BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[BLOOFINZ-IO Larval tuna counts and abundances] - Larval fish counts and larval tuna counts with corresponding plankton net type and geographic coordinates from R/V Roger Revelle cruise RR2201 (BLOOFINZ-IO, January-March 2022) in the Argo Basin region off NW Australia (Collaborative Research: Mesoscale variability in nitrogen sources and food-web dynamics supporting larval southern bluefin tuna in the eastern Indian Ocean)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_958726_v1)
Range:	longitude = 113.9674 to 121.5028°E, latitude = -17.17 to -13.0028°N, depth = 1.0 to 42.0m, time = 2022-01-31T11:47:00Z to 2022-03-02T14:11:00Z
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 {
  Event_No {
    String long_name "Event_no";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.64362962e+9, 1.64623026e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Date {
    String long_name "Date";
    String units "unitless";
  }
  time_unitless {
    String long_name "Time";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range -17.17, -13.0028;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 113.9674, 121.5028;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Tow {
    Int32 actual_range 1, 189;
    String long_name "Tow";
    String units "unitless";
  }
  Net_Type {
    String long_name "Net_type";
    String units "unitless";
  }
  Mesh {
    Int32 actual_range 505, 1000;
    String long_name "Mesh";
    String units "microns";
  }
  Side {
    String long_name "Side";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 1.0, 42.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Tow_depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Tow_Vol {
    Int32 actual_range 362, 1244;
    String long_name "Tow_vol";
    String units "cubic meters (m3)";
  }
  Sample_ID {
    String long_name "Sample_id";
    String units "unitless";
  }
  Cycle {
    Int32 actual_range 1, 4;
    String long_name "Cycle";
    String units "unitless";
  }
  Sample_Status {
    String long_name "Sample_status";
    String units "unitless";
  }
  SBT_Count {
    Int32 actual_range 0, 137;
    String long_name "Sbt_count";
    String units "individuals";
  }
  ALB_Count {
    Int32 actual_range 0, 27;
    String long_name "Alb_count";
    String units "individuals";
  }
  YFT_Count {
    Int32 actual_range 0, 15;
    String long_name "Yft_count";
    String units "individuals";
  }
  BET_Count {
    Int32 actual_range 0, 2;
    String long_name "Bet_count";
    String units "individuals";
  }
  Thun_Count {
    Int32 actual_range 0, 29;
    String long_name "Thun_count";
    String units "individuals";
  }
  SKJ_Count {
    Int32 actual_range 0, 7;
    String long_name "Skj_count";
    String units "individuals";
  }
  Tuna_Count {
    Int32 actual_range 1, 163;
    String long_name "Tuna_count";
    String units "individuals";
  }
  Fish_Count {
    Int32 actual_range 7, 804;
    String long_name "Fish_count";
    String units "individuals";
  }
  SBT_1000m3 {
    Float32 actual_range 0.0, 194.6;
    String long_name "Sbt_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  ALB_1000m3 {
    Float32 actual_range 0.0, 40.8;
    String long_name "Alb_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  YFT_1000m3 {
    Float32 actual_range 0.0, 27.8;
    String long_name "Yft_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  BET_1000m3 {
    Float32 actual_range 0.0, 4.2;
    String long_name "Bet_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  Thun_1000m3 {
    Float32 actual_range 0.0, 55.2;
    String long_name "Thun_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  SKJ_1000m3 {
    Float32 actual_range 0.0, 11.4;
    String long_name "Skj_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  Tuna_1000m3 {
    Float32 actual_range 1.7, 227.0;
    String long_name "Tuna_1000m3";
    String units "individuals per 1000 cubic meters";
  }
  Fish_1000m3 {
    Float32 actual_range 14.1, 1256.2;
    String long_name "Fish_1000m3";
    String units "individuals per 1000 cubic meters";
  }
 }
  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 defaultDataQuery "&amp;time&lt;now";
    String doi "10.26008/1912/bco-dmo.958726.1";
    Float64 Easternmost_Easting 121.5028;
    Float64 geospatial_lat_max -13.0028;
    Float64 geospatial_lat_min -17.17;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 121.5028;
    Float64 geospatial_lon_min 113.9674;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 42.0;
    Float64 geospatial_vertical_min 1.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2025-06-24T08:09:27Z (local files)
2025-06-24T08:09:27Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_958726_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/958726";
    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.";
    Float64 Northernmost_Northing -13.0028;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -17.17;
    String summary "This dataset contains larval fish counts and larval tuna counts with corresponding plankton net type and geographic coordinates from cruise RR2201 of R/V Roger Revelle (BLOOFINZ-IO, January-March 2022) in the Argo Basin region off northwestern Australia.";
    String time_coverage_end "2022-03-02T14:11:00Z";
    String time_coverage_start "2022-01-31T11:47:00Z";
    String title "[BLOOFINZ-IO Larval tuna counts and abundances] - Larval fish counts and larval tuna counts with corresponding plankton net type and geographic coordinates from R/V Roger Revelle cruise RR2201 (BLOOFINZ-IO, January-March 2022) in the Argo Basin region off NW Australia (Collaborative Research: Mesoscale variability in nitrogen sources and food-web dynamics supporting larval southern bluefin tuna in the eastern Indian Ocean)";
    Float64 Westernmost_Easting 113.9674;
  }
}

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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