Accessing BCO-DMO data
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Dataset Title:  Acoustic backscatter from sites in McMurdo Sound from 2014-2015 (McMurdo
Predator Prey project)
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_715512)
Range: longitude = 165.06108 to 166.33482°E, latitude = -77.703186 to -77.5508°N, depth = 7.3439226 to 231.65654m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | 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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  site {
    String description "site name string";
    String ioos_category "Unknown";
    String long_name "Site";
    String units "unitless";
  sitenum {
    Float32 _FillValue NaN;
    Float32 actual_range 9.0, 258.0;
    String description "numerical representation of site";
    String ioos_category "Unknown";
    String long_name "Sitenum";
    String units "unitless";
  datetime {
    String description "date time of sampling; string with mm/dd/yyy hh:mm:ss";
    String ioos_category "Time";
    String long_name "Datetime";
    String source_name "datetime";
    String units "unitless";
  Group {
    String description "classification of backscatter;Krill = Crystal krill; Silverfish= Antarctic silverfish; LargeFish = unknown large fish; WeakScatterers = unknown scatterers generally < -70 dB re 1 m-1";
    String ioos_category "Unknown";
    String long_name "Group";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -77.70318638, -77.5508;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude of sampling station (positive is north)";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range 165.0610853, 166.3348293;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude of sampling station (positive is west)";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  dn {
    Float64 _FillValue NaN;
    Float64 actual_range 735560.1655, 735605.0763;
    String description "python matplotlib datenum; days since 0001-01-01 00:00:00 UTC";
    String ioos_category "Unknown";
    String long_name "DN";
    String units "days";
  sv_linear_sum {
    Float64 _FillValue NaN;
    Float64 actual_range 1.31e-7, 0.017623113;
    String description "sum of linear acoustic volume backscatter";
    String ioos_category "Unknown";
    String long_name "Sv Linear Sum";
    String units "m^-1";
  n {
    Int32 _FillValue 2147483647;
    Int32 actual_range 14, 123498;
    String description "number of classified volumes";
    String ioos_category "Statistics";
    String long_name "N";
    String units "unitless";
  effort {
    Int32 _FillValue 2147483647;
    Int32 actual_range 35133, 323949;
    String description "number of total surveyed volumes";
    String ioos_category "Unknown";
    String long_name "Effort";
    String units "unitess";
  sv_mean {
    Float64 _FillValue NaN;
    Float64 actual_range -90.84759626, -56.63791855;
    String description "mean volume backscatter of classified samples";
    String ioos_category "Statistics";
    String long_name "Sv Mean";
    String units "decibel at reference level 1 meter (dB re 1 m-1)";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 7.34392257, 231.6565411;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "mean depth of classified volume backscattering";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  sv_mean_effort {
    Float64 _FillValue NaN;
    Float64 actual_range -122.2160813, -70.11085932;
    String description "mean volume backscatter of survey station";
    String ioos_category "Statistics";
    String long_name "Sv Mean Effort";
    String units "decibel at reference level 1 meter (dB re 1 m-1)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description "\"\"";
    String awards_0_award_nid "665130";
    String awards_0_award_number "PLR-0944747";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0944747";
    String awards_0_funder_name "NSF Division of Polar Programs";
    String awards_0_funding_acronym "NSF PLR";
    String awards_0_funding_source_nid "490497";
    String awards_0_program_manager "Dr Chris H. Fritsen";
    String awards_0_program_manager_nid "50502";
    String awards_1_award_nid "665135";
    String awards_1_award_number "PLR-0944511";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0944511";
    String awards_1_funder_name "NSF Division of Polar Programs";
    String awards_1_funding_acronym "NSF PLR";
    String awards_1_funding_source_nid "490497";
    String awards_1_program_manager "Dr Chris H. Fritsen";
    String awards_1_program_manager_nid "50502";
    String awards_2_award_nid "665138";
    String awards_2_award_number "PLR-0944694";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0944694";
    String awards_2_funder_name "NSF Division of Polar Programs";
    String awards_2_funding_acronym "NSF PLR";
    String awards_2_funding_source_nid "490497";
    String awards_2_program_manager "Dr Chris H. Fritsen";
    String awards_2_program_manager_nid "50502";
    String cdm_data_type "Other";
    String comment 
"Mean acoustic backscatter by site from McMurdo Sound. 
  PI: Kendra Daly 
  Co-PI: Stacy Kim 
  Version: 2018-02-21";
    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.pl v1.0";
    String date_created "2017-09-25T14:44:26Z";
    String date_modified "2018-03-19T18:22:41Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.731147";
    Float64 Easternmost_Easting 166.3348293;
    Float64 geospatial_lat_max -77.5508;
    Float64 geospatial_lat_min -77.70318638;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 166.3348293;
    Float64 geospatial_lon_min 165.0610853;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 231.6565411;
    Float64 geospatial_vertical_min 7.34392257;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2019-06-16T03:26:29Z (local files)
2019-06-16T03:26:29Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_715512.das";
    String infoUrl "https://www.bco-dmo.org/dataset/715512";
    String institution "BCO-DMO";
    String instruments_0_acronym "ROV";
    String instruments_0_dataset_instrument_description "SCINI ROV (https://bitbucket.org/scinirov/scini/wiki/Home)";
    String instruments_0_dataset_instrument_nid "727522";
    String instruments_0_description "Remotely operated underwater vehicles (ROVs) are unoccupied, highly maneuverable underwater robots operated by a person aboard a surface vessel. They are linked to the ship by a group of cables that carry electrical signals back and forth between the operator and the vehicle. Most are equipped with at least a video camera and lights. Additional equipment is commonly added to expand the vehicle’s capabilities. These may include a still camera, a manipulator or cutting arm, water samplers, and instruments that measure water clarity, light penetration, and temperature. More information.";
    String instruments_0_instrument_name "Remotely Operated Vehicle";
    String instruments_0_instrument_nid "445";
    String instruments_0_supplied_name "SCINI ROV";
    String instruments_1_acronym "BioSonics DT-X Echosounder";
    String instruments_1_dataset_instrument_description "Biosonics, Inc. DT-X echosounder with 120 kHz split beam transducer";
    String instruments_1_dataset_instrument_nid "716064";
    String instruments_1_description "The BioSonics DT-X Digital Scientific Echosounder is available in single or spilt beam configuration. The resultant data set comprises 38 and 120 kHz split beam data.  The DT-X Digital Scientific Echosounder is used for stock assessment, biomass estimates, and habitat mapping. DT-X digital transducers are available in a range of frequencies (38, 70, 120, 200, and 420 kHz) and beam patterns in split beam or single beam. Up to 5 transducers can be mulltiplexed for simultaneous data collection in any combination of frequencies and transducer orientations. The BioSonics split beam echosounder data can be analyzed for fish quantity, individual sizes, direction of travel through the acoustic beam.  Data analysis is done using BioSonics, Echoview, or Sonar4/5-Pro software (and other options are available). Additional information is available from: BioSonics DT-X Digital Echosounder (http://www.biosonicsinc.com/product-overview.asp), BioSonics (http://www.biosonicsinc.com), Echoview (http://www.echoview.com/), and Sonar4/5-Pro (http://tid.uio.no/~hbalk/sonar4_5/index.htm).";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/FFES/";
    String instruments_1_instrument_name "BioSonics DT-X Digital Scientific Echosounder";
    String instruments_1_instrument_nid "646";
    String instruments_1_supplied_name "Biosonics, Inc. DT-X echosounder";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, datetime, depth, depth_mean, dmo, effort, erddap, group, latitude, linear, longitude, management, mean, oceanography, office, preliminary, site, sitenum, statistics, sum, sv_linear_sum, sv_mean, sv_mean_effort, time";
    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 metadata_source "https://www.bco-dmo.org/api/dataset/715512";
    Float64 Northernmost_Northing -77.5508;
    String param_mapping "{'715512': {'lat': 'flag - latitude', 'depth_mean': 'master - depth', 'lon': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/715512/parameters";
    String people_0_affiliation "University of South Florida";
    String people_0_affiliation_acronym "USF";
    String people_0_person_name "Dr Kendra L. Daly";
    String people_0_person_nid "50505";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "H.T. Harvey & Associates";
    String people_1_person_name "Dr David  G. Ainley";
    String people_1_person_nid "50491";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Point Blue Conservation Science";
    String people_2_person_name "Dr Grant Ballard";
    String people_2_person_nid "566872";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Moss Landing Marine Laboratories";
    String people_3_affiliation_acronym "MLML";
    String people_3_person_name "Dr Stacy Kim";
    String people_3_person_nid "51714";
    String people_3_role "Co-Principal Investigator";
    String people_3_role_type "originator";
    String people_4_affiliation "University of South Florida";
    String people_4_affiliation_acronym "USF";
    String people_4_person_name "Benjamin Saenz";
    String people_4_person_nid "715795";
    String people_4_role "Contact";
    String people_4_role_type "related";
    String people_5_affiliation "Woods Hole Oceanographic Institution";
    String people_5_affiliation_acronym "WHOI BCO-DMO";
    String people_5_person_name "Mathew Biddle";
    String people_5_person_nid "708682";
    String people_5_role "BCO-DMO Data Manager";
    String people_5_role_type "related";
    String project "Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound";
    String projects_0_acronym "McMurdo Predator Prey";
    String projects_0_description 
"Extracted from the NSF award abstract:
The research project investigates the importance of top down forcing on pelagic food webs. The relatively pristine Ross Sea includes large populations of upper-level predators such as minke and killer whales, Ad�lie and Emperor penguins, and Antarctic toothfish. This project focuses on food web interactions of Ad�lie penguins, minke whales, and the fish-eating Ross Sea killer whales, all of which exert foraging pressure on their main prey, crystal krill (Euphausia cyrstallorophias) and silver fish (Pleuragramma antarcticum) in McMurdo Sound.
The investigators used a video- and acoustic-capable ROV, and standard biological and environmental sensors to quantify the abundance and distribution of phytoplankton, sea ice biota, prey, and relevant habitat data.� The sampling area included 37 stations across an 30 x 15 km section of McMurdo Sound, stratified by distance from the ice edge as a proxy for air-breathing predator access. This study will be among the first to assess top-down forcing in the Ross Sea ecosystem and will form the basis for�multidisciplinary studies in the future.
Map sampling stations";
    String projects_0_end_date "2016-11";
    String projects_0_geolocation "McMurdo Sound, Antarctica";
    String projects_0_name "Food web dynamics in an intact ecosystem: the role of top predators in McMurdo Sound";
    String projects_0_project_nid "665131";
    String projects_0_project_website "https://scini-penguin.mlml.calstate.edu/pauls-wordpress-test-site/";
    String projects_0_start_date "2011-06";
    String publisher_name "Mathew Biddle";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -77.70318638;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary 
"Krill and fish were sampled acoustically and visually beneath the fast ice
using the tethered SCINI ROV, which was deployed and operated through a 25 cm
diameter hole drilled through the sea ice. SCINI contained cameras and
thrusters, and towed a sensor package consisting of a WET Labs fluorometer
(ECO-AFL/FL) and a single-beam Biosonics 120 kHz DT-X echosounder. Visual
targets were identified to the lowest taxon possible; these observations were
used primarily to verify classification of acoustic signals. The echosounder
operated at a nominal ping rate of 1 ping s-1; however, this rate was
occasionally adjusted if false bottom signals were observed. The general
profile of a dive included a surface transect of ~300 m horizontal distance,
where the acoustic transducer faced downward, and also a dive to ~120 m if
conditions allowed. Echogram data were saved to a depth of 500 m, and
background noise was removed. Given the effective range of the transducer of
approximately 100 m (resolving -80 dB targets), surveys characterized the
upper 200 m of the water column.";
    String title "Acoustic backscatter from sites in McMurdo Sound from 2014-2015 (McMurdo Predator Prey project)";
    String version "1";
    Float64 Westernmost_Easting 165.0610853;
    String xml_source "osprey2erddap.update_xml() v1.0-alpha";


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.

Tabledap request URLs must be in the form
For example,
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.

ERDDAP, Version 1.82
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