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Dataset Title:  [MIS_Midwater_Transect] - Abundance of Operational Taxonomic Units (OTU's)
from images collected by the ROV/SCINI along midwater transects under the
McMurdo Ice Shelf, Dec. 2008 (Development of a Remotely Operated Vehicle for
Under Sea Ice Research in Polar Environments)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_744693)
Range: longitude = 164.225 to 164.2433°E, latitude = -78.2233 to -78.2167°N
Information:  Summary ? | License ? | FGDC | 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 {
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -78.2233, -78.2167;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; north is positive";
    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 164.225, 164.2433;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; east is positive";
    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";
  }
  date {
    String bcodmo_name "date";
    String description "sampling date formatted as yyyy-mm-dd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    String axis "Z";
    String bcodmo_name "depth";
    String description "sampling depth range";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  replicate {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 2;
    String bcodmo_name "replicate";
    String description "replicate number";
    String long_name "Replicate";
    String units "unitless";
  }
  transect_length_m {
    Float32 _FillValue NaN;
    Float32 actual_range 9.05, 88.2;
    String bcodmo_name "len_track";
    String description "length of transect";
    String long_name "Transect Length M";
    String units "meters";
  }
  Mertensiidae {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.38;
    String bcodmo_name "abundance";
    String description "abundance of Mertensiidae along the transect as identified in SCINI images";
    String long_name "Mertensiidae";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "number/meter along transect";
  }
  white_streak {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.32;
    String bcodmo_name "abundance";
    String description "abundance of white streaks along the transect as identified in SCINI images";
    String long_name "White Streak";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "number/meter along transect";
  }
  Medusazoa {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.11;
    String bcodmo_name "abundance";
    String description "abundance of Medusazoa along the transect as identified in SCINI images";
    String long_name "Medusazoa";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "number/meter along transect";
  }
  white_dot {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.09;
    String bcodmo_name "abundance";
    String description "abundance of white dots along the transect as identified in SCINI images";
    String long_name "White Dot";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "number/meter along transect";
  }
  Euphausia {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.09;
    String bcodmo_name "abundance";
    String description "abundance of Euphausia along the transect as identified in SCINI images";
    String long_name "Euphausia";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "number/meter along transect";
  }
  pink_dot {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.04;
    String bcodmo_name "abundance";
    String description "abundance of pink dots along the transect as identified in SCINI images";
    String long_name "Pink Dot";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "number/meter along transect";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Sites are centered at 78\\u00b0 13.2\\u2019S, 164\\u00b0 14.1\\u2019E, from North
500 meters north of this location, and South 500 meters south of this
location, within the center of the barranca. The bottom depth was 188 m.
 
Depths are in meters.
 
Animal densities are reported as number per meter. Transect imagery was
collected with the ROV SCINI.\\u00a0 Organisms were identified to the lowest
possible taxon.";
    String awards_0_award_nid "743647";
    String awards_0_award_number "PLR-0619622";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0619622";
    String awards_0_funder_name "NSF Office of Polar Programs (formerly NSF PLR)";
    String awards_0_funding_acronym "NSF OPP";
    String awards_0_funding_source_nid "713360";
    String awards_0_program_manager "Dr Roberta Marinelli";
    String awards_0_program_manager_nid "51469";
    String cdm_data_type "Other";
    String comment 
"Transect imagery results from ROV SCINI: (OTU) Taxonomic abundance (individuals per meter) 
   McMurdo Ice Shelf Midwater Transect,  Dec. 2008 
   PI: S. Kim (MLML) 
   version: 2018-08-28";
    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 "2018-08-28T18:54:50Z";
    String date_modified "2019-12-02T22:11:37Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.744693.1";
    Float64 Easternmost_Easting 164.2433;
    Float64 geospatial_lat_max -78.2167;
    Float64 geospatial_lat_min -78.2233;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 164.2433;
    Float64 geospatial_lon_min 164.225;
    String geospatial_lon_units "degrees_east";
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-10-13T22:18:13Z (local files)
2024-10-13T22:18:13Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_744693.das";
    String infoUrl "https://www.bco-dmo.org/dataset/744693";
    String institution "BCO-DMO";
    String instruments_0_acronym "ROV";
    String instruments_0_dataset_instrument_description "Submersible Capable of under Ice Navigation and Imaging (SCINI) is a small, slender vehicle that can fit through a 20 cm hole in the ice, allowing for deployment without heavy drilling equipment and with minimal logistical support. Its maximum depth capability is 300 m. SCINI is equipped with two video cameras, scaling lasers, and lights, with forward speeds of up to 4 knots. SCINI uses Ethernet over power on a 400 m long two-wire tether. A long baseline acoustic positioning system is used for navigation which uses a combination of two to four acoustic transducers hanging below the ice and a synchronized pinger on the vehicle for positional accuracy of better than 1 meter. [See Cazenave, F, R Zook, D Carroll, M Flagg, S Kim.  2011.  Development of the ROV SCINI and deployment in McMurdo Sound, Antarctica.  Journal of Ocean Technology 6(3):39-58.]";
    String instruments_0_dataset_instrument_nid "744696";
    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 "ROV/SCINI";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, date, depth, depth_m, dmo, dot, erddap, euphausia, latitude, length, longitude, management, medusazoa, mertensiidae, oceanography, office, pink, pink_dot, preliminary, replicate, streak, time, transect, transect_length_m, white, white_dot, white_streak";
    String license "https://www.bco-dmo.org/dataset/744693/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/744693";
    Float64 Northernmost_Northing -78.2167;
    String param_mapping "{'744693': {'lat': 'master - latitude', 'lon': 'master - longitude', 'depth_m': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/744693/parameters";
    String people_0_affiliation "Moss Landing Marine Laboratories";
    String people_0_affiliation_acronym "MLML";
    String people_0_person_name "Dr Stacy Kim";
    String people_0_person_nid "51714";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "SCINI";
    String projects_0_acronym "SCINI";
    String projects_0_description 
"NSF Award Abstract:
In marine habitats worldwide, the zone between scuba-diving depths (to 40 m) and surge-free depths (below 200 m) has been poorly studied. Under ice-covered seas, wave motion is minimal to nonexistent, and the zone between 40 and 200 m is accessible to ROVs. Polar marine research has the benefit of stable sea ice platforms for staging and deploying instruments like ROVs, but this requires a hole that is, fo rmost ROVs, a meter in diameter. This proposal develops an ROV that can be deployed through a 15 cm hole that can be drilled with a hand-held power head, requiring minimal logistical support and technical expertise. The new ROV provides access to regions that remain unstudied, expanding our scientific reach and ability to address new questions. We will develop, test, and modify the ROV while accomplishing several overlapping and interdependent science objectives, including (1) exploration and documentation of rates and patterns of ecological succession from one of the most extreme coastal habitats in the world, (2) a survey of two unique benthic habitats and communities beyond scuba diving depths (at 40-170 m), which are almost completely unknown to most researchers and assembly of individual photographs into high-resolution images of the seafloor and (3) testing of protocols for conducting sonar mapping and creating high resolution continuous bathymetric maps of the entire seafloor around McMurdo Station. The ROV will be constructed as modules; this allows flexibility to change the ROV capabilities to suit different missions. Some components can be purchased off the shelf (e.g. VideoRay high resolution and low light video cameras), but may require development of some custom integration software. Power is provided from the surface via a 2 conductor tether; bi-directional high speed data is modulated on the tether as well, providing 84 mbs of data and unlimited dive duration. The topside controls consist of a laptop computer and joystick for the pilot. Many of the control functions and display screens could be accessed via the Internet for educational demonstrations and interactions. Two graduate students will participate fully in the project. Several other Antarctic scientists have indicated a strong interest in utilizing this tool in their research and it will be available to a pool of users on completion of the project.";
    String projects_0_end_date "2010-01";
    String projects_0_geolocation "McMurdo Sound, McMurdo Ice Shelf";
    String projects_0_name "Development of a Remotely Operated Vehicle for Under Sea Ice Research in Polar Environments";
    String projects_0_project_nid "743648";
    String projects_0_start_date "2007-02";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -78.2233;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Abundance of Operational Taxonomic Units (OTU's) from images collected by the ROV/SCINI along midwater transects under the McMurdo Ice Shelf, Dec. 2008";
    String title "[MIS_Midwater_Transect] - Abundance of Operational Taxonomic Units (OTU's) from images collected by the ROV/SCINI along midwater transects under the McMurdo Ice Shelf, Dec. 2008 (Development of a Remotely Operated Vehicle for Under Sea Ice Research in Polar Environments)";
    String version "1";
    Float64 Westernmost_Easting 164.225;
    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.

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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