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Dataset Title:  EMSO Western Ligurian : Albatross mooring, AQUADOPP sensor (CSV 2018-2019) Subscribe RSS
Institution:  MIO UMR 7294 CNRS / OSU Pytheas   (Dataset ID: Emso_Western_Ligurian_Albatross_Aquadopp_CSV_2018)
Range: time = 2018-05-19T10:00:00Z to 2019-05-17T04:00:00Z
Information:  Summary ? | License ? | Metadata | Background (external link) | Subset | Data Access Form | Files
 
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Constraints ? Optional
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Server-side Functions ?
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? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
 
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[The graph you specified. Please be patient.]

 

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 {
  Id {
    String ioos_category "Identifier";
    String long_name "Id";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.526724e+9, 1.5580656e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Date";
    String source_name "Date";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  Depth {
    Float32 actual_range 450.0, 2400.0;
    String ioos_category "Unknown";
    String long_name "Depth";
  }
  X_East {
    Float32 actual_range -0.223, 0.143;
    String ioos_category "Location";
    String long_name "X East";
  }
  Y_North {
    Float32 actual_range -0.175, 0.124;
    String ioos_category "Location";
    String long_name "Y North";
  }
  Z_Up {
    Float32 actual_range -0.084, 0.066;
    String ioos_category "Location";
    String long_name "Z Up";
  }
  Amplitude_X {
    Float32 actual_range 46.0, 149.0;
    String ioos_category "Location";
    String long_name "Amplitude X";
  }
  Amplitude_Y {
    Float32 actual_range 47.0, 133.0;
    String ioos_category "Location";
    String long_name "Amplitude Y";
  }
  Amplitude_Z {
    Float32 actual_range 46.0, 125.0;
    String ioos_category "Location";
    String long_name "Amplitude Z";
  }
  Batterie {
    Float32 actual_range 11.3, 13.6;
    String ioos_category "Unknown";
    String long_name "Batterie";
  }
  SoundSpeed {
    Float32 actual_range 1512.5, 1545.0;
    String ioos_category "Currents";
    String long_name "Sound Speed";
  }
  Heading {
    Float32 actual_range 0.0, 359.9;
    String ioos_category "Unknown";
    String long_name "Heading";
  }
  Pitch {
    Float32 actual_range -9.0, 1.3;
    String ioos_category "Unknown";
    String long_name "Pitch";
  }
  Roll {
    Float32 actual_range -5.4, 3.2;
    String ioos_category "Unknown";
    String long_name "Roll";
  }
  Pressure {
    Float32 actual_range 447.564, 2391.743;
    String ioos_category "Pressure";
    String long_name "Pressure";
  }
  Temperature {
    Float32 actual_range 13.1, 13.91;
    String ioos_category "Temperature";
    String long_name "Temperature";
  }
  Speed {
    Float32 actual_range 0.0, 0.238;
    String ioos_category "Currents";
    String long_name "Speed";
  }
  Direction {
    Float32 actual_range 0.0, 359.46;
    Float64 colorBarMaximum 360.0;
    Float64 colorBarMinimum 0.0;
    String ioos_category "Currents";
    String long_name "Direction";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_name "MIO UMR 7294 CNRS / OSU Pytheas";
    String creator_type "institution";
    String creator_url "http://www.emso-fr.org/EMSO-France";
    String history 
"2024-04-15T15:51:14Z (local files)
2024-04-15T15:51:14Z http://erddap.osupytheas.fr/tabledap/Emso_Western_Ligurian_Albatross_Aquadopp_CSV_2018.das";
    String infoUrl "http://www.emso-fr.org/EMSO-France";
    String institution "MIO UMR 7294 CNRS / OSU Pytheas";
    String keywords "2018-2019, albatross, amplitude, Amplitude_X, Amplitude_Y, Amplitude_Z, aquadopp, batterie, cnrs, conductivity, csv, ctd, currents, data, date, depth, direction, east, emso, heading, identifier, ligurian, mio, mooring, north, oregon, osu, pitch, pressure, pytheas, roll, sensor, sonde, sound, SoundSpeed, speed, state, temperature, time, umr, university, western, X_East, Y_North, Z_Up";
    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 sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "Depth";
    String summary "The European Multidisciplinary Seafloor and water column Observatory (EMSO) is a research infrastructure distributed throughout Europe for seabed and water column observatories. It aims to further explore the oceans, better understand the phenomena that occur on the seabed, and elucidate the critical role that these phenomena play in global Earth systems. This observatory is based on observation sites (or nodes) that have been deployed in strategic locations in European seas, from the Arctic to the Atlantic, from the Mediterranean to the Black Sea. There are currently eleven deep water nodes plus four shallow water test nodes. EMSO Western Ligurian is one of these permanent underwater observatories located in the Ligurian Sea and is deployed off Toulon, France. This region was chosen for its particular scientific interests such as: seismicity, topography, turbidity, biodiversity, water mass dynamics and organic matter flow. This underwater observation network is also part of KM3NeT (https://www.km3net.org/) which has a modular topology designed to connect up to 120 neutrino detection units. Earth and Sea Science (ESS) instrumentation connected to KM3NeT is based on two complementary components: an instrumented interface module (MII) and an autonomous instrumented line (ALBATROSS). The ALBATROSS line is an inductive line (2000 m) composed of an acoustic communication system, two inductive cables equipped with Conductivity, Temperature, Depth (CTD)-O2 sensors, current meters and two instrumented buoys. This line is deployed at a distance of 2-3 kilometers from the MII, and communication on land is done by an acoustic link with the MII, and electro-optical cable via the KM3NeT node.";
    String time_coverage_end "2019-05-17T04:00:00Z";
    String time_coverage_start "2018-05-19T10:00:00Z";
    String title "EMSO Western Ligurian : Albatross mooring, AQUADOPP sensor (CSV 2018-2019)";
  }
}

 

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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