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Dataset Title:	[BAIT phytoplankton element quotas] - Element quotas of individual phytoplankton cells from four Bermuda Atlantic Iron Time-Series (BAIT) cruises in 2019 (NSFGEO-NERC: Collaborative Research: Using Time-series Field Observations to Constrain an Ocean Iron Model)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_956540_v1)
Range:	depth = 20.0 to 100.0m
Information:	Summary \| License \| 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 {
  aps_run {
    String long_name "Aps_run";
    String units "unitless";
  }
  MDA {
    Int32 actual_range 24, 262;
    String long_name "Mda";
    String units "unitless";
  }
  Cruise {
    String long_name "Cruise";
    String units "unitless";
  }
  Station {
    String long_name "Station";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 20, 100;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth_m";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Depth {
    String long_name "Depth";
    String units "unitless";
  }
  Vol {
    Float32 actual_range 0.1308013, 393.2453;
    String long_name "Vol";
    String units "cubic micrometers (um3)";
  }
  cellC_mol {
    Float32 actual_range 2.67e-15, 4.92e-12;
    String long_name "Cellc_mol";
    String units "moles (mol)";
  }
  log_Si_C {
    Float32 actual_range 3.209304, 6.536352;
    String long_name "Log_si_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_Fe_C {
    Float32 actual_range 0.5381657, 2.739822;
    String long_name "Log_fe_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_Cu_C {
    Float32 actual_range -0.3896792, 3.041633;
    String long_name "Log_cu_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_Zn_C {
    Float32 actual_range 0.1724571, 3.197726;
    String long_name "Log_zn_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_P_C {
    Float32 actual_range 1.324579, 4.191729;
    String long_name "Log_p_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_S_C {
    Float32 actual_range 2.665315, 5.586447;
    String long_name "Log_s_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_Mn_C {
    Float32 actual_range -0.8870736, 1.807162;
    String long_name "Log_mn_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_Co_C {
    Float32 actual_range -0.3993578, 1.217228;
    String long_name "Log_co_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_Ni_C {
    Float32 actual_range -1.508705, 1.861199;
    String long_name "Log_ni_c";
    String units "micromoles per mole (umol/mol)";
  }
  log_C_P {
    Float32 actual_range 1.808272, 4.675421;
    String long_name "Log_c_p";
    String units "moles per mole (mol/mol)";
  }
  flag_C_P {
    Int32 actual_range 1, 9;
    String long_name "Flag_c_p";
    String units "unitless";
  }
  flag_Fe_C {
    Int32 actual_range 1, 9;
    String long_name "Flag_fe_c";
    String units "unitless";
  }
  flag_Zn_C {
    Int32 actual_range 1, 9;
    String long_name "Flag_zn_c";
    String units "unitless";
  }
  flag_Mn_C {
    Int32 actual_range 1, 9;
    String long_name "Flag_mn_c";
    String units "unitless";
  }
  flag_Ni_C {
    Int32 actual_range 1, 9;
    String long_name "Flag_ni_c";
    String units "unitless";
  }
  flag_Co_C {
    Int32 actual_range 1, 9;
    String long_name "Flag_co_c";
    String units "unitless";
  }
  flag_Cu_C {
    Int32 actual_range 1, 9;
    String long_name "Flag_cu_c";
    String units "unitless";
  }
  bf_image_filename {
    String long_name "Bf_image_filename";
    String units "unitless";
  }
  maps_filename {
    String long_name "Maps_filename";
    String units "unitless";
  }
  spectra_filename {
    String long_name "Spectra_filename";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.956540.1";
    Float64 geospatial_vertical_max 100.0;
    Float64 geospatial_vertical_min 20.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2025-06-06T17:21:19Z (local files)
2025-06-06T17:21:19Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_956540_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/956540";
    String institution "BCO-DMO";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String sourceUrl "(local files)";
    String summary "Individual phytoplankton cells were collected on four cruises (March, May, August, and November 2019) as part of the Bermuda Atlantic Iron Time-Series (BAIT) Project. The elemental (Si, P, S, Mn, Fe, Co, Ni, Cu, Zn) content of each cell was measured with synchrotron x-ray fluorescence (SXRF). Carbon was calculated from biovolume. These data can be used to assess biogenic particulate metal fraction, as well as changes in the accumulation of these elements across seasons.";
    String title "[BAIT phytoplankton element quotas] - Element quotas of individual phytoplankton cells from four Bermuda Atlantic Iron Time-Series (BAIT) cruises in 2019 (NSFGEO-NERC: Collaborative Research: Using Time-series Field Observations to Constrain an Ocean Iron Model)";
  }
}

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.

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