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Dataset Title:	[Total Organic Sulfur] - Total organic sulfur (TOS) collected from Niskin bottle samples on R/V Knorr cruise KN210-04 in the Western Atlantic Ocean between Uruguay and Barbados from March to May 2013 (Deep Atlantic DOM project) (Dissolved Organic Matter Composition in the Deep Atlantic Ocean)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_745536)
Range:	longitude = -55.29925 to -28.502443°E, latitude = -37.998253 to 9.700333°N, depth = 5.724 to 5108.562m
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

Web page authors can embed a graph of the latest data in a web page using HTML <img> tags.
Anyone can use ERDDAPs Slide Sorter to build a personal web page that displays graphs with the latest data (or other images or HTML content), each in its own, draggable slide.

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  cast {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 2, 68;
    String bcodmo_name "cast";
    String description "cast number";
    String long_name "Cast";
    String units "unitless";
  }
  station {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 2, 23;
    String bcodmo_name "station";
    String description "station number";
    String long_name "Station";
    String units "unitless";
  }
  date_utc_YYYYMMDD_start {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20130327, 20130504;
    String bcodmo_name "date";
    String description "date, UTC, given as year – month – day";
    String long_name "Date Utc YYYYMMDD Start";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  time_utc_HHMM_start {
    Int16 _FillValue 32767;
    Int16 actual_range 334, 2317;
    String bcodmo_name "time";
    String description "time, UTC, given as hour – minute";
    String long_name "Time Utc HHMM Start";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/AHMSAA01/";
    String units "unitless";
  }
  event_start {
    String bcodmo_name "event";
    String description "the event number from the ELOG maintained during the cruise";
    String long_name "Event Start";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/EVTAGFL/";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 5.724, 5108.562;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth in meters";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -37.998253, 9.700333;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String source_name "lat_start";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -55.29925, -28.502444;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String source_name "lon_start";
    String standard_name "longitude";
    String units "degrees_east";
  }
  TOS_nM {
    Float64 _FillValue NaN;
    Float64 actual_range 43.8006994318009, 1275.09413111938;
    String bcodmo_name "S";
    String description "total organic sulfur, in nM";
    String long_name "TOS N M";
    String units "nanomolar (nM)";
  }
  TOS_sd {
    Float64 _FillValue NaN;
    Float64 actual_range 8.90314481756031, 118.726847258504;
    String bcodmo_name "S";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation for total organic sulfur, from averages of replicates where available";
    String long_name "TOS Sd";
    String units "nanomolar (nM)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Whole seawater samples for obtaining the concentration of total organic sulfur
(TOS) were collected directly from the Niskin bottles into combusted 40 mL
glass vials. The vials were stored frozen (-20\\u00b0C) until analysis on land.
 
TOS was determined as described in Cutter et al. In brief, a sample is pumped
through three ion exchange cartridges connected in series, a 1 mL Ba (Dionex
OnGuard II #057093) to remove most of the sulfate, then through a 2.5 mL Ag
(Dionex OnGuard II Ag #057090) to remove chloride, and finally through a 1 mL
cartridge packed with BioRad AG 4x4 resin (#143-3341) to remove the remaining
sulfate. The resulting sample is then analyzed via ion chromatography to
quantify remaining sulfate. Total sulfur is quantitatively converted to H2S by
via reductive pyrolysis in pure hydrogen gas and quantified by gas
chromatography/flame photometric detection using the trapping /detection
system of Radford-Knoery and Cutter. Total organic sulfur is calculated as the
difference between total sulfur and residual sulfate. Each step of this
analysis has an error attached. The units for TOS are nM; when
provided,\\u00a0TOS_sd is the standard deviation of the average for replicate
samples. Precision was >10% RSD at/above 200 nM S and the detection limit was
26 nM S.";
    String awards_0_award_nid "54954";
    String awards_0_award_number "OCE-1154320";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1154320";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Donald L. Rice";
    String awards_0_program_manager_nid "51467";
    String cdm_data_type "Other";
    String comment 
"Total Organic Sulfur 
   R/V Knorr KN210-04 
  PI: Elizabeth Kujawinski (WHOI) 
  Co-PI: Krista Longnecker (WHOI) 
  Version date: 04 September 2018";
    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 "2018-09-04T21:13:03Z";
    String date_modified "2019-03-15T18:07:29Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.745536.1";
    Float64 Easternmost_Easting -28.502444;
    Float64 geospatial_lat_max 9.700333;
    Float64 geospatial_lat_min -37.998253;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -28.502444;
    Float64 geospatial_lon_min -55.29925;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 5108.562;
    Float64 geospatial_vertical_min 5.724;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-08T17:44:48Z (local files)
2024-11-08T17:44:48Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_745536.das";
    String infoUrl "https://www.bco-dmo.org/dataset/745536";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Whole seawater samples for obtaining the concentration of total organic sulfur (TOS) were collected directly from the Niskin bottles into combusted 40 mL glass vials.";
    String instruments_0_dataset_instrument_nid "745548";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends.  The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD.  Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_0_supplied_name "Niskin bottle";
    String instruments_1_acronym "Ion Chromatograph";
    String instruments_1_dataset_instrument_description "In brief, a sample is pumped through three ion exchange cartridges connected in series, a 1 mL Ba (Dionex OnGuard II #057093) to remove most of the sulfate, then through a 2.5 mL Ag (Dionex OnGuard II Ag #057090) to remove chloride, and finally through a 1 mL cartridge packed with BioRad AG 4x4 resin (#143-3341) to remove the remaining sulfate. The resulting sample is then analyzed via ion chromatography to quantify remaining sulfate.";
    String instruments_1_dataset_instrument_nid "745550";
    String instruments_1_description "Ion chromatography is a form of liquid chromatography that measures concentrations of ionic species by separating them based on their interaction with a resin. Ionic species separate differently depending on species type and size. Ion chromatographs are able to measure concentrations of major anions, such as fluoride, chloride, nitrate, nitrite, and sulfate, as well as major cations such as lithium, sodium, ammonium, potassium, calcium, and magnesium in the parts-per-billion (ppb) range. (from http://serc.carleton.edu/microbelife/research_methods/biogeochemical/ic.html)";
    String instruments_1_instrument_name "Ion Chromatograph";
    String instruments_1_instrument_nid "662";
    String instruments_1_supplied_name "ion chromatography";
    String keywords "bco, bco-dmo, biological, cast, chemical, data, dataset, date, date_utc_YYYYMMDD_start, depth, depth_m, dmo, erddap, event, event_start, hhmm, latitude, longitude, management, oceanography, office, preliminary, start, station, time, time_utc_HHMM_start, tos, TOS_nM, TOS_sd, yyyymmdd";
    String license "https://www.bco-dmo.org/dataset/745536/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/745536";
    Float64 Northernmost_Northing 9.700333;
    String param_mapping "{'745536': {'lon_start': 'flag - longitude', 'depth_m': 'flag - depth', 'lat_start': 'flag - latitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/745536/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Elizabeth Kujawinski";
    String people_0_person_nid "51089";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI";
    String people_1_person_name "Krista Longnecker";
    String people_1_person_nid "51483";
    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 "Krista Longnecker";
    String people_2_person_nid "51483";
    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 "Shannon Rauch";
    String people_3_person_nid "51498";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "Deep Atlantic DOM";
    String projects_0_acronym "Deep Atlantic DOM";
    String projects_0_description 
"Transformations of dissolved organic matter (DOM) in the deep ocean have profound impacts on the global carbon cycle due to the sequestration of carbon dioxide (CO2) away from the atmosphere.  Although research has been conducted on the high molecular weight component of this material, the same cannot be said for low molecular weight DOM because the needed analytical techniques have not been available to determine its composition and reactivity.
In recent years, a research team at Woods Hole Oceanographic Institution has acquired the necessary analytical capability. As such, in this project, they will carry out the first systematic survey of deep ocean DOM in the western Atlantic Ocean to characterize the low molecular weight fraction of DOM in southward flowing North Atlantic Deep Water (NADW), northward flowing Antarctic Bottom Water (AABW), and Antarctic Intermediate Water (AAIW).  Using ultrahigh resolution mass spectrometry and multi-stage fragmentation coupled to liquid chromatography, the scientists will determine the spatial variability in the composition of DOM along the flow path of the water masses, as well as assess the source water, transport, and surface processes that contribute to temporal changes in DOM composition.  These results will be augmented with structural elucidation and quantitative assays of unique marker compounds for each water mass.  Results will provide important insights into the biogeochemical reactions that govern DOM dynamics in the deep ocean.";
    String projects_0_end_date "2015-01";
    String projects_0_geolocation "Western Atlantic Ocean";
    String projects_0_name "Dissolved Organic Matter Composition in the Deep Atlantic Ocean";
    String projects_0_project_nid "2204";
    String projects_0_start_date "2012-02";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -37.998253;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "This dataset contains the concentration of total organic sulfur (TOS) in seawater from samples collected during the R/V Knorr cruise KN210-04 between 29 Mar 2013 and 06 May 2013 along the eastern coast of South America.";
    String title "[Total Organic Sulfur] - Total organic sulfur (TOS) collected from Niskin bottle samples on R/V Knorr cruise KN210-04 in the Western Atlantic Ocean between Uruguay and Barbados from March to May 2013 (Deep Atlantic DOM project) (Dissolved Organic Matter Composition in the Deep Atlantic Ocean)";
    String version "1";
    Float64 Westernmost_Easting -55.29925;
    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.

(easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
(easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
(not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
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.