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Dataset Title:	Salmon length, weight, sex, stomach data from F/V Great Pacific, R/V Miller Freeman multiple cruises in the Coastal Gulf of Alaska, NE Pacific from 2001- 2004 (NEP project)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_3106)
Range:	longitude = -157.43 to -137.2°E, latitude = 54.29 to 60.04°N
Information:	Summary \| License \| 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 {
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2001, 2004;
    String bcodmo_name "year";
    String description "year, reported as YYYY, e.g. 1995";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "dimensionless";
  }
  transect {
    String bcodmo_name "transect";
    String description "Transect name.";
    String long_name "Transect";
    String units "dimensionless";
  }
  sta_id {
    String bcodmo_name "sta_id";
    String description "Station identification.";
    String long_name "Sta Id";
    String units "dimensionless";
  }
  haul_id {
    Int32 _FillValue 2147483647;
    Int32 actual_range 2001001, 2004031;
    String bcodmo_name "haul identification";
    String description "First four numbers represent year, second four numbers represent haul number.";
    String long_name "Haul Id";
    String units "dimensionless";
  }
  month_local {
    String bcodmo_name "month_local";
    String description "month of year, local time";
    String long_name "Month Local";
    String units "dimensionless";
  }
  day_local {
    String bcodmo_name "day_local";
    String description "day of month, local time";
    String long_name "Day Local";
    String units "dimensionless";
  }
  yrday_local {
    Int16 _FillValue 32767;
    Int16 actual_range 198, 313;
    String bcodmo_name "yrday_local";
    String description "Local day and decimal time, as 326.5 for the 326th day of the year, or November 22 at 1200 hours (noon).";
    String long_name "Yrday Local";
    String units "dimensionless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 54.29, 60.04;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude, in decimal degrees, North is positive, negative denotes South.";
    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";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -157.43, -137.2;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude, in decimal degrees, East is positive, negative denotes West.";
    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";
  }
  depth_w {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 10000.0;
    String bcodmo_name "depth_w";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "water depth";
    String long_name "Depth";
    String standard_name "depth";
    String units "meters";
  }
  species_common_name {
    String bcodmo_name "species";
    String description "common name of fish species";
    String long_name "Species Common Name";
    String units "dimensionless";
  }
  length_froz {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 446;
    String bcodmo_name "length";
    String description "length of frozen fish from front tip to fork of tail";
    String long_name "Length Froz";
    String units "?";
  }
  length_wet {
    Int16 _FillValue 32767;
    Int16 actual_range 37, 2673;
    String bcodmo_name "length";
    String description "length of wet fish";
    String long_name "Length Wet";
    String units "?";
  }
  weight_froz {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 1231;
    String bcodmo_name "weight";
    String description "weight of frozen fish";
    String long_name "Weight Froz";
    String units "grams";
  }
  weight_wet {
    Int32 _FillValue 2147483647;
    Int32 actual_range 2, 44442;
    String bcodmo_name "weight";
    String description "weight of wet fish - pre-frozen";
    String long_name "Weight Wet";
    String units "grams";
  }
  sex {
    String bcodmo_name "sex";
    String description "Male (m), Female (f), Immature (i)";
    String long_name "Sex";
    String units "dimensionless";
  }
  maturity {
    String bcodmo_name "stage";
    String description "Status of maturity: adult (A), juvenile (J), immature (I).";
    String long_name "Maturity";
    String units "dimensionless";
  }
  stomwt_full {
    Byte _FillValue 127;
    Byte actual_range 0, 3;
    String bcodmo_name "unknown";
    String description "Stomach weight while full.";
    String long_name "Stomwt Full";
    String units "grams";
  }
  stomwt_empty {
    Byte _FillValue 127;
    Byte actual_range 0, 1;
    String bcodmo_name "unknown";
    String description "empty stomach weight";
    String long_name "Stomwt Empty";
    String units "?";
  }
  sealice {
    Byte _FillValue 127;
    Byte actual_range 0, 68;
    String bcodmo_name "unknown";
    String description "number of parasitic sea lice found on body";
    String long_name "Sealice";
    String units "dimensionless";
  }
  comments {
    String bcodmo_name "comment";
    String description "comments pertaining to sample";
    String long_name "Comments";
    String units "dimensionless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Fish samples were collected with a 198-m-long mid-water rope trawl with
hexagonal mesh wings and body, and a 1.2-cm mesh liner in the codend (Fig. 2,
Table 1). The rope trawl was towed at 3.5 to 5 kt, at or near surface, and had
a typical spread of 40-m horizontally and 14-m vertically. All tows lasted 30
minutes and covered 1.5 to 2.8 nautical miles. All fish sampling was done
during daylight hours. Sometimes this meant that salmon trawls preceded CTD
casts. For reference, sunrise occurred at 06:04 ADT and sunset at 22:27 ADT on
1 August 2003 at 58o N. Alaska Daylight Time (ADT) is 8 hours earlier than
Greenwich Mean Time (GMT).
 
[Station map](\\\\\"http://globec.whoi.edu/images/nep/NEP_GoA-
ltop_station_map.jpg\\\\\") from the GP0108 cruise report.";
    String awards_0_award_nid "54767";
    String awards_0_award_number "OCE-0109078";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0109078";
    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 "Phillip R. Taylor";
    String awards_0_program_manager_nid "50451";
    String awards_1_award_nid "55044";
    String awards_1_award_number "unknown NEP NOAA";
    String awards_1_funder_name "National Oceanic and Atmospheric Administration";
    String awards_1_funding_acronym "NOAA";
    String awards_1_funding_source_nid "352";
    String cdm_data_type "Other";
    String comment 
"Salmon Biodata 2001-2004 
  P.I.: E. Cokelet (U. Alaska - Fairbanks) 
  Gulf of Alaska";
    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 "2010-06-16T20:40:39Z";
    String date_modified "2020-01-20T18:04:24Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.3106.1";
    Float64 Easternmost_Easting -137.2;
    Float64 geospatial_lat_max 60.04;
    Float64 geospatial_lat_min 54.29;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -137.2;
    Float64 geospatial_lon_min -157.43;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-04-16T19:41:31Z (local files)
2024-04-16T19:41:31Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_3106.das";
    String infoUrl "https://www.bco-dmo.org/dataset/3106";
    String institution "BCO-DMO";
    String instruments_0_acronym "TrawlMid";
    String instruments_0_dataset_instrument_description "Fish samples were collected with a 198-m-long mid-water rope trawl  with hexagonal mesh wings and body, and a 1.2-cm mesh liner in the  codend. The rope trawl was towed at 3.5 to 5 kt, at or near surface, and  had a typical spread of 40-m horizontally and 14-m vertically.";
    String instruments_0_dataset_instrument_nid "5395";
    String instruments_0_description 
"A mid-water or pelagic trawl is a net towed at a chosen depth in the water column to catch schooling fish such as herring and mackerel.  Midwater trawl nets have very large front openings to herd schooling fish toward the back end where they become trapped in the narrow \"broiler\".  The sides of the deployed net are spread horizontally with two large metal foils, called \"doors,\" positioned in front of the net. As the trawler moves forward, the doors, and therefore the net, are forced outward, keeping the net open.
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/23/";
    String instruments_0_instrument_name "Midwater Trawl";
    String instruments_0_instrument_nid "467";
    String instruments_0_supplied_name "Midwater Trawl";
    String keywords "bco, bco-dmo, biological, chemical, comments, common, data, dataset, day, day_local, depth, depth_w, dmo, empty, erddap, froz, full, haul, haul_id, latitude, length, length_froz, length_wet, local, longitude, management, maturity, month, month_local, name, oceanography, office, preliminary, sealice, sex, species, species_common_name, sta, sta_id, stomwt, stomwt_empty, stomwt_full, transect, weight, weight_froz, weight_wet, wet, year, yrday, yrday_local";
    String license "https://www.bco-dmo.org/dataset/3106/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/3106";
    Float64 Northernmost_Northing 60.04;
    String param_mapping "{'3106': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/3106/parameters";
    String people_0_affiliation "National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center";
    String people_0_affiliation_acronym "NOAA-AFSC-Auke";
    String people_0_person_name "Dr Alex  C Wertheimer";
    String people_0_person_nid "51053";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "National Oceanic and Atmospheric Administration";
    String people_1_affiliation_acronym "NOAA-PMEL";
    String people_1_person_name "Dr Edward  D. Cokelet";
    String people_1_person_nid "50466";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center";
    String people_2_affiliation_acronym "NOAA-AFSC-Auke";
    String people_2_person_name "Dr Edward  V. Farley";
    String people_2_person_nid "50465";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "University of Washington";
    String people_3_affiliation_acronym "UW";
    String people_3_person_name "Dr Jamal  Hasan Moss";
    String people_3_person_nid "50467";
    String people_3_role "Scientist";
    String people_3_role_type "originator";
    String people_4_affiliation "National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center";
    String people_4_affiliation_acronym "NOAA-AFSC-Auke";
    String people_4_person_name "Dr Jamal  Hasan Moss";
    String people_4_person_nid "50467";
    String people_4_role "Scientist";
    String people_4_role_type "originator";
    String people_5_affiliation "University of Washington";
    String people_5_affiliation_acronym "UW";
    String people_5_person_name "Dr Jamal  Hasan Moss";
    String people_5_person_nid "50467";
    String people_5_role "Contact";
    String people_5_role_type "related";
    String people_6_affiliation "National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center";
    String people_6_affiliation_acronym "NOAA-AFSC-Auke";
    String people_6_person_name "Dr Jamal  Hasan Moss";
    String people_6_person_nid "50467";
    String people_6_role "Contact";
    String people_6_role_type "related";
    String people_7_affiliation "Woods Hole Oceanographic Institution";
    String people_7_affiliation_acronym "WHOI BCO-DMO";
    String people_7_person_name "Nancy Copley";
    String people_7_person_nid "50396";
    String people_7_role "BCO-DMO Data Manager";
    String people_7_role_type "related";
    String project "NEP";
    String projects_0_acronym "NEP";
    String projects_0_description 
"Program in a Nutshell
Goal:  To understand the effects of climate variability and climate change on the distribution, abundance and production of marine animals (including commercially important living marine resources) in the eastern North Pacific. To embody this understanding in diagnostic and prognostic ecosystem models, capable of capturing the ecosystem response to major climatic fluctuations.
Approach: To study the effects of past and present climate variability on the population ecology and population dynamics of marine biota and living marine resources, and to use this information as a proxy for how the ecosystems of the eastern North Pacific may respond to future global climate change. The strong temporal variability in the physical and biological signals of the NEP will be used to examine the biophysical mechanisms through which zooplankton and salmon populations respond to physical forcing and biological interactions in the coastal regions of the two gyres. Annual and interannual variability will be studied directly through long-term observations and detailed process studies; variability at longer time scales will be examined through retrospective analysis of directly measured and proxy data. Coupled biophysical models of the ecosystems of these regions will be developed and tested using the process studies and data collected from the long-term observation programs, then further tested and improved by hindcasting selected retrospective data series.";
    String projects_0_geolocation "Northeast Pacific Ocean, Gulf of Alaska";
    String projects_0_name "U.S. GLOBEC Northeast Pacific";
    String projects_0_project_nid "2038";
    String projects_0_project_website "http://nepglobec.bco-dmo.org";
    String projects_0_start_date "1997-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 54.29;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Salmon length, weight, sex, stomach data from F/V Great Pacific, R/V Miller Freeman multiple cruises in the Coastal Gulf of Alaska, NE Pacific from 2001-2004.";
    String title "Salmon length, weight, sex, stomach data from F/V Great Pacific, R/V Miller Freeman multiple cruises in the Coastal Gulf of Alaska, NE Pacific from 2001-2004 (NEP project)";
    String version "1";
    Float64 Westernmost_Easting -157.43;
    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.