AndreaBozzo/ceres-open-data-index huggingface dataset:
NOAA-20 VIIRS Global Binned Diffuse Attenuation Coefficient for Downwelling Irradiance (KD) - Near Real Time (NRT) Data, version R2022.0

The Ocean Biology DAAC produces near real-time (quicklook) products using the best-available combination of ancillary data from meteorological and ozone data. As such, the inputs and the calibration used are less than optimal. Quicklook products provide a snapshot of the data during a short time period within a single orbit.

Tags: earth-science, ocean-optics, oceans
Organization: National Aeronautics and Space Administration
ROSETTA-ORBITER 67P ROSINA 5 EXT3 V1.0

This data set contains CODMAC
level 5 science data acquired by the DFMS and RTOF ROSINA sensors
between 2016-06-28 and 2016-06-30 during the Extension phase 3 of
the Rosetta mission at the comet 67P/CG.

Tags: 67p-churyumov-gerasimenko-1-1969-r1, international-rosetta-mission
Organization: National Aeronautics and Space Administration
GPM Ground Validation Doppler on Wheels (DOW) OLYMPEX V2

The GPM Ground Validation Doppler on Wheels (DOW) OLYMPEX V2 dataset was obtained by a dual-polarization and dual-frequency X-band mobile radar operated by the Center for Severe Weather Research (CSWR) during the Olympic Mountain Experiment (OLYMPEX) campaign. The DOW was deployed in the Chehalis Valley for the OLYMPEX field campaign with the goal of obtaining radar reflectivity and Doppler velocity observations in order to better understand the orographic enhancement of precipitation during frontal passages over mountain ranges. The DOW radar uses two 250 kW transmitters with a measurement range of roughly 60 km. These data are available in CFradial netCDF-4 format from November 6, 2015 through January 15, 2016.

Tags: earth-science, radar, spectral-engineering
Organization: National Aeronautics and Space Administration
ROSETTA-ORBITER 67P RSI 1/2/3
                                     COMET ESCORT 1 0529 V1.0

This is a Rosetta Radio Science data set, collected during the COMET ESCORT 1 phase 2014-11-20 to 2015-03-10. It is a Global Gravity measurement at the comet 67P and covers the time 2014-12-31T00:38:20.000 to 2014-12-31T03:41:26.500.

Tags: 67p-churyumov-gerasimenko-1-1969-r1, international-rosetta-mission
Organization: National Aeronautics and Space Administration
VL1 MARS METEOROLOGY DATA RESAMPLED DATA BINNED-P-T-V V1.0

This data set contains binned and splined data obtained from the Viking Meteorology Instrument System (VMIS) through portions of the Viking Lander 1 mission. The data set consists of mean values of pressure, temperature, and wind speed (zonal and meridional) calculated for 25 bins of equal duration per day. The data are presented on a bin by bin basis for Lander 1 sol (Mars solar day after landing) 1-350, with no data existing between sols 117 and 133. Failure of the wind direction quadrant sensor on Lander 1 sol 45 required development of data recovery techniques to produce wind direction information for periods after the failure. For details on the data recovery techniques used to produce this data set, see MURPHY_1986. Another data set is available for an extensive period of Lander 2 observations and the Lander 1 observations made prior to the sol 45 failure VL1/VL2-M-MET-4-BINNED-P-T-V-V1.0.

Tags: mars, viking
Organization: National Aeronautics and Space Administration
OrbView-2 SeaWiFS Global Mapped Remote-Sensing Reflectance (RRS) Data, version R2022.0

The SeaWiFS instrument was launched by Orbital Sciences Corporation on the OrbView-2 (a.k.a. SeaStar) satellite in August 1997, and collected data from September 1997 until the end of mission in December 2010. SeaWiFS had 8 spectral bands from 412 to 865 nm. It collected global data at 4 km resolution, and local data (limited onboard storage and direct broadcast) at 1 km. The mission and sensor were optimized for ocean color measurements, with a local noon (descending) equator crossing time orbit, fore-and-aft tilt capability, full dynamic range, and low polarization sensitivity.

Tags: aerosols, atmosphere, earth-science, ocean-optics, oceans
Organization: National Aeronautics and Space Administration
Navigation Facilities

The Navigation Facilities dataset is periodically updated by the United States Army Corp of Engineers (USACE) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The data includes location (latitude, longitude, waterway, mile, and bank); operations (name, owner, operator, purpose, handling equipment, rates, and details of open-and-covered storage facilities); and type of construction (length of berthing space for vessels and/or barges, depth, deck elevation, and details of rail-and-highway access). Additional attributes included in the data are the unique navigation-unit identifier, official name, facility type, United Nations Location Code, a location description, stress address, city, state, zip code, county, congressional district, TOWS link location identifiers, port name, waterway name, mile, bank, and service-initiated dates. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529017

Tags: atlas, database, dock, economy, facilities, geospatial, inland, location, marine, maritime, national, national geospatial data asset, national transportation atlas database, navigation, navigational, ngda, ngdaid152, ntad, point, port, structures, transportation, transportation theme, usa, vector, water
Organization: Department of Transportation
VG1 JUP MAG RESAMPLED HELIOGRAPHIC
                                       (RTN) COORDS 48.0SEC V1.0

This data set includes data from the Low Field Magnetometer (LFM) during the inbound Jupiter encounter beginning in the solar wind and continuing until at least the first magnetopause crossing. The magnetometer are given in Heliographic coordinates and the data have been averaged from the 60 ms instrument sample rate to a 48 second resampled rate. The data set consists of the following columns: 1) UT of the sample in the format yyyy-mm-ddThh:mm:ss.sssZ, 2) continuous time (decimal seconds since 1966-01-01T00:00:00.000), 3-5) spacecraft clock (m65536, mod60, fds-line), 6) magnetometer id (1 = LFM, 2 = HFM), 7) Br (radial, Sun to spacecraft, B-field component), 8) Bt (azimuthal B-field component, positive in the direction of planetary orbital motion), 9) Bn (North/South B-field component, positive northward), 10) Bmag (magnitude of the averaged components), 11) avg_Bmag (average of the magnetic field magnitudes), 12) delta (latitude = arcsin(Bn/Bmag)), 13) lambda (longitude = 180. - atan(Bt/Br)), 14-16) rms vector, 17) npts (number of points in average), 18) data flag. - a flag value that indicates either software error or spacecraft hardware interference reduced confidence in this record (flag value of 1 is bad , 0 is good or unchecked). All magnetic field observations are measured in nanoTesla. All of the magnetic field data are calibrated (see the instrument calibration description for more details).

Tags: jupiter, voyager
Organization: National Aeronautics and Space Administration
North American Rail Network Lines

The North American Rail Network (NARN) Rail Lines dataset was created in 2016 and was updated on January 29, 2026 from the Federal Railroad Administration (FRA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The NARN Rail Lines dataset is a database that provides ownership, trackage rights, type, passenger, STRACNET, andÂ  geographic reference for North America's railway system at 1:24,000 or better within the United States. The data set covers all 50 States, the District of Columbia, Mexico, and Canada. The RROWNER1â3 fields identify the parties responsible for operation, maintenance, and/or ownership to the railroad. It includes the railroad dispatcher (operational control) identifying the specific railroad entity managing the movement of trains over that segment, the maintenance responsibility identifying who is legally obligated to maintain the rail line, and/or the property owner (land and right-of-way) identifying the entity that owns the underlying land. While many railroads own their right-of-way (ROW) in "fee simple", others operate on land owned by a third party. The same entity may fulfill one or more of these roles on the same line.Â  A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1528950

Tags: atlas, database, line, linear rail, lines, narn, national, national geospatial data asset, national transportation atlas database, network, ngda, ngdaid145, north america, ntad, transportation, transportation theme, usa, vector
Organization: Department of Transportation
Rail Yards

The North American Rail Network (NARN) Rail Yards dataset was created in 2024 and was updated on January 29, 2026 from the Federal Railroad Administration (FRA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This Rail Yards layer represents and is derived from where the North American Rail Network (NARN) Lines layer as aggregated by type of track designated as yards.  A rail yard is an area consisting of a network of tracks where trains are stored and/or maintained.The NARN Rail Lines dataset is a database that provides ownership, trackage rights, type, passenger, STRACNET, and geographic reference for North America's railway system at 1:24,000 or better within the United States. The data set covers all 50 States, the District of Columbia, Mexico, and Canada. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1528005

Tags: atlas, database, line, linear rail, lines, narn, national, national transportation atlas database, network, north american, ntad, transportation, usa, vector, yards
Organization: Department of Transportation
North American Rail Network Nodes

The North American Rail Network (NARN) Rail Nodes dataset was created in 2016 and was updated on January 29, 2026 from the Federal Railroad Administration (FRA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The NARN Rail Nodes dataset is a database of North America's railway system at 1:24,000 or better within the United States. The data set covers all 50 States, the District of Columbia, Mexico, and Canada. The dataset holds topology of the network and provides geographic location information. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529070

Tags: atlas, database, narn, national, national geospatial data asset, national transportation atlas database, network, ngda, ngdaid146, nodes, north american, ntad, point, rail, transportation, transportation theme, usa, vector
Organization: Department of Transportation
National Waterway Network Nodes

The National Waterway Network Nodes dataset is periodically updated by the United States Army Corp of Engineers (USACE) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The National Waterway Network (NWN) is a geographic database of navigable waterways and channels in and around the United States, for analytical studies of navigation performance, for compiling commodity flow statistics, and for mapping purposes. The NWN is comprised of a link database and a node database. Links are line strings, which consist of beginning and end points (nodes) with intermediate vertices (shape points). Links represent either actual shipping lanes (i.e., channels, Intracoastal Waterways, sea lanes, rivers) or serve as representative paths in open water (where no defined shipping paths exist). Nodes may represent physical entities such as river confluence's, ports/facilities, and intermodal terminals, USACE nodes, or may be inserted for analytical purposes (i.e., to facilitate routing). A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529054

Tags: atlas, database, geospatial, inland, inland waters, marine, maritime, national, national geospatial data asset, national transportation atlas database, navigable, ngda, ngdaid154, nodes, ntad, oceans, point, transportation, transportation theme, usa, vector, water, waterway
Organization: Department of Transportation
National Waterway Network Lines

The National Waterway Network Lines dataset is periodically updated by the United States Army Corp of Engineers (USACE) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The National Waterway Network (NWN) is a geographic database of navigable waterways and channels in and around the United States, for analytical studies of navigation performance, for compiling commodity flow statistics, and for mapping purposes. The NWN is comprised of a link database and a node database. Links are line strings, which consist of beginning and end points (nodes) with intermediate vertices (shape points). Links represent either actual shipping lanes (i.e., channels, Intracoastal Waterways, sea lanes, rivers) or serve as representative paths in open water (where no defined shipping paths exist). Nodes may represent physical entities such as river confluence's, ports/facilities, and intermodal terminals, USACE nodes, or may be inserted for analytical purposes (i.e., to facilitate routing). A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529053

Tags: atlas, database, geospatial, inland waters, line, linear marine, maritime, national, national geospatial data asset, national transportation atlas database, navigable, ngda, ngdaid153, ntad, oceans, transportation, transportation theme, usa, vector, water, waterway
Organization: Department of Transportation
Street Tree Archive

<div style='text-align:Left;'><div><div><p><span>DDOT's Urban Forestry Division (UFD) manages ~180,000 public trees and this data set shows annual changes in species composition and tree health from 2014 to present. Visit trees.dc.gov for more information.</span></p></div></div></div>

Tags: dc, ddot, division, forestry, street, tree, ufd, urban, washington, washington-dc
Organization: District of Columbia
Great Streets Grantees

<div style='text-align:Left;'><div><div><p><span>Grant and grantee information at https://greatstreets.dc.gov/ and https://greatstreets.dc.gov/service/grantees-corner. In 2006, Great Streets began as a three-prong, commercial revitalization initiative to transform emerging corridors throughout the District of Columbia into thriving and inviting neighborhood centers. Led by the Office of the Deputy Mayor for Planning and Economic Development (DMPED) in conjunction with the Office of Planning (OP) and the District Department of Transportation (DDOT), Great Streets has grown into a multi-year, multi-agency program that utilizes public actions and resources to leverage private investment in retail, office space, housing, and cultural facilities across the District. The Government of the District of Columbia through the Office of the Deputy Mayor for Planning and Economic Development (DMPED) administers the Great Streets Retail Small Business Reimbursement Grants, which are competitive grants of up to $50,000 for qualified small business owners who wish to improve their place of business. The purpose of the grant program is to support existing small businesses, attract new businesses, increase the District's tax base, create new job opportunities for District residents, and transform emerging commercial corridors into thriving and inviting neighborhood centers. If you would like to be added to the Great Streets email list to receive updates about small business opportunities in the District of Columbia, please email us at greatstreets@dc.gov.</span></p></div></div></div>

Tags: business, dc, district-of-columbia, dmped, economic, grants, great-streets, incentive, washington-dc
Organization: District of Columbia
U.S. Wind Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Wind Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NREL's reVX setbacks tool and therefore does not contain any of the state-level regulations.

**NOTE**: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases.

This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5733: see the "U.S. Wind Siting Regulation and Zoning Ordinances 2022" link below.

INFRA-COMPASS version used for collection: v0.8.2
LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano, GPT-4o mini

Tags: ai, analysis, citations, compass, energy, energy-analysis, exclusion, infra-compass, land-based-wind, llm, local, machine-readable, ordinances, power, regulatory-constraints, siting, siting-lab, sitinglab, wind
Organization: Department of Energy
U.S. Solar Siting Regulation and Zoning Ordinances (2022)

A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled based on a locality-by-locality review zoning ordinances after completing an initial review of scholarly legal articles. The citations for each ordinance are included in the Solar Ordinances spreadsheet resource below.

**Note: an updated version of this dataset can be found at the "U.S. Solar Siting Regulation and Zoning Ordinances (2025)" link below.**

Tags: energy, exclusion, incentives, law, legal, legislation, local, ordinances, policy, power, pv, regulations, regulatory-constraint, siting, sitinglab, solar, solar-pv, united-states
Organization: Department of Energy
U.S. Solar Siting Regulation and Zoning Ordinances (2025)

A machine readable collection of documented solar siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled using the Infrastructure Continuous Ordinance Mapping for Planning and Siting Systems (INFRA-COMPASS) tool, which leverages Large Language Models (LLMs) to automate the collection of local codes and ordinances applicable to energy infrastructure. URLs for the ordinance source documents are included in the Solar Ordinances spreadsheet. The GeoPackage file included below contains the jurisdiction shapes for each ordinance. Note that the GeoPackage file is formatted for ingestion by NLR's reVX setbacks tool and therefore does not contain any of the state-level regulations.

**NOTE**: This data was collected with the help of generative AI. The Large Language Models used for this effort make mistakes. Always validate the data for critical use cases.

This data is an update to a previously developed database of wind ordinances found in OEDI Submission 5734: see the "U.S. Solar Siting Regulation and Zoning Ordinances 2022" link below.

INFRA-COMPASS version used for collection: v0.11.3
LLMs used for collection: GPT-4.1, GPT-4.1 mini, GPT-4.1 nano

Tags: ai, analysis, citations, compass, energy, energy-analysis, exclusion, incentives, infra-compass, land-based-solar, law, legal, llm, local, machine-readable, ordinances, policy, power, pv, regulatory-constraint, regulatory-constraints, siting, siting-lab, sitinglab, solar, solar-pv
Organization: Department of Energy
Carpooling Slug Routes

<div style='text-align:Left;'><div><div><p><span>This layer shows slugging locations (pick-up and drop-off points) for casual carpooling. The data was originally obtained from Sluglines.com.</span></p></div></div></div>

Tags: carpooling, commuter, dc, ddot, district-of-columbia, slugline, transportation, washington-dc
Organization: District of Columbia
Nonattainment Area - 1 hr Ozone (1979 Standard-Revoked)

The Nonattainment Area - 1 hr Ozone (1979) dataset was updated on January 31, 2026 by the Environmental Protection Agency (EPA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This dataset provides detailed information about designations, classifications and the status of the nonattainment areas at the time of the 1-Hour Ozone (1979) National Ambient Air Quality Standards (NAAQS) revocation. On June 15, 2005 the 1-Hour Ozone NAAQS was revoked for all areas except the 8-Hour Ozone nonattainment Early Action Compact (EAC) areas. These data are updated weekly from an OAQPS internal database. However, that does not necessarily mean the data have changed. For more information about this nonattainment area, please see the website https://www.epa.gov/green-book/green-book-1-hour-ozone-1979-area-information-naaqs-revoked. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529058

Tags: 1 hour, 1 hr, 1 hr ozone, 1979, air, air quality, area, atlas, attainment, boundary, criteria pollutants, database, designations, environment, environmental, epa, naa, naaqs, national, national transportation atlas database, non, nonattainment, ntad, oar-oaqps, ozone, planning, pollutant, pollutants, polygon, standards, transportation, usa, vector
Organization: Department of Transportation
Nonattainment Area - Lead (Pb - 2008 Standard)

The Nonattainment Area - Lead (Pb-2008) dataset was updated on January 31, 2026 by the Environmental Protection Agency (EPA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). This dataset provides detailed information about areas identified in the U.S. where lead levels have not met the National Ambient Air Quality Standards (NAAQS) established in 2008 for lead and have been designated "nonattainment areas (NAA)". These data are weekly from an OAQPS internal database. However, that does not necessarily mean the data have changed. For more information about this non-attainment area, please see the website https://www.epa.gov/green-book/green-book-lead-2008-area-information. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529063

Tags: 2008, air, air quality, area, atlas, attainment, boundary, criteria pollutants, database, designations, environment, environmental, epa, lead, naa, naaqs, national, national transportation atlas database, non, nonattainment, ntad, oar-oaqps, pb, planning, pollutant, pollutants, polygon, standards, transportation, usa, vector
Organization: Department of Transportation