Timeline / Data.gov — Health Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 3395 line(s) added, 4280 line(s) removed.
Evidence
| Source | Data.gov — Health Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=health&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-09-30T18:26:31+00:00 |
| Content type | application/json |
| Current object |
2108ce64c2c2ae61a75786cef4f0b8f6ce6c2261f3eb475e05e3a1425388b295
download raw
metadata
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| Previous object |
e476df22b3775e17f92ddf9c9d93defa2f8f30d415391de5725f722d09e40746
download raw
metadata
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What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-09-30T18:26:31+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 3395 line(s) added, 4280 line(s) removed.
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This dataset provides point location, and relevant information of CDBG activities that have taken place since 1996, and which HUD classifies using one of the following categories: Asset Acquisition - activity related to acquisition, including disposition, clearance and demolition, and clean-up of contaminated Sites/brownfields. Economic Development - activity related to economic development, including commercial or industrial rehab, commercial or industrial land acquisition, commercial or industrial construction, commercial or industrial infrastructure development, direct assistance to businesses, and micro-enterprise assistance. Housing - activity related to housing, including multifamily rehab, housing services, code enforcement, operation and repair of foreclosed property and public housing modernization. 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No warranty, expressed or implied is made with regard to the accuracy of the spatial accuracy, and no liability is assumed by the U.S. Government in general, the dataset creators or the U.S. Department of Housing and Urban Development specifically, as to the spatial or attribute accuracy of the data." + ], + "spatial": "{\"@type\": \"Location\", \"bbox\": {\"coordinates\": [[[-159.670537, 64.840035], [-64.788143, 64.840035], [-64.788143, 13.442948], [-159.670537, 13.442948], [-159.670537, 64.840035]]], \"type\": \"Polygon\"}, \"prefLabel\": \"United States and Minor Outlying Islands\"}", + "title": "Community Development Block Grant Activity" + }, + "description": "This dataset denotes the primary point locations of CDBG activities, and provides specific information relative to each award activity. The Community Development Block Grant (CDBG) is a federal block grant distributed (via formula) to states and local governments. Recipients use the grant funds to carry out housing, economic development, and public improvement efforts that serve low, and moderate-income communities. Such activities may fall within Asset Acquisition, Economic Development, Housing, Public Improvements, and Public Services. The Community Development Block Grant (CDBG) is a federal block grant distributed (via formula) to states and local governments. Recipients use the grant funds to carry out housing, economic development, and public improvement efforts that serve low, and moderate-income communities. This dataset provides point location, and relevant information of CDBG activities that have taken place since 1996, and which HUD classifies using one of the following categories: Asset Acquisition - activity related to acquisition, including disposition, clearance and demolition, and clean-up of contaminated Sites/brownfields. 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While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. To learn more about the CDBG Program visit: https://www.hud.gov/program_offices/comm_planning/communitydevelopment/programs, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. 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Funding for remediation and abatement is limited. To adequately target households eligible for home remediation and associated intervention efforts, local healthy homes and environmental health program administrators must identify neighborhoods that are the most “at risk” of residential lead exposure where deteriorated paint is the primary source. To address this need, the DPI uses household-level data to predict a household’s risk of deteriorated paint. The Deteriorated Paint Index (DPI) data predicts areas at-risk of containing several pre-1980 households with large areas of deteriorated paint, a significant and common predictor of lead dust. Funding for remediation and abatement is limited. To adequately target households eligible for home remediation and associated intervention efforts, local healthy homes and environmental health program administrators must identify neighborhoods that are the most “at risk” of residential lead exposure where deteriorated paint is the primary source. To address this need, the DPI uses household-level data to predict a household’s risk of deteriorated paint. Predicted risk scores were calculated using microdata from the 2011 American Housing Survey (AHS) and the 2009-2013 American Community Survey (ACS) to develop a predicted risk measure. This metric estimates the predicted percentage of occupied housing units with large areas of deteriorated paint for three geographic levels: state, county, and tract. The primary methodological goal of the analysis was to post-fit ACS households with beta parameters from an AHS model that predicted the presence of a large area of deteriorated paint. Prior research shows this methodology can be used for small area estimation. Analyses were conducted using SAS Version 9.1.4 (SAS Institute Inc., Cary, NC). Household-level ACS and AHS microdata were used. Analyses were conducted in a Census-approved partner institution Federal Statistical Research Data Center. Exposure to residential lead dust will continue to be a public health problem until housing with deteriorated lead paint is remediated. Public health practitioners interested in strategically allocating healthy homes funding should consult this dataset and overlay predicted rates of deteriorated paint with important and unique local data to develop comprehensive targeting strategies. 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Promise Zones are high poverty communities where the federal government partners with local leaders to increase economic activity, improve educational opportunities, leverage private investment, reduce violent crime, enhance public health and address other priorities identified by the community. Current Promise Zones were selected through three rounds of national competition, in which applicants demonstrated a consensus vision for their community and its residents, the capacity to carry it out, and a shared commitment to specific, measurable results. Promise Zones are high poverty communities where the federal government partners with local leaders to increase economic activity, improve educational opportunities, leverage private investment, reduce violent crime, enhance public health and address other priorities identified by the community. Current Promise Zones were selected through three rounds of national competition, in which applicants demonstrated a consensus vision for their community and its residents, the capacity to carry it out, and a shared commitment to specific, measurable results.\nThe Promise Zone designation partners the Federal government with local leaders who are addressing multiple community revitalization challenges in a collaborative way. The Promise Zone designation will last for a term of 10 years. 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The indicators, conveyed as a grid of 1-degree latitude by 1-degree longitude cells, are created from observational data (Berkeley Earth Lab gridded daily maximum and minimum temperature ) and consider the frequency, intensity, and duration of extreme heat and extreme cold weather events that occurred in the US between 1913 and 2012. The Temperature Severity Indicator data identifies areas subject to extreme heat and cold events in the contiguous United States in an effort to inform temperature-related housing and planning research. The indicators, conveyed as a grid of 1-degree latitude by 1-degree longitude cells, are created from observational data (Berkeley Earth Lab gridded daily maximum and minimum temperature ) and consider the frequency, intensity, and duration of extreme heat and extreme cold weather events that occurred in the US between 1913 and 2012. DEFINING EXTREME TEMPERATURE EVENTS\n\nFor the purposes of this data, a\ndaytime extreme heat event is defined as daily maximum temperature (tmax) that\nmeets or exceeds the 90th percentile daily tmax for June, July, and\nAugust (JJA) during the reference period 1961-1990 and lasting for at least 3\nconsecutive days. A lower bound is set to 90 degrees Fahrenheit (F) to define\nthe minimum temperature qualifying as a daytime heat event. Likewise, a night time extreme\nheat event is defined as daily minimum temperature (tmin) that meets or exceeds\nthe 90th percentile daily tmin for JJA during the reference period\n1961-1990 and lasting for at least 3 consecutive nights. A lower bound is set\nto 75 F to define the minimum temperature qualifying as a night time heat\nevent.\nA daytime extreme cold event is\ndefined as daily maximum temperature (tmax) that is at least 10 F less than the\nmedian daily climatological January tmax over the reference period 1961-1990\nand lasting for at least 3 consecutive days. An upper bound is set at 32 F to\ndefine the maximum temperature qualifying as a daytime cold event, and a lower\nbound is set to -10 F, where any 3 or more consecutives days colder than this\nlimit is considered a cold event. A night time extreme cold event\nis defined as daily minimum temperature (tmin) that is at least 10 F less than\nthe median daily climatological January tmin over the reference period\n1961-1990 and lasting for at least 3 consecutive days. An upper bound is set at\n32 F to define the maximum temperature qualifying as a night time cold event,\nand a lower bound is set to -10 F, where any 3 or more consecutives nights\ncolder than this limit is considered a cold event. CREATING EXTREME TEMPERATURE\nSEVERITY INDEXES\n\nThe average annual event\nfrequency (events/yr), average event intensity compared to a seasonally\nrepresentative temperature (F), and the average event duration (days) are\ncomputed using the Berkeley Earth temperature observations as well as the above\ndefinitions for extreme heat and cold events. Results of those calculations are classified according to a quartile distribution of all values relative to attribute, and each cell receives a score according to its quartile class: 0 points for a cell value less than the 25th percentile, 1 point if between the 25th and 50th percentile, 2 points if between the 50th and 75th percentile, 3 points if greater than the 75th percentile. The index value represents the aggregation of quartile points awarded for each attribute of a particular cell. SUGGESTED USE OF DATA\nFields ending with the suffix, “_INDX” provide spatially relevant severity indices for min/max cold snaps and heat waves. As described previously, the value for each index represents the summation of attributes scores determined by a quartile distribution of all values for each facet of analysis. Index scores for these fields range from 0 to 9 providing for a relatively smooth surface map illustrating spatial variability.\nIn contrast, fields ending with the suffix, “_IND” are binary attributes that indicate areas where the index values for both night-time (tmin) and day-time (tmax) is >= 5 relative to each event type. Given the boolean nature of data in these fields they are best used to quickly identify areas of extreme temperature to answer policy related questions, and not necessarily for illustration or spatial analysis. For questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov . 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No warranty, expressed or implied is made with regard to the accuracy of the spatial accuracy, and no liability is assumed by the U.S. Government in general, the dataset creators or the U.S. Department of Housing and Urban Development specifically, as to the spatial or attribute accuracy of the data." + ], + "spatial": "{\"@type\": \"Location\", \"bbox\": {\"coordinates\": [[[-179.147339, 71.390482], [179.778467, 71.390482], [179.778467, -14.548699], [-179.147339, -14.548699], [-179.147339, 71.390482]]], \"type\": \"Polygon\"}, \"prefLabel\": \"United States and Minor Outlying Islands\"}", + "title": "Temperature Severity Indicators" + }, + "description": "The Temperature Severity Indicator data distills observational information of prolonged temperature events in the contiguous United States to inform housing and community development policy, planning, and decision making. The indicators, conveyed as a grid of 1-degree latitude by 1-degree longitude cells, are created from observational data (Berkeley Earth Lab gridded daily maximum and minimum temperature ) and consider the frequency, intensity, and duration of extreme heat and extreme cold weather events that occurred in the US between 1913 and 2012. The Temperature Severity Indicator data identifies areas subject to extreme heat and cold events in the contiguous United States in an effort to inform temperature-related housing and planning research. The indicators, conveyed as a grid of 1-degree latitude by 1-degree longitude cells, are created from observational data (Berkeley Earth Lab gridded daily maximum and minimum temperature ) and consider the frequency, intensity, and duration of extreme heat and extreme cold weather events that occurred in the US between 1913 and 2012. DEFINING EXTREME TEMPERATURE EVENTS\n\nFor the purposes of this data, a\ndaytime extreme heat event is defined as daily maximum temperature (tmax) that\nmeets or exceeds the 90th percentile daily tmax for June, July, and\nAugust (JJA) during the reference period 1961-1990 and lasting for at least 3\nconsecutive days. A lower bound is set to 90 degrees Fahrenheit (F) to define\nthe minimum temperature qualifying as a daytime heat event. Likewise, a night time extreme\nheat event is defined as daily minimum temperature (tmin) that meets or exceeds\nthe 90th percentile daily tmin for JJA during the reference period\n1961-1990 and lasting for at least 3 consecutive nights. A lower bound is set\nto 75 F to define the minimum temperature qualifying as a night time heat\nevent.\nA daytime extreme cold event is\ndefined as daily maximum temperature (tmax) that is at least 10 F less than the\nmedian daily climatological January tmax over the reference period 1961-1990\nand lasting for at least 3 consecutive days. An upper bound is set at 32 F to\ndefine the maximum temperature qualifying as a daytime cold event, and a lower\nbound is set to -10 F, where any 3 or more consecutives days colder than this\nlimit is considered a cold event. A night time extreme cold event\nis defined as daily minimum temperature (tmin) that is at least 10 F less than\nthe median daily climatological January tmin over the reference period\n1961-1990 and lasting for at least 3 consecutive days. An upper bound is set at\n32 F to define the maximum temperature qualifying as a night time cold event,\nand a lower bound is set to -10 F, where any 3 or more consecutives nights\ncolder than this limit is considered a cold event. CREATING EXTREME TEMPERATURE\nSEVERITY INDEXES\n\nThe average annual event\nfrequency (events/yr), average event intensity compared to a seasonally\nrepresentative temperature (F), and the average event duration (days) are\ncomputed using the Berkeley Earth temperature observations as well as the above\ndefinitions for extreme heat and cold events. Results of those calculations are classified according to a quartile distribution of all values relative to attribute, and each cell receives a score according to its quartile class: 0 points for a cell value less than the 25th percentile, 1 point if between the 25th and 50th percentile, 2 points if between the 50th and 75th percentile, 3 points if greater than the 75th percentile. 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The Community Development Block Grant (CDBG) program requires that each CDBG funded activity must either principally benefit low- and moderate-income persons, aid in the prevention or elimination of slums or blight, or meet a community development need having a particular urgency because existing conditions pose a serious and immediate threat to the health or welfare of the community and other financial resources are not available to meet that need. With respect to activities that principally benefit low- and moderate-income persons, at least 51 percent of the activity's beneficiaries must be low and moderate income. For CDBG, a person is considered to be of low income only if he or she is a member of a household whose income would qualify as \"very low income\" under the Section 8 Housing Assistance Payments program. Generally, these Section 8 limits are based on 50% of area median. Similarly, CDBG moderate income relies on Section 8 \"lower income\" limits, which are generally tied to 80% of area median. These data are from the 2016-2020 American Community Survey (ACS). To learn more about the Low to Moderate Income Populations visit: https://www.hudexchange.info/programs/acs-low-mod-summary-data/ , for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov. 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This dataset denotes the primary locations, and relevant information of HOME program activities, and which HUD classifies using one of the following categories: Asset Acquisition - activity related to acquisition, including disposition, clearance and demolition, and clean-up of contaminated Sites/brownfields.Economic Development - activity related to economic development, including commercial or industrial rehab, commercial or industrial land acquisition, commercial or industrial construction, commercial or industrial infrastructure development, direct assistance to businesses, and micro-enterprise assistance.Housing - activity related to housing, including multifamily rehab, housing services, code enforcement, operation and repair of foreclosed property and public housing modernization.Public Improvements - activity related to public improvements, including senior centers, youth centers, parks, street improvements, water/sewer improvements, child care centers, fire stations, health centers, non-residential historic preservation, etc.Public Services - activity related to public services, including senior services, legal services, youth services, employment training, health services, homebuyer counseling, food banks, etc.Other - activity related to urban renewal completion, non-profit organization capacity building, and assistance to institutions of higher education.HOME Activity (point) - All HOME activities. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. Note that these data only include latitude and longitude coordinates and associated attributes for those addresses that can be geocoded to an interpolated point along a street segment, or to a ZIP+4 centroid location. While not all records are able to be geocoded and mapped, we are continuously working to improve the address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. To learn more about the CDBG program visit: https://www.hud.gov/hudprograms/home-program. 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The Community Development Block Grant (CDBG) is a federal block grant distributed (via formula) to states and local governments. Recipients use the grant funds to carry out housing, economic development, and public improvement efforts that serve low, and moderate-income communities. Such activities may fall within Asset Acquisition, Economic Development, Housing, Public Improvements, and Public Services. The Community Development Block Grant (CDBG) is a federal block grant distributed (via formula) to states and local governments. Recipients use the grant funds to carry out housing, economic development, and public improvement efforts that serve low, and moderate-income communities. This dataset provides CDBG activity data aggregated to 2010 US Census Tract. Relevant information of CDBG activities that have taken place since 1996, and which HUD classifies using one of the following categories:Asset Acquisition - activity related to acquisition, including disposition, clearance and demolition, and clean-up of contaminated Sites/brownfields.Economic Development - activity related to economic development, including commercial or industrial rehab, commercial or industrial land acquisition, commercial or industrial construction, commercial or industrial infrastructure development, direct assistance to businesses, and micro-enterprise assistance.Housing - activity related to housing, including multifamily rehab, housing services, code enforcement, operation and repair of foreclosed property and public housing modernization. Public Improvements - activity related to public improvements, including senior centers, youth centers, parks, street improvements, water/sewer improvements, child care centers, fire stations, health centers, non-residential historic preservation, etc.Public Services - activity related to public services, including senior services, legal services, youth services, employment training, health services, homebuyer counseling, food banks, etc. Other - activity related to urban renewal completion, non-profit organization capacity building, and assistance to institutions of higher education.Please note that this service only provides data for those areas in which CDBG program activity has occurred. Tracts where Total Amount = 0, or Total Amount is NULL have been omitted from this dataset. To learn more about the CDBG Program visit: https://www.hud.gov/program_offices/comm_planning/communitydevelopment/programs/. 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To learn more about the Section 242 Mortgage Insurance for Hospitals program, please visit the following website: https://portal.hud.gov/hudportal/HUD?src=/federal_housing_administration/healthcare_facilities/section_242", + "distribution_titles": [ + "Historical List of All FHA Hospital Loans", + "FHA Section 242 Commitments Issued Since Fiscal Year 2001" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/87679568-7320-403c-b227-deab676ee2b8", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/87679568-7320-403c-b227-deab676ee2b8/raw", + "has_download": true, + "has_spatial": false, + "identifier": "HUD112", + "keyword": [ + "Puerto Rico", + "Section 242", + "United States", + "health", + "health care facilities", + "hospitals", + "housing", + "point", + "population", + "society" + ], + "last_harvested_date": "2026-09-30T15:12:58.170097", + "organization": { + "aliases": [ + "dept" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "7f8ee588-32a3-4b6c-b435-d6603c91dbcc", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/hud.png", + "name": "Department of Housing and Urban Development", + "organization_type": "Federal Government", + "slug": "hud" + }, + "parent_identifier": null, + "popularity": 13, + "publisher": "U.S. Department of Housing and Urban Development", + "slug": "hud-insured-hospitals", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [], + "title": "HUD-Insured Hospitals", + "type": "dataset" + }, + { + "_score": 16.606499, "_sort": [ 1790724214932, - 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14.1336, + 14.092421, 8, "f833beb3-5a11-4c99-885e-185be5591f4e" ], @@ -1267,10 +4624,10 @@ "type": "dataset" }, { - "_score": 19.311329, + "_score": 19.276546, "_sort": [ 1790724026435, - 19.311329, + 19.276546, 155, "1f851a8d-9683-4e57-9cff-4844a39d9b5a" ], @@ -1390,10 +4747,10 @@ "type": "dataset" }, { - "_score": 25.603382, + "_score": 25.583502, "_sort": [ 1790724019423, - 25.603382, + 25.583502, 3, "1b291e1e-eacb-4072-b71b-b7ee1f149b34" ], @@ -1486,10 +4843,10 @@ "type": "dataset" }, { - "_score": 55.616783, + "_score": 55.619465, "_sort": [ 1790723989360, - 55.616783, + 55.619465, 0, "c76c2200-2ed8-4394-ad7b-515acd85e222" ], @@ -1586,10 +4943,10 @@ "type": "dataset" }, { - "_score": 3.0480409, + "_score": 3.0421124, "_sort": [ 1790723976794, - 3.0480409, + 3.0421124, 1, "74400e44-6b4a-4482-93a9-22642c995cb8" ], @@ -1702,10 +5059,10 @@ "type": "dataset" }, { - "_score": 23.568438, + "_score": 23.57166, "_sort": [ 1790723942816, - 23.568438, + 23.57166, 4, "454f76bb-111e-4cf5-9d01-2049b84703d2" ], @@ -1798,10 +5155,10 @@ "type": "dataset" }, { - 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Does not include MAGI Medicaid or CHIP applications. Includes: \n\nWeekly applications received: All programs\nWeekly applications received: Cash assistance\t\nWeekly applications received: Non-MAGI medical assistance\t\nWeekly applications received: SNAP\t\nDaily average applications received: All programs\nDaily average applications received: Cash assistance\nDaily average applications received: Non-MAGI medical assistance\nDaily average applications received: SNAP\nPercentage of weekly applications: Cash assistance\nPercentage of weekly applications: Non-MAGI medical assistance\nPercentage of weekly applications: SNAP\nWeekly Percent Change Compared to Average Week before Mar 16 (baseline): All programs\nWeekly Percent Change Compared to Average Week before Mar 16 (baseline): Cash assistance\nWeekly Percent Change Compared to Average Week before Mar 16 (baseline): Medical assistance\nWeekly Percent Change Compared to Average Week before Mar 16 (baseline): SNAP\n\nData updated weekly.", "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/161b9741-2a0d-49bb-a1ea-458019ab3508", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/161b9741-2a0d-49bb-a1ea-458019ab3508/raw", - "has_download": true, - "has_spatial": false, - "identifier": "https://data.ct.gov/api/views/ymej-83fh", - "keyword": [ - "covid-19", - "economic recovery" - ], - "last_harvested_date": "2026-09-29T23:18:09.526982", - "organization": { - "aliases": [ - "ct" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "c0e9f307-e44b-4de2-bb46-e8045d0990db", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/state_ct.png", - "name": "State of Connecticut", - "organization_type": "State Government", - "slug": "connecticut" - }, - "parent_identifier": null, - "popularity": 1, - "publisher": "data.ct.gov", - "slug": "weekly-dss-application-activity-before-and-during-covid-19-emergency", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [ - "Health and Human Services" - ], - "title": "Weekly DSS Application Activity Before and During COVID-19 Emergency", - "type": "dataset" - }, - { - "_score": 9.193024, - "_sort": [ - 1790723886474, - 9.193024, - 9, - "47907419-bddc-4230-97b0-8b0ece55a0a3" - ], - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Open Data Admin", - "hasEmail": "mailto:no-reply@data.ct.gov" - }, - "description": "Municipal Fiscal Indicators is an annual compendium of information compiled by the Office of Policy and Management, Office of Finance, Municipal Finance Services Unit (MFS). Municipal Fiscal Indicators contains the most current financial data available for each of Connecticut's 169 municipalities.\n\nThe data contained in Indicators provides key financial and demographic information on municipalities in Connecticut. The data includes selected demographic and economic data relating to, or having an impact upon, a municipality’s financial condition.\n\nThe majority of this data was compiled from the audited financial statements that are filed annually with the State of Connecticut, Office of Policy and Management, Office of Finance. Unlike prior years' where the audited financial information was compiled by OPM, the FY 2020 and beyond information in this edition was based upon the self-reporting by municipalities of their own audited data.\n\nNote: This dataset includes annually reported data using three types of years: calendar year, fiscal year, and grand list year. The calendar year spans January 1 to December 31. In Connecticut, the state fiscal year runs from July 1 to June 30, with the numerical year indicating when the fiscal year ends (e.g., fiscal year 2022 ended on June 30, 2022). The grand list year refers to the year municipalities assess property values, which occurs annually on October 1. For example, the property values assessed on October 1, 2020, are referred to as \"Grand List Year 2020.\" However, these values are used to levy property taxes for the next fiscal year, spanning July 1, 2021, to June 30, 2022. In this context, grand list year 2020 corresponds to fiscal year ending 2022. Similarly, mill rates for each year are based on the grand list from two years prior.\n\nThe most recent edition is for the Fiscal Years Ended 2019-2023 published in September 2025.\n\nFor additional data on net current expenditures per pupil, see the State Department of Education website here: https://portal.ct.gov/sde/fiscal-services/net-current-expenditures-per-pupil-used-for-excess-cost-grant-basic-contributions/documents\n\nFor additional population data from the Department of Public Health, visit their website here: https://portal.ct.gov/dph/health-information-systems--reporting/population/annual-town-and-county-population-for-connecticut\n\nThe most recent data on the Municipal Fiscal Indicators is included in the following datasets:\n\nThe most recent data on the Municipal Fiscal Indicators is included in the following datasets:\n\nMunicipal-Fiscal-Indicators: Financial Statement Information, 2020-2023\nhttps://data.ct.gov/d/d6pe-dw46\n\nMunicipal-Fiscal-Indicators: Uniform Chart of Accounts, 2020-2023\nhttps://data.ct.gov/d/e2qt-k238\n\nMunicipal Fiscal Indicators: Pension Funding Information for Defined Benefit Pension Plans, 2020-2023\nhttps://data.ct.gov/d/73q3-sgr8\n\nMunicipal Fiscal Indicators: Type and Number of Pension Plans, 2020-2023\nhttps://data.ct.gov/d/i84g-vvfb\n\nMunicipal Fiscal Indicators: Other Post-Employment Benefits (OPEB), 2020-2023\nhttps://data.ct.gov/d/ei7n-pnn9\n\nMunicipal Fiscal Indicators: Economic and Grand List Data, 2019-2025\nhttps://data.ct.gov/d/xgef-f6jp\n\nMunicipal Fiscal Indicators: Benchmark Labor Data, 2019-2024\nhttps://data.ct.gov/d/5ijb-j6bn\n\nMunicipal Fiscal Indicators: Bond Ratings, 2019-2023\nhttps://data.ct.gov/d/a65i-iag5\n\nMunicipal Fiscal Indicators: Individual Town Data, 2014-2023\nhttps://data.ct.gov/d/ej6f-y2wf\n\nMunicipal Fiscal Indicators: Totals and Averages, 2014-2023\nhttps://data.ct.gov/d/ryvc-y5rf", - "distribution": [ - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/xgef-f6jp/columns.json", - "describedByType": "application/json", - "downloadURL": "https://data.ct.gov/api/v3/views/xgef-f6jp/query.json?accessType=DOWNLOAD", - "mediaType": "application/json" - }, - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/xgef-f6jp/columns.xml", - "describedByType": "application/xml", - "downloadURL": "https://data.ct.gov/api/v3/views/xgef-f6jp/query.xml?accessType=DOWNLOAD", - "mediaType": "application/xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.ct.gov/api/v3/views/xgef-f6jp/export.csv?accessType=DOWNLOAD", - "mediaType": "text/csv" - } - ], - "identifier": "https://data.ct.gov/api/views/xgef-f6jp", - "issued": "2026-04-28", - "keyword": [ - "2019 municipal fiscal indicators", - "2020 municipal fiscal indicators", - "2021 municipal fiscal indicators", - "2022 municipal fiscal indicators", - "2023 municipal fiscal indicators", - "municipal fiscal indicators", - "opm" - ], - "landingPage": "https://data.ct.gov/d/xgef-f6jp", - "modified": "2026-07-17", - "publisher": { - "@type": "org:Organization", - "name": "data.ct.gov" - }, - "theme": [ - "Local Government" - ], - "title": "Municipal Fiscal Indicators: Economic and Grand List Data, 2019-2025" - }, - "description": "Municipal Fiscal Indicators is an annual compendium of information compiled by the Office of Policy and Management, Office of Finance, Municipal Finance Services Unit (MFS). Municipal Fiscal Indicators contains the most current financial data available for each of Connecticut's 169 municipalities.\n\nThe data contained in Indicators provides key financial and demographic information on municipalities in Connecticut. The data includes selected demographic and economic data relating to, or having an impact upon, a municipality’s financial condition.\n\nThe majority of this data was compiled from the audited financial statements that are filed annually with the State of Connecticut, Office of Policy and Management, Office of Finance. Unlike prior years' where the audited financial information was compiled by OPM, the FY 2020 and beyond information in this edition was based upon the self-reporting by municipalities of their own audited data.\n\nNote: This dataset includes annually reported data using three types of years: calendar year, fiscal year, and grand list year. The calendar year spans January 1 to December 31. In Connecticut, the state fiscal year runs from July 1 to June 30, with the numerical year indicating when the fiscal year ends (e.g., fiscal year 2022 ended on June 30, 2022). The grand list year refers to the year municipalities assess property values, which occurs annually on October 1. For example, the property values assessed on October 1, 2020, are referred to as \"Grand List Year 2020.\" However, these values are used to levy property taxes for the next fiscal year, spanning July 1, 2021, to June 30, 2022. In this context, grand list year 2020 corresponds to fiscal year ending 2022. 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View the full dataset and detailed metadata <a href=\"https://data.cms.gov/covid-19/covid-19-nursing-home-data\">here</a>.\n\nThe Nursing Home COVID-19 Public File includes data reported by nursing homes to the CDC’s National Healthcare Safety Network (NHSN) system COVID-19 Long Term Care Facility Module, including Resident Impact, Facility Capacity, Staff & Personnel, and Supplies & Personal Protective Equipment, and Ventilator Capacity and Supplies Data Elements.", - "distribution": [ - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/w8wc-65i5/columns.json", - "describedByType": "application/json", - "downloadURL": "https://data.ct.gov/api/v3/views/w8wc-65i5/query.json?accessType=DOWNLOAD", - "mediaType": "application/json" - }, - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/w8wc-65i5/columns.xml", - "describedByType": "application/xml", - "downloadURL": "https://data.ct.gov/api/v3/views/w8wc-65i5/query.xml?accessType=DOWNLOAD", - "mediaType": "application/xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.ct.gov/api/v3/views/w8wc-65i5/export.csv?accessType=DOWNLOAD", - "mediaType": "text/csv" - } - ], - "identifier": "https://data.ct.gov/api/views/w8wc-65i5", - "issued": "2024-11-04", - "keyword": [ - "covid congregate settings", - "covid-19" - ], - "landingPage": "https://data.ct.gov/d/w8wc-65i5", - "license": "https://www.usa.gov/government-works", - "modified": "2026-07-17", - "publisher": { - "@type": "org:Organization", - "name": "data.ct.gov" - }, - "theme": [ - "Health and Human Services" - ], - "title": "CMS COVID-19 Nursing Home Dataset" - }, - "description": "The Nursing Home COVID-19 Public File from the Centers for Medicare & Medicaid Services, filtered for Connecticut. View the full dataset and detailed metadata <a href=\"https://data.cms.gov/covid-19/covid-19-nursing-home-data\">here</a>.\n\nThe Nursing Home COVID-19 Public File includes data reported by nursing homes to the CDC’s National Healthcare Safety Network (NHSN) system COVID-19 Long Term Care Facility Module, including Resident Impact, Facility Capacity, Staff & Personnel, and Supplies & Personal Protective Equipment, and Ventilator Capacity and Supplies Data Elements.", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/0acc598c-745d-4403-bf7c-01ce4249221b", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/0acc598c-745d-4403-bf7c-01ce4249221b/raw", - "has_download": true, - "has_spatial": false, - "identifier": "https://data.ct.gov/api/views/w8wc-65i5", - "keyword": [ - "covid congregate settings", - "covid-19" - ], - "last_harvested_date": "2026-09-29T23:18:03.391607", - "organization": { - "aliases": [ - "ct" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "c0e9f307-e44b-4de2-bb46-e8045d0990db", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/state_ct.png", - "name": "State of Connecticut", - "organization_type": "State Government", - "slug": "connecticut" - }, - "parent_identifier": null, - "popularity": 9, - "publisher": "data.ct.gov", - "slug": "cms-covid-19-nursing-home-dataset", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [ - "Health and Human Services" - ], - "title": "CMS COVID-19 Nursing Home Dataset", - "type": "dataset" - }, - { - "_score": 17.535782, - "_sort": [ - 1790723882187, - 17.535782, - 4, - "81008b45-8f0f-4e4b-a79b-27d6e9770ac2" - ], - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Open Data Admin", - "hasEmail": "mailto:no-reply@data.ct.gov" - }, - "description": "The \"COVID-19 Reported Patient Impact and Hospital Capacity by Facility\" dataset from the U.S. Department of Health & Human Services, filtered for Connecticut. View the full dataset and detailed metadata here: https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/anag-cw7u\n\nThe following dataset provides facility-level data for hospital utilization aggregated on a weekly basis (Friday to Thursday). These are derived from reports with facility-level granularity across two main sources: (1) HHS TeleTracking, and (2) reporting provided directly to HHS Protect by state/territorial health departments on behalf of their healthcare facilities.\n\nThe hospital population includes all hospitals registered with Centers for Medicare & Medicaid Services (CMS) as of June 1, 2020. It includes non-CMS hospitals that have reported since July 15, 2020. It does not include psychiatric, rehabilitation, Indian Health Service (IHS) facilities, U.S. Department of Veterans Affairs (VA) facilities, Defense Health Agency (DHA) facilities, and religious non-medical facilities.\n\nFor a given entry, the term “collection_week” signifies the start of the period that is aggregated. For example, a “collection_week” of 2020-11-20 means the average/sum/coverage of the elements captured from that given facility starting and including Friday, November 20, 2020, and ending and including reports for Thursday, November 26, 2020.\n\nReported elements include an append of either “_coverage”, “_sum”, or “_avg”.\n\nA “_coverage” append denotes how many times the facility reported that element during that collection week.\n\nA “_sum” append denotes the sum of the reports provided for that facility for that element during that collection week.\n\nA “_avg” append is the average of the reports provided for that facility for that element during that collection week.\n\nThe file will be updated weekly. No statistical analysis is applied to impute non-response. For averages, calculations are based on the number of values collected for a given hospital in that collection week. Suppression is applied to the file for sums and averages less than four (4). In these cases, the field will be replaced with “-999,999”.\n\nThis data is preliminary and subject to change as more data become available. Data is available starting on July 31, 2020.\n\nSometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied according to prioritization rules within HHS Protect.\n\nFor influenza fields listed in the file, the current HHS guidance marks these fields as optional. As a result, coverage of these elements are varied.\n\nOn May 3, 2021, the following fields have been added to this data set.\nhhs_ids\nprevious_day_admission_adult_covid_confirmed_7_day_coverage\nprevious_day_admission_pediatric_covid_confirmed_7_day_coverage\nprevious_day_admission_adult_covid_suspected_7_day_coverage\nprevious_day_admission_pediatric_covid_suspected_7_day_coverage\nprevious_week_personnel_covid_vaccinated_doses_administered_7_day_sum\ntotal_personnel_covid_vaccinated_doses_none_7_day_sum\ntotal_personnel_covid_vaccinated_doses_one_7_day_sum\ntotal_personnel_covid_vaccinated_doses_all_7_day_sum\nprevious_week_patients_covid_vaccinated_doses_one_7_day_sum\nprevious_week_patients_covid_vaccinated_doses_all_7_day_sum\n\n\nOn May 8, 2021, this data set has been converted to a corrected data set. The corrections applied to this data set are to smooth out data anomalies caused by keyed in data errors. To help determine which records have had corrections made to it. An additional Boolean field called is_corrected has been added. To see the numbers as reported by the facilities, go to:\nhttps://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb\n\nOn May 13, 2021 Changed vaccination fields from sum to max or min fields. 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In these cases, the field will be replaced with “-999,999”.\n\nThis data is preliminary and subject to change as more data become available. Data is available starting on July 31, 2020.\n\nSometimes, reports for a given facility will be provided to both HHS TeleTracking and HHS Protect. When this occurs, to ensure that there are not duplicate reports, deduplication is applied according to prioritization rules within HHS Protect.\n\nFor influenza fields listed in the file, the current HHS guidance marks these fields as optional. As a result, coverage of these elements are varied.\n\nOn May 3, 2021, the following fields have been added to this data set.\nhhs_ids\nprevious_day_admission_adult_covid_confirmed_7_day_coverage\nprevious_day_admission_pediatric_covid_confirmed_7_day_coverage\nprevious_day_admission_adult_covid_suspected_7_day_coverage\nprevious_day_admission_pediatric_covid_suspected_7_day_coverage\nprevious_week_personnel_covid_vaccinated_doses_administered_7_day_sum\ntotal_personnel_covid_vaccinated_doses_none_7_day_sum\ntotal_personnel_covid_vaccinated_doses_one_7_day_sum\ntotal_personnel_covid_vaccinated_doses_all_7_day_sum\nprevious_week_patients_covid_vaccinated_doses_one_7_day_sum\nprevious_week_patients_covid_vaccinated_doses_all_7_day_sum\n\n\nOn May 8, 2021, this data set has been converted to a corrected data set. The corrections applied to this data set are to smooth out data anomalies caused by keyed in data errors. To help determine which records have had corrections made to it. An additional Boolean field called is_corrected has been added. To see the numbers as reported by the facilities, go to:\nhttps://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/uqq2-txqb\n\nOn May 13, 2021 Changed vaccination fields from sum to max or min fields. 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A \"Y\" value under the different substance columns indicates that particular substance was detected.\n\nData are derived from an investigation by the Office of the Chief Medical Examiner which includes the toxicity report, death certificate, as well as a scene investigation.\n\nThe “Morphine (Not Heroin)” values are related to the differences between how Morphine and Heroin are metabolized and therefor detected in the toxicity results. Heroin metabolizes to 6-MAM which then metabolizes to morphine. 6-MAM is unique to heroin, and has a short half-life (as does heroin itself). Thus, in some heroin deaths, the toxicity results will not indicate whether the morphine is from heroin or prescription morphine. In these cases the Medical Examiner may be able to determine the cause based on the scene investigation (such as finding heroin needles). If they find prescription morphine at the scene it is certified as “Morphine (not heroin).” Therefor, the Cause of Death may indicate Morphine, but the Heroin or Morphine (Not Heroin) may not be indicated.\n\n “Any Opioid” – If the Medical Examiner cannot conclude whether it’s RX Morphine or heroin based morphine in the toxicity results, that column may be checked", - "distribution": [ - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/rybz-nyjw/columns.json", - "describedByType": "application/json", - "downloadURL": "https://data.ct.gov/api/v3/views/rybz-nyjw/query.json?accessType=DOWNLOAD", - "mediaType": "application/json" - }, - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/rybz-nyjw/columns.xml", - "describedByType": "application/xml", - "downloadURL": "https://data.ct.gov/api/v3/views/rybz-nyjw/query.xml?accessType=DOWNLOAD", - "mediaType": "application/xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.ct.gov/api/v3/views/rybz-nyjw/export.csv?accessType=DOWNLOAD", - "mediaType": "text/csv" - } - ], - "identifier": "https://data.ct.gov/api/views/rybz-nyjw", - "issued": "2022-05-13", - "keyword": [ - "death", - "drug", - "heroin", - "ocme", - "opioid", - "overdose", - "substance abuse" - ], - "landingPage": "https://data.ct.gov/d/rybz-nyjw", - "modified": "2026-07-17", - "publisher": { - "@type": "org:Organization", - "name": "data.ct.gov" - }, - "theme": [ - "Health and Human Services" - ], - "title": "Accidental Drug Related Deaths 2012-2024" - }, - "description": "A listing of each accidental death associated with drug overdose in Connecticut from 2012 to 2024. 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The data can be explored by searching for specific payee names or by browsing by Government Function. The <a href = \"https://opencheckbook.ct.gov\" target =\"_blank\"> Open Checkbook app </a> allows the user to drill down from aggregated spending accounts all the way down to each individual payment to a payee for more recent fiscal years.\n\nThe actively updated, most recent seven fiscal years are available <a href = \"https://data.ct.gov/Government/State-of-CT-Open-Expenditures-Ledger/jz5u-r6jf/about_data\" target =\"_blank\"> here </a> \n\nThis data is appended annually with an additional year of historical data.\n\nCertain payee names have been removed in order to protect the privacy of individuals, in accordance with Health Insurance Portability and Accountability Act (HIPAA) regulations or where the information is otherwise protected by law. \n\nRedacted information includes:\n•Payees who are statutorily protected\n•Information that would lead to violating HIPAA laws\n•Information of Minors", - "distribution": [ - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/avfh-2eg7/columns.json", - "describedByType": "application/json", - "downloadURL": "https://data.ct.gov/api/v3/views/avfh-2eg7/query.json?accessType=DOWNLOAD", - "mediaType": "application/json" - }, - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/avfh-2eg7/columns.xml", - "describedByType": "application/xml", - "downloadURL": "https://data.ct.gov/api/v3/views/avfh-2eg7/query.xml?accessType=DOWNLOAD", - "mediaType": "application/xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.ct.gov/api/v3/views/avfh-2eg7/export.csv?accessType=DOWNLOAD", - "mediaType": "text/csv" - } - ], - "identifier": "https://data.ct.gov/api/views/avfh-2eg7", - "issued": "2026-07-11", - "keyword": [ - "checkbook", - "expenditures", - "ledger", - "open connecticut", - "vendor payments" - ], - "landingPage": "https://data.ct.gov/d/avfh-2eg7", - "modified": "2026-09-26", - "publisher": { - "@type": "org:Organization", - "name": "data.ct.gov" - }, - "theme": [ - "Government" - ], - "title": "State of CT: Open Expenditures - Ledger Archive" - }, - "description": "This archived data allows citizens to view who received payments from the State for goods or services and how much they received for historical fiscal years beginning in state fiscal year 2011-2012. The data can be explored by searching for specific payee names or by browsing by Government Function. The <a href = \"https://opencheckbook.ct.gov\" target =\"_blank\"> Open Checkbook app </a> allows the user to drill down from aggregated spending accounts all the way down to each individual payment to a payee for more recent fiscal years.\n\nThe actively updated, most recent seven fiscal years are available <a href = \"https://data.ct.gov/Government/State-of-CT-Open-Expenditures-Ledger/jz5u-r6jf/about_data\" target =\"_blank\"> here </a> \n\nThis data is appended annually with an additional year of historical data.\n\nCertain payee names have been removed in order to protect the privacy of individuals, in accordance with Health Insurance Portability and Accountability Act (HIPAA) regulations or where the information is otherwise protected by law. \n\nRedacted information includes:\n•Payees who are statutorily protected\n•Information that would lead to violating HIPAA laws\n•Information of Minors", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/9a797b5d-7d08-4a3c-b7fc-e559885a4e02", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/9a797b5d-7d08-4a3c-b7fc-e559885a4e02/raw", - "has_download": true, - "has_spatial": false, - "identifier": "https://data.ct.gov/api/views/avfh-2eg7", - "keyword": [ - "checkbook", - "expenditures", - "ledger", - "open connecticut", - "vendor payments" - ], - "last_harvested_date": "2026-09-29T23:17:03.201529", - "organization": { - "aliases": [ - "ct" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "c0e9f307-e44b-4de2-bb46-e8045d0990db", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/state_ct.png", - "name": "State of Connecticut", - "organization_type": "State Government", - "slug": "connecticut" - }, - "parent_identifier": null, - "popularity": 5, - "publisher": "data.ct.gov", - "slug": "state-of-ct-open-expenditures-ledger-archive", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [ - "Government" - ], - "title": "State of CT: Open Expenditures - Ledger Archive", - "type": "dataset" - }, - { - "_score": 10.718412, - "_sort": [ - 1790723822030, - 10.718412, - 8, - "9155c9c3-44e7-4d7a-b629-a6ed12314504" - ], - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "contactPoint": { - "@type": "vcard:Contact", - "fn": "PSAdmin", - "hasEmail": "mailto:no-reply@data.ct.gov" - }, - "description": "Note: This dataset is undergoing essential maintenance until Wednesday September 30th. The data currently reflects payments made through September 24th, 2026. More recent records will be available when maintenance is completed.\n\nThis data allows citizens to view who received payments from the state for goods or services and how much they received. The data can be explored by searching for specific payee names or by browsing by Government Function. <a href=\"http://opencheckbook.ct.gov\">The Open Checkbook app</a> allows the user to drill down from aggregated spending accounts all the way down to each individual payment to a payee. \n\nThe data is updated nightly and therefore reflects current spending activities more accurately than any other publicly available source. In general the data reflects all payments made up to 24 to 48 hours prior to view.\n\nCertain payee names have been removed in order to protect the privacy of individuals, in accordance with Health Insurance Portability and Accountability Act (HIPAA) regulations or where the information is otherwise protected by law. \n\nRedacted information includes:\n•Payees who are statutorily protected\n•Information that would lead to violating HIPAA laws\n•Information of Minors", - "distribution": [ - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/ajdm-rvz7/columns.json", - "describedByType": "application/json", - "downloadURL": "https://data.ct.gov/api/v3/views/ajdm-rvz7/query.json?accessType=DOWNLOAD", - "mediaType": "application/json" - }, - { - "@type": "dcat:Distribution", - "describedBy": "https://data.ct.gov/api/views/ajdm-rvz7/columns.xml", - "describedByType": "application/xml", - "downloadURL": "https://data.ct.gov/api/v3/views/ajdm-rvz7/query.xml?accessType=DOWNLOAD", - "mediaType": "application/xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.ct.gov/api/v3/views/ajdm-rvz7/export.csv?accessType=DOWNLOAD", - "mediaType": "text/csv" - } - ], - "identifier": "https://data.ct.gov/api/views/ajdm-rvz7", - "issued": "2026-09-26", - "keyword": [ - "checkbook", - "expenditures", - "usodcensus" - ], - "landingPage": "https://data.ct.gov/d/ajdm-rvz7", - "modified": "2026-09-28", - "publisher": { - "@type": "org:Organization", - "name": "data.ct.gov" - }, - "theme": [ - "Government" - ], - "title": "State of CT: Open Expenditures - Ledger Current" - }, - "description": "Note: This dataset is undergoing essential maintenance until Wednesday September 30th. 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In general the data reflects all payments made up to 24 to 48 hours prior to view.\n\nCertain payee names have been removed in order to protect the privacy of individuals, in accordance with Health Insurance Portability and Accountability Act (HIPAA) regulations or where the information is otherwise protected by law. \n\nRedacted information includes:\n•Payees who are statutorily protected\n•Information that would lead to violating HIPAA laws\n•Information of Minors", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/fa7fcd3f-1c96-48eb-b25b-d35bfa194be4", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/fa7fcd3f-1c96-48eb-b25b-d35bfa194be4/raw", - "has_download": true, - "has_spatial": false, - "identifier": "https://data.ct.gov/api/views/ajdm-rvz7", - "keyword": [ - "checkbook", - "expenditures", - "usodcensus" - ], - "last_harvested_date": "2026-09-29T23:17:02.030146", - "organization": { - "aliases": [ - "ct" - ], - "code_repo_exempt": false, -