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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)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
Event_No (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"20220131.1147.001"	"20220302.1411.001"
time (Iso_datetime_utc, UTC)	!= =~ <= >= = < >		!= =~ <= >= = < >		2022-01-31T11:47:00Z	2022-03-02T14:11:00Z
Date (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2022-01-31"	"2022-03-02"
time_unitless (Time, unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"00:02"	"23:51"
latitude (degrees_north)	!= =~ <= >= = < >		!= =~ <= >= = < >		-17.17	-13.0028
longitude (degrees_east)	!= =~ <= >= = < >		!= =~ <= >= = < >		113.9674	121.5028
Tow (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		1	189
Net_Type (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Bongo90"	"Widow"
Mesh (microns)	!= =~ <= >= = < >		!= =~ <= >= = < >		505	1000
Side (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"L"	"R"
depth (Tow_depth, m)	!= =~ <= >= = < >		!= =~ <= >= = < >		1.0	42.0
Tow_Vol (cubic meters (m3))	!= =~ <= >= = < >		!= =~ <= >= = < >		362	1244
Sample_ID (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"D04943"	"D05544"
Cycle (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		1	4
Sample_Status (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"All (ship, lab 1/4)"	"Tunas (ship, lab)"
SBT_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	137
ALB_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	27
YFT_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	15
BET_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	2
Thun_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	29
SKJ_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	7
Tuna_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		1	163
Fish_Count (individuals)	!= =~ <= >= = < >		!= =~ <= >= = < >		7	804
SBT_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	194.6
ALB_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	40.8
YFT_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	27.8
BET_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	4.2
Thun_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	55.2
SKJ_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	11.4
Tuna_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		1.7	227.0
Fish_1000m3 (individuals per 1000 cubic meters)	!= =~ <= >= = < >		!= =~ <= >= = < >		14.1	1256.2

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" Event_No time Date time_unitless latitude longitude Tow Net_Type Mesh Side depth Tow_Vol Sample_ID Cycle Sample_Status SBT_Count ALB_Count YFT_Count BET_Count Thun_Count SKJ_Count Tuna_Count Fish_Count SBT_1000m3 ALB_1000m3 YFT_1000m3 BET_1000m3 Thun_1000m3 SKJ_1000m3 Tuna_1000m3 Fish_1000m3 Event_No time Date time_unitless latitude longitude Tow Net_Type Mesh Side depth Tow_Vol Sample_ID Cycle Sample_Status SBT_Count ALB_Count YFT_Count BET_Count Thun_Count SKJ_Count Tuna_Count Fish_Count SBT_1000m3 ALB_1000m3 YFT_1000m3 BET_1000m3 Thun_1000m3 SKJ_1000m3 Tuna_1000m3 Fish_1000m3 Event_No time Date time_unitless latitude longitude Tow Net_Type Mesh Side depth Tow_Vol Sample_ID Cycle Sample_Status SBT_Count ALB_Count YFT_Count BET_Count Thun_Count SKJ_Count Tuna_Count Fish_Count SBT_1000m3 ALB_1000m3 YFT_1000m3 BET_1000m3 Thun_1000m3 SKJ_1000m3 Tuna_1000m3 Fish_1000m3 Event_No time Date time_unitless latitude longitude Tow Net_Type Mesh Side depth Tow_Vol Sample_ID Cycle Sample_Status SBT_Count ALB_Count YFT_Count BET_Count Thun_Count SKJ_Count Tuna_Count Fish_Count SBT_1000m3 ALB_1000m3 YFT_1000m3 BET_1000m3 Thun_1000m3 SKJ_1000m3 Tuna_1000m3 Fish_1000m3 Event_No time Date time_unitless latitude longitude Tow Net_Type Mesh Side depth Tow_Vol Sample_ID Cycle Sample_Status SBT_Count ALB_Count YFT_Count BET_Count Thun_Count SKJ_Count Tuna_Count Fish_Count SBT_1000m3 ALB_1000m3 YFT_1000m3 BET_1000m3 Thun_1000m3 SKJ_1000m3 Tuna_1000m3 Fish_1000m3 ")

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each response column becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .kml - View a .kml file, suitable for Google Earth. .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

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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 "&time<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 
"2025-06-24T08:40:02Z (local files)
2025-06-24T08:40:02Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_958726_v1.html";
    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;
  }
}

 

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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 Data Access Protocol (DAP) and its selection constraints.

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.
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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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