AndreaBozzo/ceres-open-data-index huggingface dataset:
Connecticut NWI Wetlands 2024

<div style='text-align:Left;'><div><div><p><span>This data set represents the extent, approximate location and type of wetlands and deepwater habitats in the United States and its Territories. These data delineate the areal extent of wetlands and surface waters as defined by Cowardin et al. (1979). The National Wetlands Inventory - Version 2, Surface Waters and Wetlands Inventory was derived by retaining the wetland and deepwater polygons that compose the NWI digital wetlands spatial data layer and reintroducing any linear wetland or surface water features that were orphaned from the original NWI hard copy maps by converting them to narrow polygonal features. Additionally, the data are supplemented with hydrography data, buffered to become polygonal features, as a secondary source for any single-line stream features not mapped by the NWI and to complete segmented connections. Wetland mapping conducted in WA, OR, CA, NV and ID after 2012 and most other projects mapped after 2015 were mapped to include all surface water features and are not derived data. The linear hydrography dataset used to derive Version 2 was the U.S. Geological Survey's National Hydrography Dataset (NHD). Specific information on the NHD version used to derive Version 2 and where Version 2 was mapped can be found in the 'comments' field of the Wetlands_Project_Metadata feature class. Certain wetland habitats are excluded from the National mapping program because of the limitations of aerial imagery as the primary data source used to detect wetlands. These habitats include seagrasses or submerged aquatic vegetation that are found in the intertidal and subtidal zones of estuaries and near shore coastal waters. Some deepwater reef communities (coral or tuberficid worm reefs) have also been excluded from the inventory. These habitats, because of their depth, go undetected by aerial imagery. By policy, the Service also excludes certain types of "farmed wetlands" as may be defined by the Food Security Act or that do not coincide with the Cowardin et al. definition. Contact the Service's Regional Wetland Coordinator for additional information on what types of farmed wetlands are included on wetland maps. This dataset should be used in conjunction with the Wetlands_Project_Metadata layer, which contains project specific wetlands mapping procedures and information on dates, scales and emulsion of imagery used to map the wetlands within specific project boundaries.</span></p></div></div></div>

Tags: bogs, coastal-waters, connecticut, deepwater-habitats, environment, fens, geoscientificinformation, hydrography, inlandwaters, marshes, national-wetlands-inventory, nwi, oceans, surface-water, swamps, u-s-fish-and-wildlife-service, usfws, wetlands
Organization: State of Connecticut
Combined Asthma Emergency Department and Hospitalizations by Census Tract, Town, Connecticut, 2010-2014

Note:  77% of overall reported events were geocoded by census tract level [ESRI ArcGIS], and the remaining 23% of events were equally weighted and redistributed proportionally within each town across the state. Therefore, all numbers and rates are estimates only, and reflect all asthma hospitalizations and ED visits that occurred in Connecticut from 2010-2014.
Rates based on counts fewer than 20 are unstable, and therefore are not presented; cells with less than 6 events are not displayed due to confidentiality regulations.

Tags: asthma, emergency-department, hospitalizations
Organization: State of Connecticut
Shoreline Change Transects 1983-2006

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: connecticut, ct-deep, ct-seagrant, noaa, shoreline, short-term, uconn, usgs
Organization: State of Connecticut
Positive Net Shoreline Movement (meters)

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: connecticut, ct-deep, ct-seagrant, noaa, shoreline, short-term, uconn, usgs
Organization: State of Connecticut
COVID-19 Cases in Child Care Centers and Group Child Care Homes by Week - Archive

This dataset summarizes the number of cases among child care attendees and staff reported to the Department of Public Health (DPH). 

Each week, licensed child care centers are required to report cases of COVID-19 among attendees and staff to the DPH and the local health department. There are 1,388 licensed child care centers and group child care homes in Connecticut that serve approximately 50,000 children. 

Beginning the week of January 9th, reporting transitioned from individual case reporting to aggregate reporting of cases among attendees and staff. The form for collecting aggregate data from child care centers can be found here: https://forms.office.com/pages/responsepage.aspx?id=-nyLEd2juUiwJjH_abtzi-XnLB2c4-RLhUuoE9uLWJJUNURSR09GNlBBWFVIMlFaQ1BGUzcxMFNDUy4u

Data are preliminary and, like other passive surveillance systems, under reporting occurs and the true incidence of disease is more than the number of cases reported. Data from previous weeks are updated as new data are received. Several weeks of data from the new reporting system will be needed to determine trends.

Tags: child-care, covid-19, covid-archive
Organization: State of Connecticut
Vital Statistics

The Office of Vital Records at the Connecticut Department of Public Health maintains statewide registries of vital events (births, fetal deaths, deaths and marriages) which have occurred in CT or to residents of CT.  Data collected through the vital records registries are analyzed annually to create statistical reports on the number of events and associated demographic and health information.  In CT, these vital statistics reports are known as Registration Reports.

Monthly Birth and Death Counts and Annual Registration Reports and Methods are available on the Department of Public Health's website.

Tags: vital-records, vital-statistics
Organization: State of Connecticut
Postive End Point Rates (meters/year)

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: connecticut, ct-deep, ct-seagrant, noaa, shoreline, short-term, uconn, usgs
Organization: State of Connecticut
Negative End Point Rates (meters/year)

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: connecticut, ct-deep, ct-seagrant, noaa, shoreline, short-term, uconn, usgs
Organization: State of Connecticut
Negative Net Shoreline Movement (meters)

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: connecticut, ct-deep, ct-seagrant, noaa, shoreline, short-term, uconn, usgs
Organization: State of Connecticut
Broadband Data by Town - 2024

<span style='font-family:&quot;Avenir Next&quot;, &quot;Avenir Next&quot;; font-size:16px;'>The Connecticut Broadband Availability and Adoption Maps were created to help citizens and policymakers understand the strengths and weaknesses of broadband infrastructure in the state. Data is aggregated to the block, tract, and town (county subdivision) levels and includes counts of locations classified as unserved, underserved, and served as well as whether they meet the state goal of 1000Mbps/100Mbps. This feature layer includes all OPM collected data at the town level.</span>

Tags: 2024, broadband, connectivity, ct, internet
Organization: State of Connecticut
HUC Watershed Line

<div><span style='font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, system-ui, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Web&quot;, sans-serif; font-size:14px;'>This data set is a digital hydrologic unit boundary layer that is at the Subwatershed (12-digit) level. The original data set was developed by delineating the boundary lines on base USGS 1:24000 scale topographic quadrangle, and digitizing the delineated lines. Digital Raster Graphics (DRG) images were used for edits to the data layer.</span></div><div><span><span style='font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, system-ui, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Web&quot;, sans-serif; font-size:14px;'><p>This data set consists of geo-referenced digital map data and attribute data. The spatial data are in a statewide coverage format and include complete coverage of the entire state of Connecticut, and small parts of surrounding states. The hydrologic unit ID code attached to each delineated polygon is linked to the attribute data.<br /><br /></p> </span></span></div>

Tags: hydrologic-units, subwatersheds, watershed-boundary-dataset, watersheds, wbd
Organization: State of Connecticut
Connecticut Enterprise Zone Certifications

In the attached excel document you will find information on the Connecticut Enterprise Zone program from 2002 to and including 2017 final approved certifications (projects eligible for benefits).

Additional program information can be found here:  http://www.ct.gov/ecd/cwp/view.asp?a=1097&q=249762

Tags: business, decd, economic-development, enterprise-zones, executive-order-38, executive-order-39
Organization: State of Connecticut
COVID-19 Contact Tracing: COVID Alert CT Summary by Week - ARCHIVE

Note: This dataset has been archived and is no longer being updated.

COVID Alert CT is Connecticut's voluntary, anonymous, exposure-notification smartphone app. If downloaded, the app will alert users if they have come into close contact with somebody who tests positive for COVID-19.

This dataset includes the cumulative and weekly activations for COVID Alert CT for iOS and Android smartphones.

The location of app users is not tracked--the app uses Bluetooth technology to detect when another person with the same app comes within 6 feet. The phones exchange a secure code with the each other to record that they were near. The number of codes issued and claimed is also included in this dataset. 

Data presented are based on a weekly reporting period (Sunday - Saturday). All data are preliminary and are subject to change.

Additional information on COVID-19 Contact Tracing can be found here: https://portal.ct.gov/coronavirus/covidalertCT/homepage

Tags: contact-tracing, covid-19
Organization: State of Connecticut
HUC Watershed Poly

<div><span style='font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, system-ui, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Web&quot;, sans-serif; font-size:14px;'>This data set is a digital hydrologic unit boundary layer that is at the Subwatershed (12-digit) level. The original data set was developed by delineating the boundary lines on base USGS 1:24000 scale topographic quadrangle, and digitizing the delineated lines. Digital Raster Graphics (DRG) images were used for edits to the data layer.</span></div><div><span><span style='font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, system-ui, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;, &quot;Segoe UI Web&quot;, sans-serif; font-size:14px;'><p>This data set consists of geo-referenced digital map data and attribute data. The spatial data are in a statewide coverage format and include complete coverage of the entire state of Connecticut, and small parts of surrounding states. The hydrologic unit ID code attached to each delineated polygon is linked to the attribute data.<br /><br /></p> </span></span></div>

Tags: hydrologic-units, subwatersheds, watershed-boundary-dataset, watersheds, wbd
Organization: State of Connecticut
Positive Linear Regression Rates (meters/year)

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: change, connecticut, ct-deep, ct-seagrant, long-term, noaa, shoreline, uconn, usgs
Organization: State of Connecticut
CT Shorelines: 1880s-2006

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: change, connecticut, ct-deep, ct-seagrant, long-term, noaa, shoreline, uconn, usgs
Organization: State of Connecticut
Shoreline Change Short Term

Shorelines are continuously moving in response to winds, waves, tides, sediment supply, changes in relative sea level, and human activities. Shoreline changes are generally not constant through time and frequently switch from negative (erosion) to positive (accretion) and vice versa. Cyclic and non-cyclic processes change the position of the shoreline over a variety of timescales, from the daily and seasonal effects of winds and waves, to changes in sea level over a century to thousands of years. The shoreline "rate of change" statistic thus reflects a cumulative summary of the processes that altered the shoreline for the time period analyzed.

Tags: connecticut, ct-deep, ct-seagrant, noaa, shoreline, short-term, uconn, usgs
Organization: State of Connecticut
COVID-19 Cases in CT Schools (Statewide), 2021-2022 School Year - Archive

This dataset provides the number of weekly COVID-19 cases for staff and students in CT public and private PK-12 schools during the 2021-2022 school year. The following metrics are included:

Number of student cases - total
Number of student cases - fully vaccinated

June 30, 2022 is the last report for the 2021 – 2022 academic school year.  
Number of student cases - not vaccinated
Number of student cases - no vaccine information

Number of staff cases - total
Number of staff cases - fully vaccinated
Number of staff cases - not vaccinated
Number of staff cases - no vaccine information

Data for the 2020-2021 school year is available here: https://data.ct.gov/Health-and-Human-Services/COVID-19-Cases-in-CT-Schools-Statewide-2020-2021-S/ehua-hw73

Tags: covid-19, covid-archive, covid-school-data
Organization: State of Connecticut
NNDSS - Table II. Ehrlichiosis and Anaplasmosis, Anaplasma phagocytophilum infection to Ehrlichia chaffeensis infection

NNDSS - Table II. Ehrlichiosis and Anaplasmosis, Anaplasma phagocytophilum infection to Ehrlichia chaffeensis infection - 2018. In this Table, provisional cases of selected notifiable diseases (≥1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states or territory.

Note:

This table contains provisional cases of selected national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up.  Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html 

Footnotes:

C.N.M.I.: Commonwealth of Northern Mariana Islands. 
U: Unavailable. —: No reported cases. N: Not reportable. NA:  Not Available.  NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum. 

* Case counts for reporting years 2017 and 2018 are provisional and subject to change. Data for years 2013 through 2016 are finalized. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf.

Tags: 2018, anaplasma-phagocytophilum-infection, ehrlichia-chaffeensis-infection, ehrlichiosis-and-anaplasmosis, nedss, netss, nndss, wonder
Organization: U.S. Department of Health & Human Services
ASTDD Synopses of State Oral Health Programs - Selected indicators

2011-2022. The ASTDD Synopses of State Oral Health Programs contain information useful in tracking states’ efforts to improve oral health and contributions to progress toward the national targets for Healthy People objectives for oral health. A subset of the information collected from the most recent five years is provided on the Oral Health Data website. For more information, see http://www.cdc.gov/oralhealthdata/overview/synopses/index.html

Tags: cleft-lip-cleft-palate-recording, cleft-lip-cleft-palate-referral-to-care, infrastructure, oral-health, policy, programs, school-based-sealant-programs, state-dental-directors, state-oral-health-program-characteristics, workforce
Organization: U.S. Department of Health & Human Services
NNDSS - Table II. Invasive Pneumococcal to Legionellosis

NNDSS - Table II. Invasive Pneumococcal to Legionellosis - 2016.  In this Table, provisional* cases of selected† notifiable diseases (≥1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data.  Data on United States exclude counts from US territories.

Note:
These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting. 

Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available. 

Footnotes:
C.N.M.I.: Commonwealth of Northern Mariana Islands. 
U: Unavailable.    -: No reported cases.    N: Not reportable.    NN: Not Nationally Notifiable.  NP:  Nationally notifiable but not published.    Cum: Cumulative year-to-date counts.    Med: Median.    Max: Maximum.

* Case counts for reporting year 2016 are provisional and subject to change.   For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for TB are displayed in Table IV, which appears quarterly. 
† Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions. 
§ Includes drug resistant and susceptible cases of Invasive Pneumococcal Disease. This condition was previously named Streptococcus pneumoniae invasive disease and cases were reported to CDC using different event codes to specify whether the cases were drug resistant or in a defined age group, such as <5 years.

Tags: 2016, invasive-pneumococcal-disease, legionellosis, mmwr, nedss, netss, nndss, pneumococcal, wonder
Organization: U.S. Department of Health & Human Services