cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25921/8fmc-1q11
title: Ocean velocity, and biophysical measurements - temperature, salinity, oxygen, turbidity, chlorophyll-a, and other variables - taken by CTD at eight mooring sites in the Cross Sound area in Southeast Alaska, 2011-03-15 to 2014-11-04 (NCEI Accession 0292553)

description: These time-series data sets consist of Current Profiler observations and data from biophysical moorings at 8 locations in Southeast Alaska near Cross Sound: CS1, CS2, CS3, CS11 and IP2 (ADCP and WCP locations); CS12, CS13 and IP1 (biophysical locations). Data were collected as part of the North Pacific Research Board (NPRB) Gulf of Alaska Integrated Ecosystem Research Program (GOA IERP) lower-trophic-level research effort. Variables include current speed and direction, calculated current components U and V, temperature, conductivity, salinity, pressure, water depth, oxygen concentration, calculated oxygen percent saturation, turbidity, raw chlorophyll fluorescence and chlorophyll a. Instrumentation included Aanderaa RCM-9 current meter, Teledyne RDI Workhorse Sentinel ADCP (WCP), Teledyne-RDI Long-Ranger 75khz ADCP (LRCP), SeaBird SBE-37 and SBE-39 profilers, WetLabs EcoFluorometers and an Satlantic In Situ Ultraviolet Spectrophotometer (ISUS) nitrate sensor. Various instruments were mounted at various depths in the water column at each mooring site. The GOA IERP had two field years including this set from 2011 and another in 2013. The NOAA/PMEL EcoFOCI program deployed moored instruments as part of the (NPRB) Gulf of Alaska IERP (2010-14).

The cruise was funded by the NOAA, Pacific Marine Environmental Laboratory EcoFOCI program and the North Pacific Research Board (NPRB). Instruments were deployed in March, 2011 and recovered in November, 2011 from F/V Harmony (HA11-01) and NOAA Ship Oscar Dyson (DY1309, leg 2) respectively. One exception was the ADCP mooring IP-2a near Icy Point just north of Cross Sound that failed to release on the recovery cruise in 2011, and was finally recovered in 2014, returning an extended data set due to longevity of instrument battery packs. Deployment and recovery operations on these cruise were managed by EcoFOCI personnel from NOAA/PMEL. Mooring time series data were processed at NOAA/PMEL/EcoFOCI using standard techniques. Time is recorded as UTC. Data contacts: Phyllis Stabeno, Shaun Bell, Ryan McCabe, Peggy Sullivan.

Measurements were conducted with participation from the National Oceanic and Atmospheric Administration (NOAA), Pacific Marine Environmental Laboratory (PMEL), Ecosystems and Fisheries-Oceanography Coordinated Investigations (EcoFOCI); University of Washington, Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES); North Pacific Research Board (NPRB). Data are in NetCDF.
DOI: 10.25921/4qne-j435
title: Ocean velocity, and biophysical measurements (temperature, salinity and others) collected by ADCP and CTD from Mooring Stations in Southeast Alaska, Cross Sound (CS-1), and Chatham Strait (CH-1) by NOAA PMEL EcoFOCI in 2005 (2005-08-11 to 2005-11-29) and 2006 (2006-08-28 to 2007-03-22). Deployed and Recovered from ADF&G research vessel Medeia (NCEI Accession 0292692)

description: These time-series data sets consist of Current Profiler data and biophysical data from moored instruments at 2 locations in Southeast Alaska in 2005 and 2006. A Cross Sound (CS-11) mooring was deployed August through November 2005 at 58.17 N, 136.57 W. In 2006 moorings were deployed in August at both Cross Sound (CS-11, 58.17 N, 136.57 W) and Chatham Strait (CH-1, 56.50 N, 134.39 W), and recovered in March of 2007. Data from these moored instruments include current speed and direction, calculated current components U and V, temperature, conductivity, salinity, pressure, water depth and calculated Sigma-T values. Instrumentation included Teledyne-RDI Long-Ranger 75khz ADCP (LRCP) and SeaBird SBE-37 (Microcat).

Instruments were deployed and recovered from the Alaska Department of Fish and Game ship R/V Medeia. The cruise was funded by NOAA, EcoFOCI (Ecosystems & Fisheries-Oceanography Coordinated Investigations) and NPCREP (North Pacific Climate Regimes and Ecosystem Productivity) programs. Operations on these cruises were managed by EcoFOCI personnel from NOAA/PMEL. Mooring time series data were processed at PMEL using standard techniques. Time is recorded as UTC.

Data contacts: Phyllis Stabeno, Shaun Bell, Ryan McCabe, Peggy Sullivan.

Collected with participation from National Oceanic and Atmospheric Administration (NOAA), Pacific Marine Environmental Laboratory (PMEL), Ecosystems and Fisheries-Oceanography Coordinated Investigations (EcoFOCI); University of Washington, Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES). Data are in NetCDF. Longitudes are in degW.
DOI: 10.25921/0kh1-x444
title: Coral Reef Ecosystem and Larval Research Consisting Of Biologic Data from the Nancy Foster in Caribbean Sea and Gulf of Mexico from April 11, 2015 to June 24, 2018 (NCEI Accession 0293057)

description: National Oceanic and Atmospheric Administration (NOAA) scientists from the Southeast Fisheries Science Center (SEFSC) and Atlantic Oceanographic and Meteorological Laboratory (AOML), working with scientists from the University of the Virgin Islands (UVI) in St. Thomas conducted a multi-year interdisciplinary research project which was a continuation of the 2007-2011 project using the NOAA Ship Nancy Foster to conduct biological and physical oceanographic surveys of the Virgin Island's (VI) bank ecosystems and surrounding regional waters as well as areas around Jamaica, Cuba and the Gulf of Mexico. The long-term sustainability of fisheries in the VI and surrounding regions is dependent on a comprehensive understanding of regional spawning aggregations, larval transport, and overall larval recruitment in the study area.

This survey sampled water properties, currents, and dispersal and transport of settlement-stage larvae in the VI and neighboring regions. Data in this archival package includes: processed larval fish data collected from the various net tows (BONGO, MOCNESS, etc.) , processed data from all conductivity, temperature, depth (CTD) casts, processed data from all lowered acoustic Doppler profiler (LADCP) casts, processed hull-mounted acoustic Doppler current profiler (SADCP), processed sea surface, flow-through data collected with the ship's thermosalinograph (TSG) and fluorometer collected aboard NOAA Ship Nancy Foster during cruises NF-15-02, NF-15-03, NF-16-02, NF-16-03, NF-17-03 and NF-18-03 from 2015-04-11 to 2018-06-24.
DOI: 10.25921/kwhk-bw94
title: NCCOS Mapping: Bathymetric Lidar Waveform Metrics for Saipan, The Commonwealth of the Northern Mariana Islands (CNMI), 2019-07-11 to 2019-07-31 (NCEI Accession 0294340)

description: This data package contains bathymetric light detection and ranging (lidar) Hawkeye-4X waveforms metrics (LWFM) for 0 to 50 meter depths around the island of Saipan, Commonwealth of the Northern Mariana Islands (CNMI). Bathymetric lidar waveforms depict the amount of laser light returned from the seafloor recorded during each laser pulse. Typically, only the leading edge of the seafloor return is used to calculate bottom depth. However, the shape of the seafloor return also contains novel information about the physical structure and biological cover on the seafloor (Collin et al. 2011, Wilson et al. 2019). To extract this information, the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) partnered with Oregon State University (OSU), NOAA Office for Coastal Management (OCM), Woolpert and Hexagon Leica to develop software to export, process, normalize and rasterize 16 LWFM describing the shape of the seafloor return (Jung et al. 2024; Collin et al. 2011; Parrish et al. 2014; Kashani et al. 2015; Kogut et al. 2022). The resulting LWFM rasters were used to predict the distribution of key coral reef taxa and habitats west of Saipan (Costa et al. 2024). This effort marks one of the few studies that have used LWFM to predict tropical coral reef habitats to date. These processing workflows and associated software will also make LWFM creation easier and more routine for future Hawkeye-4X lidar collections by NOAA and its partners. This project was funded by NOAA’s Coral Reef Conservation Program (CRCP), and leverages significant investments made by NOAA NCCOS, NOAA National Geodetic Survey, NOAA Office for Coastal Management, and the U.S. Geological Survey in the region.
DOI: 10.25921/1yqg-aq95
title: Water temperature, salinity, trawl catch and specimen data collected by CTD and other instruments from the fishing vessel Northwest Explorer in the Bering Sea from 2019-08-30 to 2023-09-16 (NCEI Accession 0294341)

description: Data set containing all data collected during Northern Bering Sea Surface Trawl Survey 2019-2023. Dataset includes sampling event data, CTD data, trawl catch, and specimen measurement list. Data are in CSV format.
DOI: 10.25921/35c4-7k73
title: U.S. Virgin Islands Coral Reef Resilience Prioritization: Coral Reef Resilience in the U.S. Virgin Islands, 2013-01-01 to 2021-07-31 (NCEI Accession 0294911)

description: This dataset includes relative resilience scores for the U.S. Virgin Islands Coral Reef Ecosystem. The score is composed of 18 indicators which were weighted and combined to create the final resilience values. All indicator values are included in this dataset along with the final resilience scores. The information is provided within the National Coral Reef Monitoring Program’s 50m x 50m survey grid.
DOI: 10.25921/rc4f-sb35
title: NCCOS Mapping: Geospatial products of water depth, acoustic backscatter, and ROV data collected from NOAA Ship Nancy Foster in the Tortugas South Ecological Reserve and Florida Keys National Marine Sanctuary from 2020-09-07 to 2020-09-16 (NCEI Accession 0295610)

description: Multibeam bathymetry and acoustic backscatter data collected from NOAA Ship Nancy Foster from 2020-09-07 to 2020-09-16 in the Florida Keys National Marine Sanctuary. This cruise designation was originally scheduled as NF-20-01, but due to rescheduling as a result of COVID-19, the mission was designated as NF-20-08.

Data were collected using a Kongsberg EM2040 multibeam echosounder. Survey depths vary from 41m to 160m in the Dry Tortugas area. Transit data were also collected from Charleston, South Carolina and south along the eastern coast of Florida. Data are available in 2x2, 4x4, and 8x8 meter resolutions.

During the field mission, a Mohawk 18 Remotely Operated Vehicle (ROV), operated by the University of North Carolina Undersea Vehicles Program collected HD photo and ground validation video. Video data is not included with this dataset.
DOI: 10.25921/cdy1-d728
title: NCCOS Competitive Research Program (CRP) Assessment: Future surface water predictions with sea level rise and shoreline adaptation in Santa Monica Bay, California (NCEI Accession 0295695)

description: This dataset contains predictions of surface water depth (m) under 200 cm (2 m or 6.6 ft) of sea level rise and three storm scenarios by 2100. Estimates of associated socioeconomic impacts are also included. These predictions were completed in the area of Santa Monica Bay, California, specifically Venice Beach and Marina Del Rey. The model domain included ten different modeled infrastructure types to better understand the impact of natural and nature-based features (NNBFs) and conventional infrastructure to reduce sea level rise-driven flood hazards.

Sea level rise scenario: 200 cm (2 m or 6.6 ft) by 2100.

Storm scenarios: no storm, annual storm event, 20-year storm event, 100-year storm event.

Modeled infrastructure types: no action (no change from current), targeted dunes, dunes in locations with elevation below 4 m NAVD88, dunes in locations with elevation below 5 m NAVD88, sea wall, sluice gate, sluice gate + targeted dune, sluice gate + dunes in locations with elevation below 4 m NAVD88, sluice gate + dunes in locations with elevation below 5 m NAVD88, sluice gate + sea wall.

The following physical and socio-economic impacts were calculated for each modeled infrastructure type within each storm scenario: flood area, flood volume, total economic damages, residential economic damages, nonresidential economic damages, total displaced population, displaced child population, displaced senior population, displaced minority population, displaced low-income population, low construction cost estimate, high construction cost estimate, benefit-cost ratio based on low construction cost estimate, benefit-cost ratio based on high construction cost estimate.

The file naming convention is a combination of sea level rise height (in cm), the storm scenario, and the modeled infrastructure type. For additional details, please see the data files section.
DOI: 10.25921/qzm2-zg29
title: Satellite-Based Global Land Surface Datasets for Earth System Model Applications (NCEI Accession 0295750)

description: This dataset includes key land surface properties based on various operational satellite measurements (e.g. MODIS, VIIRS and GEDI). They include the land surface type, vegetation clumping index, leaf area index, vegetative canopy height, and green vegetation fraction. Critical processing steps are taken to extend the surface properties for full global coverage, as well as gap-filling. All variables are gridded to universal global latitude/longitude gridded coordinates (-90° - 90° in latitude and 0° - 360° in longitude) with a consistent spatial resolution of 0.01° (~ 1 km). Currently, the dataset is available for a one year period (2020), and extension in time is expected.
DOI: 10.5281/zenodo.16256638
title: A Large-Scale Investigation into the Loss of Pull Request Data on GitHub
DOI: 10.5281/zenodo.17951141
title: A Large-Scale Investigation into the Loss of Pull Request Data on GitHub
DOI: 10.5281/zenodo.17951443
title: Interior-Exterior Contrasts of Concave Hulls Amplify Driving Effect of Climatic factors on Geospatial Animal Migratory Rhythm

description: The file "shp_point" contains the gps points of animals.

The file "concave_hulls" contains the built concave hulls of the migratory animals.

The explanation in the dryad-data.xlsx: year and moth are the monthly date, and numbered from 1 to 73 in the line num. x and y are the projected coordinate, while x1 and y1 are the coordinate under Geographic Coordinate System. pci, tci, and ndvi are the values of the Interior-Exterior contrasts of concave hulls. While _con represent the values of the Interior of concave hulls.
DOI: 10.5281/zenodo.17951444
title: Interior-Exterior Contrasts of Concave Hulls Amplify Driving Effect of Climatic factors on Geospatial Animal Migratory Rhythm

description: The file "shp_point" contains the gps points of animals.

The file "concave_hulls" contains the built concave hulls of the migratory animals.

The explanation in the dryad-data.xlsx: year and moth are the monthly date, and numbered from 1 to 73 in the line num. x and y are the projected coordinate, while x1 and y1 are the coordinate under Geographic Coordinate System. pci, tci, and ndvi are the values of the Interior-Exterior contrasts of concave hulls. While _con represent the values of the Interior of concave hulls.
DOI: 10.15468/dl.5x4a4a
title: Occurrence Download

description: A dataset containing 2000 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Invertebrate Collection of IBIOMAR (CCT CONICET-CENPAT) (CNP-INV)"
 ]
}

 The dataset includes 2000 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054671-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ccqjjg
title: Occurrence Download

description: A dataset containing 2388 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Spain, France, Italy)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Lanius minor"
 ]
}

 The dataset includes 2388 records from 80 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054670-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25921/m615-q735
title: Ocean currents (speed, direction, U, V), and biophysical measurements (temperature, salinity, oxygen, turbidity, chlorophyll a, and other variables) collected from 4 mooring deployments at the NOAA long-term observatory site, M2, in the Southeastern Bering Sea, Alaska, by the EcoFOCI group at NOAA, PMEL, 2017-04-27 to 2018-05-01 (NCEI Accession 0298473)

description: These time-series data sets are from Current Profilers and other instruments on biophysical and ADCP moorings at NOAA Data Observatory "M2" on the southeastern Bering Sea Shelf. Instruments on summer moorings 17bsm-2a and 17bsp-2a (ADCP & biophysical, respectively) were deployed in April, 2017 (NOAA Ship Oscar Dyson DY17-04) and recovered at the end of September, 2017 (NOAA Ship Oscar Dyson, DY17-08). Over-wintering moorings 17bs-2c & 17bsp-2b (biophysical and ADCP, respectively) were deployed on October 2, 2017 and recovered April 30- May 1, 2018 (Oscar Dyson DY18-05). Surface mooring 17bsm-2a, indicated by the "m", had WeatherPak instruments on a surface float. The other 3 were subsurface moorings. The "p" in "bsp" indicates an ADCP current-meter mooring. Instrumentation included Aanderaa RCM-9 current meter, Teledyne RDI Workhorse Sentinel ADCP (WCP), PMEL MTR temperature recorders, SeaBird SBE-37 (Microcat), SBE-39, SBE-56, SBE 16 plus (Seacat) profilers and WetLabs EcoFluorometers.

Data include current speed and direction, calculated current components U and V, temperature, conductivity, salinity, pressure, water depth, oxygen concentration, calculated oxygen percent saturation, turbidity, raw chlorophyll fluorescence and chlorophyll a.

The cruise was funded by NOAA, Pacific Marine Environmental Laboratory EcoFOCI program and Alaska Ocean Observing System (AOOS), the NOAA-regional ocean data partnership.

Deployment and recovery operations on this cruise were managed by EcoFOCI personnel from NOAA/PMEL. Mooring time series data were processed at NOAA/PMEL/EcoFOCI using standard techniques. Time is recorded as UTC. Longitudes are stored in degW.

Data contacts: Phyllis Stabeno, Shaun Bell, Ryan McCabe, Peggy Sullivan.
DOI: 10.5281/zenodo.17800486
title: Audio-SAR-Dataset

description: Description

The SAR-Dataset is a synthetic audio dataset designed for training and evaluating acoustic classifiers to detect human-made distress signals in post-disaster environments. This dataset supports research in drone-based search and rescue operations where acoustic detection can complement visual sensing systems.

Dataset Generation

The dataset is generated from isolated sound samples in the PostDisasterDataset [1] by combining human-made distress signals with realistic background noises typical of post-disaster environments (thunder, rain, engines, tools). Each human distress sound is overlaid with randomly selected background noise attenuated by 6 dB, resulting in mean SNR values between 10-20 dB across classes.

Dataset Details

Total samples: 15,000 ten-second audio recordings

Classes (5): crying, coughing, screaming, knocking, none (3,000 samples each)

Split: 80% training (12,000) / 10% validation (1,500) / 10% test (1,500)

Audio format: 10-second mono recordings at 32 kHz

SNR range: 10-20 dB mean

File Naming Convention

[UniqueID]_[HumanClassID]_[BackgroundClassID].wav

Human Class ID





0 – coughing




1 – crying




2  – knocking




3 – screaming



Background Class ID





0 – engine




1 – heavy equipment




2 – rain




3 – thunder




4 – tools




5 – water




6 – wind



[1] Tuan-Anh Pham, Seong-Hun Park, Jong-Hoon Lee, Sang-Jin Han, Jungyu Choi, and Sungbin Im. An audio dataset and hierarchical taxonomy for post-disaster scenes. In Proceedings of Acoustics 2024. Australian Acoustical Society, November 2024.
DOI: 10.5281/zenodo.17800485
title: Audio-SAR-Dataset

description: Description

The SAR-Dataset is a synthetic audio dataset designed for training and evaluating acoustic classifiers to detect human-made distress signals in post-disaster environments. This dataset supports research in drone-based search and rescue operations where acoustic detection can complement visual sensing systems.

Dataset Generation

The dataset is generated from isolated sound samples in the PostDisasterDataset [1] by combining human-made distress signals with realistic background noises typical of post-disaster environments (thunder, rain, engines, tools). Each human distress sound is overlaid with randomly selected background noise attenuated by 6 dB, resulting in mean SNR values between 10-20 dB across classes.

Dataset Details

Total samples: 15,000 ten-second audio recordings

Classes (5): crying, coughing, screaming, knocking, none (3,000 samples each)

Split: 80% training (12,000) / 10% validation (1,500) / 10% test (1,500)

Audio format: 10-second mono recordings at 32 kHz

SNR range: 10-20 dB mean

File Naming Convention

[UniqueID]_[HumanClassID]_[BackgroundClassID].wav

Human Class ID





0 – coughing




1 – crying




2  – knocking




3 – screaming



Background Class ID





0 – engine




1 – heavy equipment




2 – rain




3 – thunder




4 – tools




5 – water




6 – wind



[1] Tuan-Anh Pham, Seong-Hun Park, Jong-Hoon Lee, Sang-Jin Han, Jungyu Choi, and Sungbin Im. An audio dataset and hierarchical taxonomy for post-disaster scenes. In Proceedings of Acoustics 2024. Australian Acoustical Society, November 2024.
DOI: 10.25921/s614-9c04
title: Experimental evaluation of nutrient and disease treatment effects on Acropora cervicornis (NCEI Accession 0299892)

description: Acropora cervicornis fragments of each genotype were evenly and haphazardly assigned to two nutrient treatments: ambient nutrients (Ambient) or elevated ammonium (NH4). Each nutrient treatment was replicated in four independent tanks (n = 3 fragments per genotype per tank). For ~1.5 months (47 d), Ambient tanks were maintained under nutrient levels consistent with the values in Virginia Key, FL, while elevated NH4 tanks were dosed with NH4Cl [3 mM] every 15 minutes using peristaltic pumps. The initial NH4 dose volume was 10 mL of the stock solution, targeting a ~10 μM increase in NH4 concentration. These values were calculated to account for the dilution of the nutrients resulting from adding new ambient seawater to the tanks (200 mL/min in a total tank volume of 180 L). After detecting higher than normal NH4 concentrations in the incoming seawater from Biscayne Bay, the NH4 dose volume was lowered to 5 mL of the stock solution, targeting ~5 μM NH4 increase above ambient values. The fragments were also assigned to disease vs. placebo treatments, the disease treatments involving exposure to homogenates of corals showing signs of white band disease following the protocol found in Rosales & Palacio-Castro (2024).

Water samples (~40 mL) were collected to monitor NH4 levels in the treatments and immediately refrigerated at 4C. The elevated NH4 tanks were sampled daily, but the Ambient tanks were sampled less frequently (~2-3 days and no samples were collected during weeks 1 and 3 of the experiment). Nutrient concentrations were measured at NOAA-AOML using an AA3 nutrient analyzer (Seal Analytical, Southampton, UK). The instrument was calibrated before each run using standard solutions and procedures. Initially, only NH4 was monitored, but after high NH4 concentrations in the source seawater were detected, additional measurements of PO4 were included.