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Dataset Title:  R/V Falkor 160115 CTD log from the ProteOMZ expedition in the Central Pacfic
during 2016 (ProteOMZ project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_708458)
Information:  Summary ? | License ? | Metadata | Background (external link) | Subset | Files | Make a graph
Variable ?   Optional
Constraint #1 ?
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 cruise (unitless) ?      
   - +  ?
 station (unitless) ?          1    12
 type (unitless) ?          "B"    "C"
 date (unitless) ?          "2016/01/17"    "2016/02/01"
 time2 (Time, unitless) ?          "10:30"    "NaN"
 longitude (degrees_east) ?          -156.0    -139.7959
  < slider >
 latitude (degrees_north) ?          6.66667E-4    16.99608333
  < slider >
 cast (unitless) ?          2    18
 niskin (unitless) ?          "1"    "sensors only - no ..."
 target_depth (meters) ?          5    1000
 depth (Actual Depth, m) ?          4.0    1003.0
  < slider >
 time (ISO Date Time UTC, UTC) ?          2016-01-17T13:50:00Z    
  < slider >
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cruise {
    String bcodmo_name "cruise_id";
    String description "Cruise name";
    String long_name "Cruise";
    String units "unitless";
  station {
    Byte _FillValue 127;
    Byte actual_range 1, 12;
    String bcodmo_name "station";
    String description "Station number";
    String long_name "Station";
    String units "unitless";
  type {
    String bcodmo_name "ev_type";
    String description "Event type; bottle only";
    String long_name "Type";
    String units "unitless";
  date {
    String bcodmo_name "date";
    String description "Date of sampling; YYYY/MM/DD";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  time2 {
    String bcodmo_name "time";
    String description "Local time of sampling; HH:MM";
    String long_name "Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -156.0, -139.7959;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude; E is positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 6.66667e-4, 16.99608333;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude; N is positive";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  cast {
    Byte _FillValue 127;
    Byte actual_range 2, 18;
    String bcodmo_name "cast";
    String description "Cast ID number";
    String long_name "Cast";
    String units "unitless";
  niskin {
    String bcodmo_name "bot_Nis";
    String description "Niskin bottle ID number";
    String long_name "Niskin";
    String units "unitless";
  target_depth {
    Int16 _FillValue 32767;
    Int16 actual_range 5, 1000;
    String bcodmo_name "depth";
    String description "Target depth";
    String long_name "Target Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String units "meters";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 4.0, 1003.0;
    String axis "Z";
    String bcodmo_name "depth";
    String description "Actual depth";
    String ioos_category "Location";
    String long_name "Actual Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4530386e+9, NaN;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "Date ISO formatted; UTC";
    String ioos_category "Time";
    String long_name "ISO Date Time UTC";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"R/V Falkor 160115 CTD log data.
Sampling was conducted using a CTD.";
    String awards_0_award_nid "646122";
    String awards_0_award_number "GBMF3782";
    String awards_0_data_url "https://www.moore.org/grant-detail?grantId=GBMF3782";
    String awards_0_funder_name "Gordon and Betty Moore Foundation: Marine Microbiology Initiative";
    String awards_0_funding_acronym "MMI";
    String awards_0_funding_source_nid "385";
    String awards_1_award_nid "685693";
    String awards_1_award_number "Unknown ProteOMZ Sloan Foundation";
    String awards_1_funder_name "Alfred P. Sloan Foundation";
    String awards_1_funding_acronym "Sloan";
    String awards_1_funding_source_nid "367";
    String awards_2_award_nid "685695";
    String awards_2_award_number "R/V Falkor 160115 SOI ProteOMZ Expedition";
    String awards_2_funder_name "Schmidt Ocean Institute";
    String awards_2_funding_acronym "SOI";
    String awards_2_funding_source_nid "393";
    String cdm_data_type "Other";
    String comment 
"R/V Falcor 160115 CTD Log: ProteOMZ Expedition 
  M. Saito and A. Santoro, PIs 
  Version 7 September 2017";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2017-07-12T19:10:19Z";
    String date_modified "2019-03-26T19:29:05Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.708458.1";
    Float64 Easternmost_Easting -139.7959;
    Float64 geospatial_lat_max 16.99608333;
    Float64 geospatial_lat_min 6.66667e-4;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -139.7959;
    Float64 geospatial_lon_min -156.0;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 1003.0;
    Float64 geospatial_vertical_min 4.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2021-12-05T01:01:15Z (local files)
2021-12-05T01:01:15Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_708458.html";
    String infoUrl "https://www.bco-dmo.org/dataset/708458";
    String institution "BCO-DMO";
    String instruments_0_acronym "CTD";
    String instruments_0_dataset_instrument_description "Used for water sampling";
    String instruments_0_dataset_instrument_nid "708466";
    String instruments_0_description "The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column.  The instrument is lowered via cable through the water column and permits scientists observe the physical properties in real time via a conducting cable connecting the CTD to a deck unit and computer on the ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or  radiometers.  It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.  This instrument designation is used when specific make and model are not known.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_0_instrument_name "CTD profiler";
    String instruments_0_instrument_nid "417";
    String instruments_0_supplied_name "CTD";
    String instruments_1_acronym "MIMS";
    String instruments_1_dataset_instrument_nid "708490";
    String instruments_1_description "Membrane-introduction mass spectrometry (MIMS) is a method of introducing analytes into the mass spectrometer's vacuum chamber via a semipermeable membrane.";
    String instruments_1_instrument_name "Membrane Inlet Mass Spectrometer";
    String instruments_1_instrument_nid "661606";
    String instruments_1_supplied_name "MIMS";
    String keywords "actual, actual_depth, bco, bco-dmo, biological, cast, chemical, cruise, data, dataset, date, depth, dmo, erddap, iso, ISO_DateTime_UTC, latitude, longitude, management, niskin, oceanography, office, preliminary, station, target, target_depth, time, time2, type";
    String license "https://www.bco-dmo.org/dataset/708458/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/708458";
    Float64 Northernmost_Northing 16.99608333;
    String param_mapping "{'708458': {'actual_depth': 'flag - depth', 'lat': 'master - latitude', 'lon': 'master - longitude', 'ISO_DateTime_UTC': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/708458/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Mak A. Saito";
    String people_0_person_nid "50985";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Barbara";
    String people_1_affiliation_acronym "UCSB-LifeSci";
    String people_1_person_name "Alyson Santoro";
    String people_1_person_nid "555313";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI";
    String people_2_person_name "Mak A. Saito";
    String people_2_person_nid "50985";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Hannah Ake";
    String people_3_person_nid "650173";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "ProteOMZ (Proteomics in an Oxygen Minimum Zone)";
    String projects_0_acronym "ProteOMZ (Proteomics in an Oxygen Minimum Zone)";
    String projects_0_description 
"From Schmidt Ocean Institute's ProteOMZ Project page:
Rising temperatures, ocean acidification, and overfishing have now gained widespread notoriety as human-caused phenomena that are changing our seas. In recent years, scientists have increasingly recognized that there is yet another ingredient in that deleterious mix: a process called deoxygenation that results in less oxygen available in our seas.
Large-scale ocean circulation naturally results in low-oxygen areas of the ocean called oxygen deficient zones (ODZs). The cycling of carbon and nutrients – the foundation of marine life, called biogeochemistry – is fundamentally different in ODZs than in oxygen-rich areas. Because researchers think deoxygenation will greatly expand the total area of ODZs over the next 100 years, studying how these areas function now is important in predicting and understanding the oceans of the future. This first expedition of 2016 led by Dr. Mak Saito from the Woods Hole Oceanographic Institution (WHOI) along with scientists from University of Maryland Center for Environmental Science, University of California Santa Cruz, and University of Washington aimed to do just that, investigate ODZs.
During the 28 day voyage named “ProteOMZ,” researchers aboard R/V Falkor traveled from Honolulu, Hawaii to Tahiti to describe the biogeochemical processes that occur within this particular swath of the ocean’s ODZs. By doing so, they contributed to our greater understanding of ODZs, gathered a database of baseline measurements to which future measurements can be compared, and established a new methodology that could be used in future research on these expanding ODZs.";
    String projects_0_geolocation "Central Pacific Ocean (Hawaii to Tahiti)";
    String projects_0_name "The ProteOMZ Expedition: Investigating Life Without Oxygen in the Pacific Ocean";
    String projects_0_project_nid "685696";
    String projects_0_project_website "https://schmidtocean.org/cruise/investigating-life-without-oxygen-in-the-tropical-pacific/#team";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 6.66667e-4;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "cruise";
    String summary "R/V Falkor 160115 CTD log from the ProteOMZ expedition in the Central Pacfic during 2016 (ProteOMZ project)";
    String time_coverage_start "2016-01-17T13:50:00Z";
    String title "R/V Falkor 160115 CTD log from the ProteOMZ expedition in the Central Pacfic during 2016 (ProteOMZ project)";
    String version "1";
    Float64 Westernmost_Easting -156.0;
    String xml_source "osprey2erddap.update_xml() v1.3";


Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

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For example,
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

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