulative file, are adjusted to reflect the new and old FSA values. All counts of 30 or under are not included and are represented with an asterisk in the Quarterly National CLB report by FSA. The Quarterly National CLB report by FSA presents CLB data by FSA and does not include the CLB aggregated data at either the national or province and territory levels. As of January 1, 2022, individuals eligible for the CLB who were born in 2004 or after but did not receive it yet can apply for the benefit when they turn 18. As a result, adult beneficiaries (i.e., those who receive it between the ages of 18 and 20) are included in beneficiary counts from 2022 onward. The primary source of data that is used to produce these numbers comes from the Canada Education Savings Program’s administrative data. Some updates (e.g., reversals, repayments, data errors, and reporting delays) may have been introduced in the Canada Education Savings Program’s administrative data that could affect the previous reporting periods. As a result, the values in the latest quarterly report supersede the previous quarterly reports. Please note that the Open Government Portal provides data that add to those already available in the Canada Education Savings Program Annual Statistical Review. The most recent version of the report, which includes data up to 2023, was published on October 7, 2024 and can be found here: https://www.canada.ca/en/employment-social-development/services/student-financial-aid/education-savings/reports/statistical-review.html