AndreaBozzo/ceres-open-data-index huggingface dataset:
Hazard Reduction by Habitats

Each point in Coastal Resiliency Assessment Shoreline Points represents a 250 meter segment of the Maryland coast, including Atlantic, Chesapeake Bay and Coastal Bay shorelines. The Natural Capital Project's Coastal Vulnerability model was used to calculate a Shoreline Hazard Index, representing the relative exposure of each segment to storm-induced erosion and flooding. Inputs to the model included 6 physical variables (geomorphology, elevation, sea level rise, wave power, storm surge height and erosion rates) and 5 habitat types (forest, marsh, dune, oyster reef and underwater grass). Two scenarios of the model were run: one scenario incorporating the protective role of all existing coastal habitats and the other scenario simulating the complete loss of habitats. The difference between the two scenarios indicates the potential magnitude of coastal hazard reduction by habitats at each location. Model results were integrated with MD DNR’s Community Flood Risk Areas (March, 2016) in order to highlight areas where hazard reduction by habitats is most likely to benefit at-risk coastal communities.

Organization: State of Maryland
Priority Shoreline Areas

Each point in Coastal Resiliency Assessment Shoreline Points represents a 250 meter segment of the Maryland coast, including Atlantic, Chesapeake Bay and Coastal Bay shorelines. The Natural Capital Project's Coastal Vulnerability model was used to calculate a Shoreline Hazard Index, representing the relative exposure of each segment to storm-induced erosion and flooding. Inputs to the model included 6 physical variables (geomorphology, elevation, sea level rise, wave power, storm surge height and erosion rates) and 5 habitat types (forest, marsh, dune, oyster reef and underwater grass). Two scenarios of the model were run: one scenario incorporating the protective role of all existing coastal habitats and the other scenario simulating the complete loss of habitats. The difference between the two scenarios indicates the potential magnitude of coastal hazard reduction by habitats at each location. Model results were integrated with MD DNR’s Community Flood Risk Areas (March, 2016) in order to highlight areas where hazard reduction by habitats is most likely to benefit at-risk coastal communities. This dataset was produced under award number NA13NOS4190136 from the Office of Ocean and Coastal Resource Management (OCRM), National Oceanic and Atmospheric Administration (NOAA) through the Maryland Department of Natural Resources Chesapeake and Coastal Services (CCS). The statements, finding and recommendations are those of the authors and do not necessarily reflect the views of NOAA or the U.S. Department of Commerce. The Natural Capital Project (NatCap), CCS and The Nature Conservancy (TNC) all contributed to the production of this dataset.

Organization: State of Maryland
Baltimore 10 years Shoreline Erosion Level

To quantify shoreline rates of change (erosion or accretion), Maryland Geological Survey (MGS) used historical and recent shorelines spanning 1994-2011 as input into the Digital Shoreline Analysis System (DSAS) Version 4.3. DSAS, a computer program developed by the U.S. Geological Survey (USGS), determines linear rates of shoreline change along closely spaced, shore-normal transects. Based on DSAS output, MGS assigned generalized rate of change categories as attributes to a recent shoreline for Baltimore County. This recent shoreline consisted of the National Oceanic and Atmospheric Administration (NOAA) Continually Updated Shoreline Product (CUSP) digital shoreline currently available for Baltimore County. Based on the results of an End Point Rate (EPR) analysis on the ca. 1990s shoreline and the ca. 2000/2010 shoreline (recent shoreline), MGS grouped the rate results into the following general categories: (a) No change (-0.01 to 0.01 feet/year), (b) Accretion (greater than 0.01 feet/year), (c) Slight erosion rate (0 to -2 feet/year), (d) Low erosion rate (-2 to -4 feet/year), (e) Moderate erosion rate (-4 to -8 ft/yr), (f) High erosion rate (greater than -8 feet/year), (g) Protected, (h) No data (insufficient shorelines to calculate 10-year EPR rate), (i) No data (no transects cast; unprotected or unknown shoreline condition), and (j) No data (rates not delivered; calculated rates suspect). Negative rate of change values indicate erosion, and positive values indicate accretion. In general, MGS tried to attribute lengths of shoreline of at least 80 meters in length sharing similar rates of change.

Organization: State of Maryland
Marsh Protection Potential Index

The Marsh Protection Potential Index (MPPI) ranks Maryland’s coastal marshes by their ability to protect vulnerable communities from coastal hazards. To do so, we identified five key questions to assess each marsh: How much is the marsh able to reduce the impact of coastal hazards? Is the marsh located where coastal hazards are a threat? Is the marsh located where there are people to protect? Is the marsh located adjacent to other protective habitats? Is the marsh likely to survive in the face of rising sea levels? Using data from the Coastal Resiliency Assessment and other sources, we developed metrics to score each marsh on these five questions. Then, the sub-scores were combined to create the Marsh Protection Potential Index overall rating, which ranks the protective ability of over 14,000 marshes statewide. It is important to note that the MPPI ranks marshes relative to other marshes, rather than providing an absolute measure of protective services. The Marsh Protection Potential Index does not attempt to describe the dollar-value of protective services provided by each marsh, nor does it compare marshes to other types of habitat or to other protection infrastructure solutions. In addition, the MPPI does not assess marshes on any of the other characteristics that often inform conservation priorities. Things like biodiversity, ecosystem health, rare species, recreation value, or water quality services are often important to stakeholders, and these are not captured by the MPPI. The MPPI is intended to supplement, not replace, the other ways conservation decision-makers prioritize natural habitats.

Organization: State of Maryland
Shoreline Hazard Index

Each point in Coastal Resiliency Assessment Shoreline Points represents a 250 meter segment of the Maryland coast, including Atlantic, Chesapeake Bay and Coastal Bay shorelines. The Natural Capital Project's Coastal Vulnerability model was used to calculate a Shoreline Hazard Index, representing the relative exposure of each segment to storm-induced erosion and flooding. Inputs to the model included 6 physical variables (geomorphology, elevation, sea level rise, wave power, storm surge height and erosion rates) and 5 habitat types (forest, marsh, dune, oyster reef and underwater grass). Two scenarios of the model were run: one scenario incorporating the protective role of all existing coastal habitats and the other scenario simulating the complete loss of habitats. The difference between the two scenarios indicates the potential magnitude of coastal hazard reduction by habitats at each location. Model results were integrated with MD DNR’s Community Flood Risk Areas (March, 2016) in order to highlight areas where hazard reduction by habitats is most likely to benefit at-risk coastal communities. This dataset was produced under award number NA13NOS4190136 from the Office of Ocean and Coastal Resource Management (OCRM), National Oceanic and Atmospheric Administration (NOAA) through the Maryland Department of Natural Resources Chesapeake and Coastal Services (CCS). The statements, finding and recommendations are those of the authors and do not necessarily reflect the views of NOAA or the U.S. Department of Commerce. The Natural Capital Project (NatCap), CCS and The Nature Conservancy (TNC) all contributed to the production of this dataset.

Organization: State of Maryland
Classification of Instructional Program (CIP) codes with STEM and High Demand indicators

This table contains records that represent Classification of Instructional Program (CIP) codes (from https://nces.ed.gov/) with Science-Technology-Engineering-Mathematics (STEM) designations (from  https://www.ice.gov/sevis/schools) and high demand status (from https://esd.wa.gov/labormarketinfo/learn-about-an-occupation#/search). Covers 1999-00 to current academic year.

Tags: cip, stem, superintendent-of-public-instruction
Organization: State of Washington
Connecticut CAMA Data 2022

This dataset contains statewide CAMA information for parcels in the State of Connecticut. This dataset was created by the GIS Office as required by CGS Sec. 4d-90-92. This dataset is a result of the 2022 data collection effort, which included collecting CAMA data from all municipalities via the Councils of Government.

Tags: ct-cama, ct-cama-2022, ct-gis-office
Organization: State of Connecticut
Connecticut CAMA Data 2023

This dataset contains statewide CAMA information for parcels in the State of Connecticut. This dataset was created by the GIS Office as required by CGS Sec. 4d-90-92. This dataset is a result of the 2023 data collection effort, which included collecting CAMA data from all municipalities via the Councils of Government.

Tags: ct-cama, ct-cama-2023, ct-gis-office
Organization: State of Connecticut
Connecticut School Construction Grants Program

The Office of Grants Administration at the Department of Administrative Services (DAS) is responsible for administering the school construction grant program. The Office of Grants Administration actively serves the 169 Connecticut municipalities, 17 Regional School Districts, and six Regional Educational Service Centers (RESCs).
This page provides information about school construction grants, including the approved grant amounts by school district, the grant amount paid to date, and the grant amount remaining that may be reimbursed, if eligible.

Tags: school-construction-grants
Organization: State of Connecticut
Infrastructure Investment and Jobs Act (IIJA)/Bipartisan Infrastructure Law (BIL) Project Data

The Bipartisan Infrastructure Law (BIL) is the largest long-term investment in our infrastructure in nearly a century. Signed into law by President Joe Biden on Nov. 15, 2021, this historic act will make life better for millions of Connecticut residents and create economic growth. To date, Connecticut has received $6.4 billion in Bipartisan Infrastructure Law (BIL) funding with over 167 specific projects identified for funding. Many more projects will be added in the coming months, as funding opportunities become grant awards and as formula funds become specific projects. By reaching communities across Connecticut – including rural communities and historically underserved populations – the law makes critical investments that will improve the lives of Connecticut residents and position the state for success.

Tags: bil, bipartisan-infrastructure-law, ctbilt, iija, infrastructure, infrastructure-investment-and-jobs-act
Organization: State of Connecticut
Lobbyist Communicators 2025-2026

Lobbyist is any person who either expends or agrees to expend, or receives or agrees to receive, $3,000 or more in a calendar year to communicate directly or to solicit others to communicate with any public official or their staff in the legislative or executive branch, or in a quasi-public agency, in an effort to influence legislative or administrative action. General Statutes §§ 1-91 (11) and (12).

Tags: lobbying, lobbyist
Organization: State of Connecticut
Utility Use and Cost Data for Executive Branch Agencies

This dataset summarizes the utility use and expenditures data for FY19 through FY24 for Executive Branch agencies. 

The data was pulled from the state's utility tracking system, EnergyCAP, on October 17, 2025, with the exception of the waste disposal data, which was pulled from Core-CT on August 2, 2025, the state's human resource management and financials system.

The data below may be incomplete and will be updated with more current data as it becomes available.

Tags: energycap, eo-1, eo-21-3, greenergov-ct, lead-by-example, sustainability, utility-use-and-cost
Organization: State of Connecticut
City Jobs Requisition Requests

This dataset reflects requisitions submitted to the Civil Service Department for both unclassified and classified positions. Classified positions are hired within the civil service system; unclassified positions are appointed. A requisition is the electronic document authorizing a new hire, promotion or other personnel transaction. Requisition data included here is for promotions and new hires submitted since January of 2018. Data is updated on a monthly basis.

Tags: city-jobs, civil-service, open-positions, reqs, requisitions
Organization: City of New Orleans
City Job Applications Submitted

This dataset reflects applications submitted to the Civil Service Department for classified positions. Application data included here is for promotions and new hires submitted since January of 2018. Contains official City position name and date of each single application by a candidate. This dataset includes data for positions for which the screening of applications has been delegated to the Sewerage and Water Board. Cannot be connected to requisitions by any unique ID. Data is updated on a monthly basis.

Tags: applications, city-jobs, civil-service, classified, hiring, personnel
Organization: City of New Orleans
2.08 Treatment Court Satisfaction (summary)

<div>Tempe Municipal Court continuously assesses its Treatment Court programs, gathering feedback through participant surveys for improvement and enhancing participant success rates.</div><div><br /></div><div>The Mental Health Court, a collaborative effort among the judge, prosecutor, defense attorney, and treatment team, addresses the unique needs of participants with mental illness and developmental disabilities. It deals with pending charges and life situations, providing individualized treatment to reduce reoffending and improve participants' quality of life.</div><div><br /></div><div>The East Valley Regional Veterans Court, involving Chandler, Carefree-Cave Creek, Fountain Hills, Gilbert, Paradise Valley, Scottsdale, and Tempe Municipal Courts, aims to improve the quality of life for Arizona Veterans. A collaborative effort addresses pending charges and life situations, expediting access to Veteran-specific resources and ensuring Veterans meet obligations through tailored plans. Treatment is conducted through the United States Department of Veterans Affairs and Social Services agencies.</div><div><br /></div><div>The performance measure dashboard is available at <a href='https://strong-community-connections-tempegov.hub.arcgis.com/pages/treatment-court-satisfaction' target='_blank' rel='nofollow ugc noopener noreferrer'>2.08 Treatment Court Satisfaction</a>.</div><div><br /></div><div><b>Additional Information</b></div><div>Source: Participant Survey</div><div>Contact: Marcos Romero</div><div>Contact E-Mail: Marcos_Romero@tempe.gov</div><div>Data Source Type: Excel</div><div>Preparation Method: Survey administered, results manually compiled</div><div>Publish Frequency: Monthly</div><div>Publish Method: Manual</div><div><a href='https://gis.tempe.gov/design/data-dictionary/2.08%20Treatment%20Court%20Satisfaction%20(summary)/' target='_blank' rel='nofollow ugc noopener noreferrer'>Data Dictionary</a><br /></div>

Tags: evrvc, mental-health-court, mhc, rvc, specialty-court, treatment-court, treatment-court-satisfaction-pm-2-08, veterans-court
Organization: City of Tempe
2.08 Treatment Court Satisfaction (detail)

<div>Tempe Municipal Court continuously assesses its Treatment Court programs, gathering feedback through participant surveys for improvement and enhancing participant success rates. </div><div><br /></div><div>The Mental Health Court, a collaborative effort among the judge, prosecutor, defense attorney, and treatment team, addresses the unique needs of participants with mental illness and developmental disabilities. It deals with pending charges and life situations, providing individualized treatment to reduce reoffending and improve participants' quality of life. </div><div><br /></div><div>The East Valley Regional Veterans Court, involving Chandler, Carefree-Cave Creek, Fountain Hills, Gilbert, Paradise Valley, Scottsdale, and Tempe Municipal Courts, aims to improve the quality of life for Arizona Veterans. A collaborative effort addresses pending charges and life situations, expediting access to Veteran-specific resources and ensuring Veterans meet obligations through tailored plans. Treatment is conducted through the United States Department of Veterans Affairs and Social Services agencies.</div><div><br /></div><div><b>Additional Information:</b></div><div><br /></div><div>Primary Contact: Marcos Romero<br />Contact Email: Marcos_Romero@tempe.gov</div><div>Data Source: Paper handout and online survey</div><div>Data Source Type: Excel</div><div>Preparation Method: Survey provided participants in electronic and paper-form at the completion of the program</div><div>Publish Method: Manual</div><div>Publish Frequency: Monthly</div><div><a href='https://gis.tempe.gov/design/data-dictionary/2.08%20Treatment%20Court%20Satisfaction%20(detail)/' target='_blank' rel='nofollow ugc noopener noreferrer'>Data Dictionary</a><br /></div><div><br /></div>

Tags: evrvc, mental-health-court, mhc, participants, rvc, specialty-court, treatment-court, veterans-court
Organization: City of Tempe
F00754: NOS Hydrographic Survey , 2018-09-18

The National Oceanic and Atmospheric Administration (NOAA) has the statutory mandate to collect hydrographic data in support of nautical chart compilation for safe navigation and to provide background data for engineers, scientific, and other commercial and industrial activities. Hydrographic survey data primarily consist of water depths, but may also include features (e.g. rocks, wrecks), navigation aids, shoreline identification, and bottom type information.
							NOAA is responsible for archiving and distributing the source data as described in this metadata record.

Tags: acoustic sounders, approaches to morehead city, bathymetry, bathymetry/seafloor topography, continent, doc/noaa/nesdis/ncei, doc/noaa/nesdis/ngdc, earth remote sensing instruments, earth science, global positioning system/inertial measurement unit, gps, gps receivers, gps/imu, hydrographic surveys for selected locations within the united states (hydro_bathy_2006), in situ ocean-based platforms, in situ/laboratory instruments, marine sediments, mbes, msbs, multibeam mapping system, multibeam swath bathymetry system, national centers for environmental information, national geophysical data center, nesdis, noaa, north america, north carolina, ocean, oceans, passive remote sensing, positioning/navigation, profilers/sounders, seafloor topography, sediment composition, ships, sonar, sound navigation and ranging, u.s. department of commerce, united states of america, water depth
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
Deep Space Climate Observatory (DSCOVR)

The Deep Space Climate ObserVatoRy (DSCOVR) satellite is a NOAA operated asset at the first Lagrange (L1) point. The primary space weather instrument is the PlasMag suite.  PlasMag includes a fluxgate magnetometer (MAG) that measures the local magnetic field, and a Faraday Cup (FC) that measures the solar wind bulk properties (wind speed, density and temperature). The PlasMag solar wind data are essential inputs for the forecasts and nowcasts provided to SWPC customers. The PlasMag data are also available to scientists for sensor cal/val and for research purposes.
	DSCOVR was launched on Feb. 11, 2015, so all data present in the Archive from earlier dates are data used for ground testing, and do not represent the space environment. DSCOVR became operational on July 27, 2016.
	End Of Life (EOL) is anticipated to be December 2019. NCEI plans to receive data until EOL, and will continue to archive the data in accordance with Data Center policies.

Tags: deep space climate observatory, doc/noaa/nesdis/ncei, doc/noaa/nesdis/ngdc, dscovr, earth science, fluxgate magnetometers, icsu-wds, international council for science - world data system, magnetic field/electric field instruments, national centers for environmental information, national geophysical data center, nesdis, noaa, noaa - space weather program, particle detectors, solar/space observation satellites, solar/space observing instruments, space, sun-earth interactions, u.s. department of commerce
Organization: National Oceanic and Atmospheric Administration, Department of Commerce
GOES-R Series Solar Ultraviolet Imager (SUVI) Level 2 Products

These SUVI Level 2 (L2) data are designed for use by the NOAA-NWS Space Weather Forecast Office and include several different products: composite images, thematic maps, bright regions, flare locations, coronal hole boundaries, coronal hole images, and fixed and running difference images. The SUVI Composite Image product is a weight average using the short and long exposures found in the SUVI Level-1b product to produce a high-dynamic range image. SUVI Fixed Difference images use a set "reference" image to produce difference images with respect to a particular event. SUVI Running Difference images use the most recent data to produce difference images showing short-term changes in the solar corona. The SUVI Thematic Map is a "mask" image that shows the automatically classified solar features. Composite images, as well as fixed and running difference images, are available in each of SUVI's six wavelengths. SUVI image products are available as FITS files. The SUVI Coronal Hole Boundary product contains lists of the boundary pixels in both image and heliographic coordinates for all coronal holes identified in the SUVI Thematic Map. The SUVI Bright Region Report uses the SUVI Thematic Map and SUVI Composite Image products to provide statistics on identified bright regions on the Sun. The SUVI Flare Location Report provides locations and statistics on flares identified by either the SUVI Thematic Map or the XRS Event Detection products. These products, Coronal Hole Boundaries, Bright Region Report, and Flare Location Report, are tabular data provided in netCDF-4 format.

Tags: corona, corona holes, coronal mass ejections, earth magnetic field, earth science, geostationary operational environmental satellites, goes, goes (geostationary operational environmental satellite), magnetosphere (other), solar active regions, solar activity, solar flares, solar imagery, solar prominences/solar filaments, solar ultraviolet emissions, solar/space observation satellites, solar/space observing instruments, space, spectral/engineering, sun-earth interactions, sunspots, suvi-goesr, ultraviolet instruments, ultraviolet radiance, ultraviolet wavelengths
Organization: National Oceanic and Atmospheric Administration, Department of Commerce