Project Overview This dataset is a catalog of oceans data science initiatives (ODSIs). We define an ODSI as an initiative that mobilizes (often geospatial and temporal) big data and/or novel data sources about the oceans with an express goal of informing or improving conditions in the oceans. ODSI identification began in Jan 2020. Additional ODSIs will continue to be added. We identified more than 150 ODSIs and populated the catalog with data gathered from ODSI websites describing key features of their work including 1) the data infrastructure 2) their organizational structure, 3) the ocean worlds, or ontologies, they create, and 4) the (explicit or implicit) policy and governance ‘solutions’ and relations they promote. The ODSIs in the catalog are global and regional in scope and aim to enhance understanding around three topical concerns: fisheries extraction, biodiversity conservation, and enhancing basic scientific knowledge. Data overview For 100 ODSIs, we created metadata about the data architecture, organizational governance, and world-making practices such as their stated purpose, theory of change, and problem/solution framing. For a subset of 30 ODSIs, we created metadata about their policy and governance stances and practices. All metadata was created based on a textual analysis of their websites and public communications. Data collection overview Sampling strategy: We began with a purposive sample of ODSIs based on the research team’s prior knowledge of and participation in global and regional ODSIs. This sample allowed us to pilot and refine our metadata catalog approach. We then used a combination of keyword searches on Google using search terms such as ‘ocean data’ ‘marine data’ and ‘fisheries data’. Adopting a snowball sampling method, we reviewed the websites of ODSIs that came up in our initial search to find references to additional ODSIs. To determine if an entity was an ODSI, we reviewed web pages for information on purpose, goals, objectives, mission, values (usually in tabs labeled ‘About’ ‘Goals’ or ‘Objectives’) and we looked for links to ‘data’ or ‘data products.’ Entities were selected for our catalog based on two criteria: 1) their stated purpose, goals, objectives, mission, values indicated a commitment to advancing ocean science and data and 2) if they focused on regional or global scales. We selected and categorized ODSIs according to three broad focal areas in global and regional oceans governance: fisheries extraction, biodiversity conservation, and basic ocean science development. Shared data organization This catalog is comprised of three files. 'Havice_ODSIC.pdf' provides a list of each ODSI included in the catalog, and a permalink to the webpage used to populate catalog metadata categories. 'Havice_ODSIC-CodingScheme.pdf' provides a list of code description for the catalog metadata. 'Havice_ODSIC-Metadata.xlsx' is the full catalog with populated metadata.

Long Island Sound observation data from Project Oceanology. These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats. cdm_data_type=Point Conventions=COARDS, CF-1.6, Unidata Dataset Discovery v1.0 featureType=Point geospatial_lat_units=degrees_north geospatial_lon_units=degrees_east id=Project Oceanology Trawl info_url=http://lisicos.uconn.edu/ infoUrl=http://lisicos.uconn.edu/ institution=University of Connecticut keywords_vocabulary=GCMD Science Keywords naming_authority=edu.connecticut sourceUrl=(source database) standard_name_vocabulary=CF-1.6 station=Project Oceanology Data station_site_desc=Project_Oceanology Data testOutOfDate=now-1day

This dataset is a collection of marine environmental data layers suitable for use in Southern Ocean species distribution modelling. All environmental layers have been generated at a spatial resolution of 0.1 degrees, covering the Southern Ocean extent (80 degrees S - 45 degrees S, -180 - 180 degrees). The layers include information relating to bathymetry, sea ice, ocean currents, primary production, particulate organic carbon, and other oceanographic data.

An example of reading and using these data layers in R can be found at https://australianantarcticdivision.github.io/blueant/articles/SO_SDM_data.html.

The following layers are provided:

1. Layer name: depth Description: Bathymetry. Downloaded from GEBCO 2014 (0.0083 degrees = 30sec arcmin resolution) and set at resolution 0.1 degrees. Then completed with the bathymetry layer manually corrected and provided in Fabri-Ruiz et al. (2017) Value range: -8038.722 - 0 Units: m

Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ Citation: Fabri-Ruiz S, Saucede T, Danis B and David B (2017). Southern Ocean Echinoids database_An updated version of Antarctic, Sub-Antarctic and cold temperate echinoid database. ZooKeys, (697), 1.

1. Layer name: geomorphology Description: Last update on biodiversity.aq portal. Derived from O'Brien et al. (2009) seafloor geomorphic feature dataset. Mapping based on GEBCO contours, ETOPO2, seismic lines). 27 categories Value range: 27 categories Units: categorical Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: O'Brien, P.E., Post, A.L., and Romeyn, R. (2009) Antarctic-wide geomorphology as an aid to habitat mapping and locating vulnerable marine ecosystems. CCAMLR VME Workshop 2009. Document WS-VME-09/10

2. Layer name: sediments Description: Sediment features Value range: 14 categories Units: categorical Source: Griffiths 2014 (unpublished) URL: http://share.biodiversity.aq/GIS/antarctic/

3. Layer name: slope Description: Seafloor slope derived from bathymetry with the terrain function of raster R package. Computation according to Horn (1981), ie option neighbor=8. The computation was done on the GEBCO bathymetry layer (0.0083 degrees resolution) and the resolution was then changed to 0.1 degrees. Unit set at degrees. Value range: 0.000252378 - 16.94809 Units: degrees Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/ Citation: Horn, B.K.P., 1981. Hill shading and the reflectance map. Proceedings of the IEEE 69:14-47

4. Layer name: roughness Description: Seafloor roughness derived from bathymetry with the terrain function of raster R package. Roughness is the difference between the maximum and the minimum value of a cell and its 8 surrounding cells. The computation was done on the GEBCO bathymetry layer (0.0083 degrees resolution) and the resolution was then changed to 0.1 degrees. Value range: 0 - 5171.278 Units: unitless Source: This study. Derived from GEBCO URL: https://www.gebco.net/data_and_products/gridded_bathymetry_data/

5. Layer name: mixed layer depth Description: Summer mixed layer depth climatology from ARGOS data. Regridded from 2-degree grid using nearest neighbour interpolation Value range: 13.79615 - 461.5424 Units: m Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

6. Layer name: seasurface_current_speed Description: Current speed near the surface (2.5m depth), derived from the CAISOM model (Galton-Fenzi et al. 2012, based on ROMS model) Value range: 1.50E-04 - 1.7 Units: m/s Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: see Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214, https://data.aad.gov.au/metadata/records/polar_environmental_data

7. Layer name: seafloor_current_speed Description: Current speed near the sea floor, derived from the CAISOM model (Galton-Fenzi et al. 2012, based on ROMS) Value range: 3.40E-04 - 0.53 Units: m/s Source: This study. Derived from Australian Antarctic Data Centre URL: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data Citation: see Galton-Fenzi BK, Hunter JR, Coleman R, Marsland SJ, Warner RC (2012) Modeling the basal melting and marine ice accretion of the Amery Ice Shelf. Journal of Geophysical Research: Oceans, 117, C09031. http://dx.doi.org/10.1029/2012jc008214, https://data.aad.gov.au/metadata/records/polar_environmental_data

8. Layer name: distance_antarctica Description: Distance to the nearest part of the Antarctic continent Value range: 0 - 3445 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

9. Layer name: distance_canyon Description: Distance to the axis of the nearest canyon Value range: 0 - 3117 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

10. Layer name: distance_max_ice_edge Description: Distance to the mean maximum winter sea ice extent (derived from daily estimates of sea ice concentration) Value range: -2614.008 - 2314.433 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

11. Layer name: distance_shelf Description: Distance to nearest area of seafloor of depth 500m or shallower Value range: -1296 - 1750 Units: km Source: https://data.aad.gov.au/metadata/records/Polar_Environmental_Data

12. Layer name: ice_cover_max Description: Ice concentration fraction, maximum on [1957-2017] time period Value range: 0 - 1 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

13. Layer name: ice_cover_mean Description: Ice concentration fraction, mean on [1957-2017] time period Value range: 0 - 0.9708595 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

14. Layer name: ice_cover_min Description: Ice concentration fraction, minimum on [1957-2017] time period Value range: 0 - 0.8536261 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

15. Layer name: ice_cover_range Description: Ice concentration fraction, difference maximum-minimum on [1957-2017] time period Value range: 0 - 1 Units: unitless Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

16. Layer name: ice_thickness_max Description: Ice thickness, maximum on [1957-2017] time period Value range: 0 - 3.471811 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

17. Layer name: ice_thickness_mean Description: Ice thickness, mean on [1957-2017] time period Value range: 0 - 1.614133 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

18. Layer name: ice_thickness_min Description: Ice thickness, minimum on [1957-2017] time period Value range: 0 - 0.7602701 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

19. Layer name: ice_thickness_range Description: Ice thickness, difference maximum-minimum on [1957-2017] time period Value range: 0 - 3.471811 Units: m Source: BioOracle accessed 24/04/2018, see Assis et al. (2018) URL: http://www.bio-oracle.org/ Citation: Assis J, Tyberghein L, Bosch S, Verbruggen H, Serrao EA and De Clerck O (2018). Bio_ORACLE v2. 0: Extending marine data layers for bioclimatic modelling. Global Ecology and Biogeography, 27(3), 277-284 , see also https://www.ecmwf.int/en/research/climate-reanalysis/ocean-reanalysis

20. Layer name:

Temperature, salinity, and other data were collected from CTD casts in the mouth of Resurrection Bay, near Seward, Alaska. Data were collected from the R/V Little Dipper from 1970 to 1997. Data were collected as part of the Gulf of Alaska (GAK) time series. Data include profiles of water temperature, salinity, sigma-theta, and delta.

Current meter components data were collected from FIXED PLATFORMS in the Auke Bay from 31 March 1989 to 01 July 1989. Data were collected by the University of Alaska - Fairbanks; Institute of Marine Science (UAK/IMS). Data were processed by NODC to the NODC standard F015 Current Meter Components format. Full format description is available from NODC at www.nodc.noaa.gov/General/NODC-Archive/f015.html.

The F015 format contains time series measurements of ocean currents. These data are obtained from current meter moorings and represent the Eulerian method of current measurement, i.e., the meters are deployed at a fixed point and measure flow past a sensor. Position, bottom depth, sensor depth and meter characteristics are reported for each station. The data record includes values of east-west (u) and north-south (v) current vector components at specified date and time. Current direction is defined as the direction toward which the water is flowing with positive directions east and north. Data values may be subject to averaging or filtering and are typically reported at 10 - 15 minute time intervals. Water temperature, pressure and conductivity or salinity may also be reported. A text record is available for optional comments.

NCEI Accession 0157036 contains oceanographic and surface meteorological data collected from an automated shore station with a suite of sensors that are attached to Stearns Wharf along the nearshore California coast. These automated sensors measure CHLOROPHYLL A CONCENTRATION, CONDUCTIVITY, DEPTH - OBSERVATION, HYDROSTATIC PRESSURE, SALINITY, WATER DENSITY and WATER TEMPERATURE at frequent intervals in the nearshore coastal ocean. These data can provide local and regional information on mixing and upwelling, land run-off, and algal blooms. Marine Science Institute at University of California, Santa Barbara, collected the data and provided the data to SCCOOS, which assembles data from Marine Science Institute at University of California, Santa Barbara, and other sub-regional coastal and ocean observing systems of the Southern California Coastal United States, submitted the data to NCEI as part of the Integrated Ocean Observing System Data Assembly Centers (IOOS DACs) Data Stewardship Program.The data are made available in netCDF formatted files, which follow the Climate and Forecast metadata convention (CF) and the Attribute Convention for Data Discovery (ACDD). Each quarter, NCEI adds to this accession the data collected or updated during the previous quarter.

No description is available. Visit https://dataone.org/datasets/%7BEAFB67F3-7F9E-44E7-BBFE-B99E19C3DA24%7D for complete metadata about this dataset.

Oceanographic measurements were collected aboard Aurora Australis cruise au1603, voyage 3 2015/2016, from 11th January to ~24th February 2016. The cruise commenced with the K-AXIS project, the major marine science component of the cruise. This was the Australian component (P.I.’s Andrew Constable, Steve Rintoul and others) of a combined biological and oceanographic study in the vicinity of the Kerguelen Axis. After conclusion of marine science work the ship went to Mawson for a resupply. During a storm on 24th February the ship broke free of its mooring lines and ran aground on the rocks at West Arm in Horseshoe Harbour, thus ending the cruise. Expeditioners were eventually taken to Casey on the Shirase, then flown home. Meanwhile the Aurora Australis was refloated and sailed to Fremantle, then on to Singapore for repairs. This report discusses the oceanographic data from CTD operations on the cruise. A total of 47 CTD vertical profile stations were taken on the cruise (Table 1). Over 850 Niskin bottle water samples were collected for the measurement of salinity, dissolved oxygen, nutrients (phosphate, nitrate+nitrite and silicate), dissolved inorganic carbon (i.e. TCO2), alkalinity, POC and PN, and biological parameters, using a 24 bottle rosette sampler. A UVP particle counter/camera system was attached to the CTD package (P.I. Emmanuel Laurenceau). A separate trace metal rosette system was deployed from the trawl deck (P.I. Andrew Bowie). Upper water column current profile data were collected by a ship mounted ADCP, and meteorological and water property data were collected by the array of ship's underway sensors. Eight drifting floats were deployed over the course of the cruise. Processing/calibration and data quality for the main CTD data are described in this report. Underway sea surface temperature and salinity data are compared to near surface CTD data. CTD station positions are shown in Figure 1, while CTD station information is summarised in Table 1. Float deployments (5 x Argo/Apex, 2 x SOCCOM and 1 x Provor) are summarised in Table 10. Further cruise itinerary/summary details can be found in the voyage leader report (Australian Antarctic Division unpublished report: Voyage 3 2015-2016, RSV Aurora Australis, Voyage Leader’s report - see the metadata record "Aurora Australis Voyage 3 2015/16 Track and Underway Data" for access to the Voyage Report).

This dataset is superseded by ICOADS Release 3, Individual Observations [https://rda.ucar.edu/datasets/ds548.0/].

The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a global ocean marine meteorological and surface ocean dataset. It is formed by merging many national and international data sources that contain measurements and visual observations from ships (merchant, navy, research), moored and drifting buoys, coastal stations, and other marine platforms. Each report contains individual observations of meteorological and oceanographic variables, such as sea surface and air temperatures, wind, pressure, humidity, and cloudiness. The coverage is global and sampling density varies depending on date and geographic position relative to shipping routes and ocean observing systems.

All three U.S. ICOADS partners (NOAA/ESRL, NOAA/NCDC, NCAR) offer various data access and format options. To review all available options see the ICOADS website [http://icoads.noaa.gov/products.html].

IMPORTANT: The time period of data available is defined in two segments. * ICOADS Release 2.5 covers 1662 through 2007 * All data following the Release 2.5 end date is based exclusively on real-time GTS data with minimal quality control. These data should be considered preliminary and will be subject to change in new Releases of ICOADS

Long Island Sound observation data from the Department of Energy and Environmental Protection (DEEP). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats. cdm_data_type=Other contributor_name=Department of Energy and Environmental Protection (DEEP) contributor_role=sponsor contributor_url=https://www.ct.gov/deep/site/default.asp Conventions=COARDS, CF-1.6, Unidata Dataset Discovery v1.0 id=DEEP info_url=http://lisicos.uconn.edu/dep_portal.php infoUrl=http://lisicos.uconn.edu/ institution=University of Connecticut keywords_vocabulary=GCMD Science Keywords naming_authority=edu.connecticut neracoos_data_provider=UCONN project=DEEP sourceUrl=(source database) standard_name_vocabulary=CF-1.6 station=DEEP CTD Data station_site_desc=DEEP Cruise Info Data testOutOfDate=now-1day

This metadata record describes bottom-mounted ADCP data collected at Santa Cruz Island, California, USA, by PISCO. Measurements were collected using an RDI 600 kHz Workhorse Sentinel ADCP beginning 2006-03-13. The instrument depth was 015 meters, in an overall water depth of 015 meters (both relative to Mean Sea Level, MSL). The instrument was programmed with a sampling interval of 2.0 minutes and a vertical resolution of 1 meter.

Overview

The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is a global ocean marine meteorological and surface ocean dataset. It is formed by merging many national and international data sources that contain measurements and visual observations from ships (merchant, navy, research), moored and drifting buoys, coastal stations, and other marine and near-surface ocean platforms. Each marine report contains individual observations of meteorological and oceanographic variables, such as sea surface and air temperatures, wind, pressure, humidity, and cloudiness. The coverage is global and sampling density varies depending on date and geographic position relative to shipping routes and ocean observing systems.

Content

The ICOADS dataset contains global marine data from ships (merchant, navy, research) and buoys, each capturing details according to the current weather or ocean conditions (wave height, sea temperature, wind speed, and so on). Each record contains the exact location of the observation which is great for visualizations. The historical depth of the data is quite comprehensive — There are records going back to 1662!

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.github_repos.[TABLENAME]. Fork this kernel to get started to learn how to safely manage analyzing large BigQuery datasets.

Acknowledgements

Dataset Source: NOAA Category: Meteorological, Climate, Transportation

Citation: National Centers for Environmental Information/NESDIS/NOAA/U.S. Department of Commerce, Research Data Archive/Computational and Information Systems Laboratory/National Center for Atmospheric Research/University Corporation for Atmospheric Research, Earth System Research Laboratory/NOAA/U.S. Department of Commerce, Cooperative Institute for Research in Environmental Sciences/University of Colorado, National Oceanography Centre/Natural Environment Research Council/United Kingdom, Met Office/Ministry of Defence/United Kingdom, Deutscher Wetterdienst (German Meteorological Service)/Germany, Department of Atmospheric Science/University of Washington, and Center for Ocean-Atmospheric Prediction Studies/Florida State University. 2016, updated monthly. International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Release 3, Individual Observations. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory: https://doi.org/10.5065/D6ZS2TR3. Accessed 01 04 2017.

Use: This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Photo by Gleb Kozenko on Unsplash

SeaDataNet is the Pan-European infrastructure for marine and ocean data management and delivery services. It is supported by the EU under its Research Infrastructures programme. It connects 40 National Oceanographic Data Centres (NODC's) and 50 other data centres from 35 countries, bordering the European seas and Atlantic Ocean. The centres are mostly part of major marine management and research organisations that are acquiring and managing a large collection of marine and ocean data from various disciplines. This includes major international organisations, ICES and IOC-IODE. The overall objective is provide overview and access to marine and oceanographic data and data-products from government and research institutes in Europe. SeaDataNet contributes to the implementation of the EU INSPIRE and Marine Strategy Framework Directives. It also plays a key role in the development and operation of the EU EMODNet initiative. The SeaDataNet infrastructure is fully operational and INSPIRE compliant. It includes a versatile SeaDataNet portal (http://www.seadatanet.org) that provides users with a range of metadata, data and data product access services as well as standards, tools and guides for good marine data management. The Common Data Index (CDI) data discovery & access service provides harmonised access to the large volumes of datasets that are managed by the connected data centres. The CDI service contains already references and gives access to more than 1,5 milllion marine and oceanographic datasets as managed by 90 data centres. These numbers are increasing regularly because of further data population and more connected data centres as part of SeaDataNet II, EMODnet and other EU projects. For inclusion in the SeaDataNet INSPIRE compliant CSW service, the CDI records (at granule level) have been aggregated into CDI collections by a combination of Discipline, Data Centre, and geometric type. Each CSW XML record therefore represents a large collection of individual metadata records and associated datasets. By following the specified URL to the SeaDataNet portal users can evaluate these metadata in detail and request access by downloading of interesting datasets via the shopping cart transaction system that is integrated in the SeaDataNet portal.

The Animal Tracking Facility (formerly known as the Australian Animal Tracking And Monitoring System (AATAMS)) is a coordinated marine animal tagging project. Satellite Relay Data Loggers (SRDL) (most with CTDs, and some also with fluorometers) are used to explore how marine mammal behaviour relates to their oceanic environment. Loggers developed at the University of St Andrews Sea Mammal Research Unit transmit data in near real time via the Argo satellite system. The Satellite Relay Data Loggers are deployed on marine mammals, including Elephant Seals, Weddell Seals, Australian Fur Seals, Australian Sea Lions, New Zealand Fur Seals. Data is being collected in the Southern Ocean, the Great Australian Bight, and off the South-East Coast of Australia. This metadata record, represents several different datasets listed hereafter, which can all be accessed through a multi-WFS service. The data represented by this record are presented in delayed mode. CTD - parameters measured by the instruments include time, conductivity (salinity), temperature, speed, fluorescence (available in the future) and depth. Diving - parameters measured by the instruments include start and end time and longitude/latitude of each individual dive, post-dive surface duration, dive duration, maximum dive depth, intermediate dive depths and times. Haulout - a haulout begins when the SRDL has been continuously dry for a specified length of time (usually 10 minutes). It ends when continuously wet for another interval (usually 40 seconds). Haulout data parameters measured by the instruments include haulout start and end dates and longitude/latitude, and haulout number. Argos locations - location data parameters measured by the instruments include time, longitude, latitude, location quality, along with other diagnostic information provided by Argos (http://www.argos-system.org/). Summary Statistics - as well as sending records of individual events such as dives and haulouts, the SRDL also calculates summary statistics of those events over a specified time period (usually 3, 4 or 6 hours). Summary statistics computed by the instruments include the proportion of time spent diving, at the surface and hauled-out, the number of dives, and the average, standard deviation and maximum dive duration and dive depth during each summary period. These statistics are based on all the data recorded by the SRDL and so are not prone to distortion by variations in the efficiency of transmission via Argos.

This dataset includes measurements of marine microbial respiration and associated environmental variables contributed before July 2025 and collated within the UK research project MicroRESPIRE and the international working group Respiration in the Mesopelagic Ocean (ReMO). The dataset includes respiration rates estimated from oxygen consumption in incubations measured with optodes, membrane inlet mass spectrometry, or Winkler analytical chemistry with optical, potentiometric or spectrophotometric detection. Rates were also estimated from the formation of formazan during incubations of water samples (INT technique) or in samples captured on filters (ETS technique). Estimates of respiration rates were also calculated from the difference between net community production and gross primary production derived from the production of oxygen during an incubation of a water sample spiked with 18O labelled water. Other incubation-based estimates were derived from the fluorescence of the redox dye RedoxSensor Green (RSG) and the production of 14CO2 during the incubation of a water sample spiked with 14C-leucine. In situ respiration was estimated from changes in oxygen concentration measured by oxygen sensors deployed on platforms such BGC Argo floats or CTDs. Measurements of prokaryote production and abundance are also included.
Environmental variables include dissolved oxygen, temperature, phytoplankton chlorophyll, inorganic nutrients and dissolved and particulate carbon, nitrogen and phosphorus. The data are available in ASCII, Excel and Ocean Data View formats and accompanied by a machine-readable JSON-LD description file. Standard deviation or standard error uncertainty values are provided where available. Metadata include details of the methods used such as volume sampled, incubation time and temperature, equations used to derive oxygen consumption at in situ temperature and details of any filtration step. Data providers (with ORCID), links to the data centre where the original data are held and publications describing the data and methods are also included. The aim is for the dataset to be as easy to use as possible by field going scientists and modellers investigating the flux of carbon from the surface to the deep ocean, with a particular focus on the mesopelagic zone between 200 and 1000 m.
This data collation was supported by funding from the UK Natural Environment Research Council (NERC) project MicroRESPIRE NE/X008630/1 as part of the BioCarbon programme and by funding to the Scientific Committee on Oceanic Research (SCOR) working group #161 (Respiration in the Mesopelagic Ocean: ReMO) provided by the national committees of SCOR and from a grant to SCOR from the U.S. National Science Foundation (OCE-2513154).

Oceanographic data were collected on Aurora Australis Voyage 4 2003/2004, from December 2003 to February 2004, and a calibrated data set was created. The oceanographic program on the voyage was a part of the cruise-determining fish survey in the vicinity of Heard Island. A total of 42 CTD vertical profile stations were taken, most to within 5 m of the bottom. Over 450 Niskin bottle samples were collected and analysed on board, for calibration of the CTD conductivity sensors. Nutrient samples were also collected, but not analysed. Near surface current data were collected using a ship mounted ADCP. Data from the array of ship's underway sensors are included in the data set.

The data report describes the processing/calibration of the CTD and ADCP data, and gives important details concerning data quality. An offset correction was derived for the underway sea surface temperature and salinity data, by comparison with near surface CTD data.

These data form part of the overall dataset for ASAC project 2388 (ASAC_2388).

This metadata record describes bottom-mounted ADCP data collected at Hopkins Marine Station, California, USA, by PISCO. Measurements were collected using an RDI 600 kHz Workhorse Sentinel ADCP beginning 2001-01-22. The instrument depth was 019 meters, in an overall water depth of 020 meters (both relative to Mean Sea Level, MSL). The instrument was programmed with a sampling interval of 2.0 minutes and a vertical resolution of 1 meter.

Northeastern Regional Association Ocean Observing Systems (NERACOOS) Gulf of Maine Buoy F01 - Massachusetts Bay. University of Maine real-time buoy observations in the Gulf of Maine at NERACOOS site F01 - Massachusetts Bay, located at 42d 31.392m N, 70d 33.930m W SE of Gloucester. Oceanographic measurements of temperature, conductivity,salinity, and density at a depth of 20 meters were taken hourly. acknowledgement=The University of Maine Ocean Observing System (UMOOS) is funded in part through NERACOOS and the National Oceanic and Atmospheric Administration (NOAA) as a Regional Association within the U.S. Integrated Ocean Observing System (IOOS). UMOOS is coordinated by the University of Maine's Physical Oceanography Group (PhOG). acknowledgment=Buoys operated by the University of Maine Physical Oceanography Group (PhOG) are funded in part through the National Oceanic and Atmospheric Administration (NOAA) as a Regional Association within the U.S. Integrated Ocean Observing System (IOOS). breakout_id=2 buffer_type=doppler cdm_data_type=TimeSeries cdm_timeseries_variables=station, longitude, latitude clock_time=Center of period comment=University of Maine, Physical Oceanography Group contact=um_phog_dmac@umeoce.maine.edu contributor_email=info@neracoos.org,info@gmri.org contributor_name=NERACOOS,Gulf of Maine Research Institute contributor_role=funder,distributor contributor_role_vocabulary=https://vocab.nerc.ac.uk/collection/G04/current/ contributor_url=http://neracoos.org,http://www.gmri.org Conventions=CF-1.8,ACDD-1.3,IOOS-1.2, COARDS date_metadata_modified=2026-05-02T00:56:52Z delta_t=60 depth_datum=Sea Level Easternmost_Easting=-68.9953 ending_time=1.77768E9 ending_time_string=2026-05-02T00:00:00Z featureType=TimeSeries geospatial_bounds=POINT (-68.9982 44.0555) geospatial_bounds_crs=EPSG:4326 geospatial_bounds_vertical_crs=EPSG:5831 geospatial_lat_max=44.0561 geospatial_lat_min=44.0534 geospatial_lat_resolution=0.01 degrees geospatial_lat_units=degrees_north geospatial_lon_max=-68.9953 geospatial_lon_min=-68.9985 geospatial_lon_resolution=0.001 degrees geospatial_lon_units=degrees_east geospatial_vertical_max=3.2 geospatial_vertical_min=2.8 geospatial_vertical_positive=down geospatial_vertical_resolution=0.5 meter geospatial_vertical_units=m grid_mapping_epsg_code=EPSG:4326 grid_mapping_inverse_flattening=298.257223563 grid_mapping_long_name=coordinate_reference_system grid_mapping_longitude_of_prime_meridian=0.0 grid_mapping_name=latitude_longitude grid_mapping_semi_major_axis=6378137.0 gts_ingest=true history=Ocean Data Acquisition Systems (ODAS) Buoy id=F0137.ocean.003m.merged_20260502T005652.373.nc infoUrl=https://oceandata.umeoce.maine.edu/buoy/F01 institution=Physical Oceanography Group, School of Marine Sciences, University of Maine institution_url=http://gyre.umeoce.maine.edu instrument=In Situ/Laboratory Instruments > Probes > Temperature Probe instrument_number=0 instrument_vocabulary=NASA/GCMD Instrument Keywords Version 8.1 ioos_ingest=true julian_day_convention=Julian date convention begins at 00:00:00 UTC on 17 November 1858 AD keywords_vocabulary=GCMD Science Keywords last_modified=2026-05-02T00:00:00Z magnetic_variation=-15.8 metadata_link=https://oceandata.umeoce.maine.edu/buoy/F01/metadata mooring_history=2026-05-01T22:51Z Deployed by R/V Connecticut

mooring_site_desc=Between Owls Head and Vinalhaven mooring_site_id=F0137 naming_authority=edu.maine nco_openmp_thread_number=1 Northernmost_Northing=44.0561 number_observations_per_hour=1 operator_sector=academic platform=moored_buoy platform_id=F01 platform_name=F01 - Penobscot Bay platform_vocabulary=https://mmisw.org/ont/ioos/platform position_datum=WGS 84 principal_investigator=Dr. Neal R. Pettigrew principal_investigator_email=nealp@maine.edu principal_investigator_institution=University of Maine, School of Marine Sciences processing=merged processing_level=Realtime preliminary QC program=Integrated Ocean Observing System project=NERACOOS project_url=http://www.neracoos.org references=http://gyre.umeoce.maine.edu/data/gomoos/buoy/doc/buoy_system_doc/buoy_system/book1.html sea_name=Gulf of Maine site_id=F01 site_latitude=44.0555 site_longitude=-68.9982 source=Ocean Data Acquisition Systems (ODAS) Buoy sourceUrl=(local files) Southernmost_Northing=44.0534 sponsor=NOAA standard_name_vocabulary=CF Standard Name Table v72 starting_time=1.7776764E9 starting_time_string=2026-05-01T23:00:00Z station_photo_url=http://gyre.umeoce.maine.edu/images/gomoosbuoy.jpg station_type=Surface Mooring subsetVariables=latitude, longitude, depth, station, deployment, time, temperature, temperature_qc_agg, temperature_qc_tests, temperature_qc, instrument_1, data_source, crs testOutOfDate=now-1day time_coverage_duration=PT1H time_coverage_end=2026-05-04T09:00:00Z time_coverage_resolution=PT60M time_coverage_start=2001-07-08T01:00:00Z time_deployed=2025-06-23T00:00Z time_recovered=0000-00-00T00:00Z time_zone=UTC uuid=n null Westernmost_Easting=-68.9985 wmo_platform_code=44033

The Institute of Marine Science (IMS) maintains an oceanographic database using the Ingres(tm) relational database management system (RDBMS). It contains physical, chemical, biological and geological data from the Gulf of Alaska, Bering Sea, Chukchi Sea, Beaufort Sea, Prince William Sound, Cook Inlet and other coastal waters. Currently, the database contains data as far back as 1970 and it is about 500 Mbytes in size. Access is restricted to IMS researchers. However most data can be extracted from the database and forward to other researchers on a at-cost basis. Copies of most data were submitted to the National Oceanographic Data Center (NODC).

Physical Oceanography % STD - Salinity, Temperature and Depth. 60% of the database. % CM - Current Meters. % TG - Tide Gauges.

Biological Oceanography % INFAUNA - Benthic Data from the Bering and Chukchi Seas. % PHYTO - Phytoplankton data from the ISHTAR project. % ZOOP - Zooplankton data from the ISHTAR, APPRISE and other projects. % CHL - Chlorophyll data from the ISHTAR project. % PP - Primary productivity, carbon and nitrogen uptake data from the ISHTAR project.

Chemical Oceanography % NUTRIENT - Nutrient chemistry data from the ISHTAR project. % METAL - Heavy metal concentration data. (very small)

Geological Oceanography % GRAIN SIZE - Sediment grain size data from the beaufort and chukchi seas.

Exxon Oil Spill Data

This database is "litigation sensitive." Access is restricted to researchers working on the Coastal Habitat Injury Assessment (CHIA) project. % INTERTIDAL % Invertebrates % Fishes % Algae % Semicircle Density % Limpet Growth/Survivorship % Mussel Growth/Survivorship % Swath Data % Mussel Histology % Photo Analysis % SUBTIDAL % Shallow Infaunal and Epifaunal Data % Deep Infaunal Data, 40+ Meters

The Institute of Marine Science (IMS) is the oldest and the largest unit of the School of Fisheries and Ocean Sciences. It is active in research and graduate training at the masters and doctoral levels, supports coastal facilities at Seward and Kasitsna Bay, and operates the 133-foot research vessel Alpha Helix for the National Science Foundataion.

Ocean observation data from the Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS). The NERACOOS region includes the northeast United States and Canadian Maritime provinces, as part of the United States Integrated Ocean Observing System (IOOS). These data are served by Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats. cdm_data_type=TimeSeries cdm_timeseries_variables=station contributor_name=Northeastern Regional Association of Coastal Ocean Observing Systems (NERACOOS) contributor_role=sponsor contributor_url=http://neracoos.org Conventions=COARDS, CF-1.6, Unidata Dataset Discovery v1.0 featureType=TimeSeries geospatial_lat_units=degrees_north geospatial_lon_units=degrees_east geospatial_vertical_positive=down geospatial_vertical_units=m id=CLIS info_url=http://lisicos.uconn.edu/about_clis.php infoUrl=http://lisicos.uconn.edu/ institution=University of Connecticut keywords_vocabulary=GCMD Science Keywords naming_authority=edu.connecticut neracoos_data_provider=UCONN project=NERACOOS sourceUrl=(source database) standard_name_vocabulary=CF-1.6 station=CLIS_WAVE station_site_desc=Central Sound Buoy Wave Data subsetVariables=station testOutOfDate=now-1day wmo_platform_code=44022