This dataset captures data describing the members of each household from the first interim assessment of Feed the Future’s population-based indicators for the ZOI in Cambodia. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity.
This dataset records the amount of food consumed by the household that came from gifts or other sources during the 7 days before the survey from the first interim assessment of Feed the Future's population-based indicaors for the ZOI in Cambodia. It has 1019 rows and 768 columns. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity. In the process of migrating data to the current DDL platform, datasets with a large number of variables required splitting into multiple spreadsheets. They should be reassembled by the user to understand the data fully.
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These data include the individual responses for the City of Tempe Annual Community Survey conducted by ETC Institute. This dataset has two layers and includes both the weighted data and unweighted data. Weighting data is a statistical method in which datasets are adjusted through calculations in order to more accurately represent the population being studied. The weighted data are used in the final published PDF report.These data help determine priorities for the community as part of the City's on-going strategic planning process. Averaged Community Survey results are used as indicators for several city performance measures. The summary data for each performance measure is provided as an open dataset for that measure (separate from this dataset). The performance measures with indicators from the survey include the following (as of 2023):1. Safe and Secure Communities1.04 Fire Services Satisfaction1.06 Crime Reporting1.07 Police Services Satisfaction1.09 Victim of Crime1.10 Worry About Being a Victim1.11 Feeling Safe in City Facilities1.23 Feeling of Safety in Parks2. Strong Community Connections2.02 Customer Service Satisfaction2.04 City Website Satisfaction2.05 Online Services Satisfaction Rate2.15 Feeling Invited to Participate in City Decisions2.21 Satisfaction with Availability of City Information3. Quality of Life3.16 City Recreation, Arts, and Cultural Centers3.17 Community Services Programs3.19 Value of Special Events3.23 Right of Way Landscape Maintenance3.36 Quality of City Services4. Sustainable Growth & DevelopmentNo Performance Measures in this category presently relate directly to the Community Survey5. Financial Stability & VitalityNo Performance Measures in this category presently relate directly to the Community SurveyMethods:The survey is mailed to a random sample of households in the City of Tempe. Follow up emails and texts are also sent to encourage participation. A link to the survey is provided with each communication. To prevent people who do not live in Tempe or who were not selected as part of the random sample from completing the survey, everyone who completed the survey was required to provide their address. These addresses were then matched to those used for the random representative sample. If the respondent’s address did not match, the response was not used. To better understand how services are being delivered across the city, individual results were mapped to determine overall distribution across the city. Additionally, demographic data were used to monitor the distribution of responses to ensure the responding population of each survey is representative of city population. Processing and Limitations:The location data in this dataset is generalized to the block level to protect privacy. This means that only the first two digits of an address are used to map the location. When they data are shared with the city only the latitude/longitude of the block level address points are provided. This results in points that overlap. In order to better visualize the data, overlapping points were randomly dispersed to remove overlap. The result of these two adjustments ensure that they are not related to a specific address, but are still close enough to allow insights about service delivery in different areas of the city. The weighted data are used by the ETC Institute, in the final published PDF report.The 2023 Annual Community Survey report is available on data.tempe.gov or by visiting https://www.tempe.gov/government/strategic-management-and-innovation/signature-surveys-research-and-dataThe individual survey questions as well as the definition of the response scale (for example, 1 means “very dissatisfied” and 5 means “very satisfied”) are provided in the data dictionary.Additional InformationSource: Community Attitude SurveyContact (author): Adam SamuelsContact E-Mail (author): Adam_Samuels@tempe.govContact (maintainer): Contact E-Mail (maintainer): Data Source Type: Excel tablePreparation Method: Data received from vendor after report is completedPublish Frequency: AnnualPublish Method: ManualData Dictionary
U.S. Government Workshttps://www.usa.gov/government-works
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The Pacific Community Results Report highlights the results achieved by SPC with our 26 Member countries and territories, and development partners. This dataset provides the data used in the Results Report provided in Excel and CSV formats.
This data has been visualised in the Results Explorer Dashboard: https://pacificdata.org/results-explorer
ECM Community Support Services tables for a Quarterly Implementation Report. Including the County and Plan Details for both ECM and Community Support.This Medi-Cal Enhanced Care Management (ECM) and Community Supports Calendar Year Quarterly Implementation Report provides a comprehensive overview of ECM and Community Supports implementation in the programs' first year. It includes data at the state, county, and plan levels on total members served, utilization, and provider networks. ECM is a statewide MCP benefit that provides person-centered, community-based care management to the highest need members. The Department of Health Care Services (DHCS) and its MCP partners began implementing ECM in phases by Populations of Focus (POFs), with the first three POFs launching statewide in CY 2022. Community Supports are services that address members’ health-related social needs and help them avoid higher, costlier levels of care. Although it is optional for MCPs to offer these services, every Medi-Cal MCP offered Community Supports in 2022, and at least two Community Supports services were offered and available in every county by the end of the year.
Selected variables from the most recent ACS Community Survey (Released 2023) aggregated by Community Area. Additional years will be added as they become available. The underlying algorithm to create the dataset calculates the % of a census tract that falls within the boundaries of a given community area. Given that census tracts and community area boundaries are not aligned, these figures should be considered an estimate. Total population in this dataset: 2,647,621 Total Chicago Population Per ACS 2023: 2,664,452 % Difference: -0.632% There are different approaches in common use for displaying Hispanic or Latino population counts. In this dataset, following the approach taken by the Census Bureau, a person who identifies as Hispanic or Latino will also be counted in the race category with which they identify. However, again following the Census Bureau data, there is also a column for White Not Hispanic or Latino. Code can be found here: https://github.com/Chicago/5-Year-ACS-Survey-Data Community Area Shapefile: https://data.cityofchicago.org/Facilities-Geographic-Boundaries/Boundaries-Community-Areas-current-/cauq-8yn6 Census Area Python Package Documentation: https://census-area.readthedocs.io/en/latest/index.html
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
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Net change in housing units arising from new buildings, demolitions, or alterations for NYC Community Districts since 2010. The NYC Department of City Planning's (DCP) Housing Database provide the 2010 census count of housing units, the net change in Class A housing units since the census, and the count of units pending completion for commonly used political and statistical boundaries. These tables are aggregated from the DCP Housing Database, which is derived from Department of Buildings (DOB)-approved housing construction and demolition jobs filed or completed in NYC since January 1, 2010. Net housing unit change is calculated as the sum of all three construction job types that add or remove residential units: new buildings, major alterations, and demolitions, and can be used to determine the change in legal housing units across time and space. All previously released versions of this data are available at BYTES of the BIG APPLE - Archive.
U.S. Government Workshttps://www.usa.gov/government-works
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DECD's listing of direct financial assistance to businesses from July 1, 2009 through June 30, 2024. New projects are usually added quarterly, but updates may be made on an ongoing basis.
Small Business Boost loan recipients can be found here: https://data.ct.gov/d/yk65-8y82
DO NOT DELETE OR MODIFY THIS ITEM. This item is managed by the ArcGIS Hub application. To make changes to this site, please visit https://hub.arcgis.com/admin/sites/new
On October 20, 2022, CDC began retrieving aggregate case and death data from jurisdictional and state partners weekly instead of daily. This dataset contains archived historical community transmission and related data elements by county. Although these data will continue to be publicly available, this dataset has not been updated since October 20, 2022. An archived dataset containing weekly historical community transmission data by county can also be found here: Weekly COVID-19 County Level of Community Transmission Historical Changes | Data | Centers for Disease Control and Prevention (cdc.gov).
Related data CDC has been providing the public with two versions of COVID-19 county-level community transmission level data: this historical dataset with the daily county-level transmission data from January 22, 2020, and a dataset with the daily values as originally posted on the COVID Data Tracker. Similar to this dataset, the original dataset with daily data as posted is archived on 10/20/2022. It will continue to be publicly available but will no longer be updated. A new dataset containing community transmission data by county as originally posted is now published weekly and can be found at: Weekly COVID-19 County Level of Community Transmission as Originally Posted | Data | Centers for Disease Control and Prevention (cdc.gov).
This public use dataset has 7 data elements reflecting historical data for community transmission levels for all available counties and jurisdictions. It contains historical data for the county level of community transmission and includes updated data submitted by states and jurisdictions. Each day, the dataset was updated to include the most recent days’ data and incorporate any historical changes made by jurisdictions. This dataset includes data since January 22, 2020. Transmission level is set to low, moderate, substantial, or high using the calculation rules below.
Methods for calculating county level of community transmission indicator The County Level of Community Transmission indicator uses two metrics: (1) total new COVID-19 cases per 100,000 persons in the last 7 days and (2) percentage of positive SARS-CoV-2 diagnostic nucleic acid amplification tests (NAAT) in the last 7 days. For each of these metrics, CDC classifies transmission values as low, moderate, substantial, or high (below and here). If the values for each of these two metrics differ (e.g., one indicates moderate and the other low), then the higher of the two should be used for decision-making.
CDC core metrics of and thresholds for community transmission levels of SARS-CoV-2
Total New Case Rate Metric: "New cases per 100,000 persons in the past 7 days" is calculated by adding the number of new cases in the county (or other administrative level) in the last 7 days divided by the population in the county (or other administrative level) and multiplying by 100,000. "New cases per 100,000 persons in the past 7 days" is considered to have transmission level of Low (0-9.99); Moderate (10.00-49.99); Substantial (50.00-99.99); and High (greater than or equal to 100.00).
Test Percent Positivity Metric: "Percentage of positive NAAT in the past 7 days" is calculated by dividing the number of positive tests in the county (or other administrative level) during the last 7 days by the total number of tests resulted over the last 7 days. "Percentage of positive NAAT in the past 7 days" is considered to have transmission level of Low (less than 5.00); Moderate (5.00-7.99); Substa
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United States Kentucky: GR: OS: CM: Charges: Housing & Community Development data was reported at 34,413.000 USD th in 2015. This records an increase from the previous number of 32,053.000 USD th for 2014. United States Kentucky: GR: OS: CM: Charges: Housing & Community Development data is updated yearly, averaging 19,829.000 USD th from Jun 1977 (Median) to 2015, with 37 observations. The data reached an all-time high of 36,517.000 USD th in 2012 and a record low of 8,706.000 USD th in 1979. United States Kentucky: GR: OS: CM: Charges: Housing & Community Development data remains active status in CEIC and is reported by US Census Bureau. The data is categorized under Global Database’s USA – Table US.F026: Revenue & Expenditure: State and Local Government: Kentucky.
Abstract: Census tract-based race and ethnicity data aggregated to City of Seattle Community Reporting Areas (CRAs) from the 1990 and 2010 Brown University Longitudinal Database (LTDB), 2010 decennial census and the 2014-2018 5-year American Community Survey (ACS). Brown University researchers created the LTDB to allow for comparing census data over time (see https://s4.ad.brown.edu/projects/diversity/Researcher/Bridging.htm). The race and ethnicity categories in the 2010 LTDB have been modified from those in the 2010 census to more closely match the 1990 race categories. (Before 2000, census questionnaires allowed respondents to identify as one race only. The LTDB allocates mixed-race people in post-1990 census estimates to non-white categories.) Please remember that the ACS data carry margins of error, and for small racial/ethnic groups they can be significant. The numeric and percentage changes overtime are also included. There is also a polygon representation for the City of Seattle as a whole.Purpose: Census data of racial and ethnic categories from 1990 and 2010 Brown University LTDB, 2010 decennial and 2018 American Community Survey (ACS). Data is for the City of Seattle Community Reporting Areas as well as a polygon representation for the City of Seattle as a whole. Numeric and percentage changes over time are also included.
NREL has updated a database of publicly available resources related to community solar in the U.S., including journal articles, reports, fact sheets, slides, videos, datasets, webinars, and other formats. This effort aims to compile resources that would benefit all partners interested in investigating the market status, data analysis, regulation, stakeholder engagement, and the best practices of community solar development.
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This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.
The NYS Department of Environmental Conservation (DEC) collects and maintains several datasets on the locations, distribution and status of species of plants and animals. Information on distribution by county from the following three databases was extracted and compiled into this dataset. First, the New York Natural Heritage Program biodiversity database: Rare animals, rare plants, and significant natural communities. Significant natural communities are rare or high-quality wetlands, forests, grasslands, ponds, streams, and other types of habitats. Next, the 2nd NYS Breeding Bird Atlas Project database: Birds documented as breeding during the atlas project from 2000-2005. And last, DEC’s NYS Reptile and Amphibian Database: Reptiles and amphibians; most records are from the NYS Amphibian & Reptile Atlas Project (Herp Atlas) from 1990-1999.
This dataset shows the boundaries for community associations registered with the City of San Antonio.
Consumption of communal resources
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A series of short video clips illustrating how to use the Community and Education Data Portal (https://portal.ga.gov.au/persona/education). The Community and Education data portal is one of many data delivery portals available from Geoscience Australia, giving users access to a wealth of useful data and tools. It has been designed specifically for non-technical users, so that general community members, including educators, can access themed surface and subsurface datasets or images with …Show full descriptionA series of short video clips illustrating how to use the Community and Education Data Portal (https://portal.ga.gov.au/persona/education). The Community and Education data portal is one of many data delivery portals available from Geoscience Australia, giving users access to a wealth of useful data and tools. It has been designed specifically for non-technical users, so that general community members, including educators, can access themed surface and subsurface datasets or images with enhanced capabilities including 3D visualisation, and online analysis tools. The User Guide Video complements the help menu in the portal. The User guide is broken into a series of topics Introduction Toolbar Map layers Multiple Layers Background Layers and Sharing 3D Layers Tools Custom Layers The step by step guides were produced by James Cropper.
https://www.etalab.gouv.fr/licence-ouverte-open-licencehttps://www.etalab.gouv.fr/licence-ouverte-open-licence
Limites administratives des communes de la Métropole
This dataset captures data describing the members of each household from the first interim assessment of Feed the Future’s population-based indicators for the ZOI in Cambodia. The ZOI is the Pursat, Battambang, Kampong Thom, and Siem Reap Provinces. The sampling design called for a two-stage cluster sample. In the first stage, 84 villages were selected; in the second stage, households were selected within each sampled village. The sampling of villages was stratified by province, with the number of villages in each stratum proportional to the population in the stratum and with villages selected with probability proportional to size, based on the 2013 Commune Database. The data is split into survey modules. Modules A through C includes location information, informed consent, and the household roster. Module D includes household characteristics. Module E is the expenditures module broken up into 8 different parts. Modules F and G include the hunger scale data and WEIA index data. Data in modules H and I include mother and child dietary diversity.