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Dataset Title:	EMSO Western Ligurian : Albatross mooring, MICROCAT sensor (CSV 2015-2016)
Institution:	MIO UMR 7294 CNRS / OSU Pytheas (Dataset ID: Emso_Western_Ligurian_Albatross_Microcat_CSV_2015)
Range:	time = 2015-06-05T07:39Z to 2016-06-05T05:14Z
Information:	Summary \| License \| Metadata \| Background \| Subset \| Data Access Form \| Files

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Graph Type:

X Axis:

Y Axis:

Color:

Constraints

Optional
Constraint #1

Optional
Constraint #2

Server-side Functions

distinct()

Hover here to see a list of options. Click on an option to select it.

Graph Settings

Marker Type:

Size:

Color:

Color Bar:

Continuity:

Scale:

Minimum:

Maximum:

N Sections:

Y Axis Minimum:

Maximum:

(Please be patient. It may take a while to get the data.)

Optional:
Then set the File Type: (File Type information)
and

or view the URL:
(Documentation / Bypass this form

)

Time range:

[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:

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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.43348994e+9, 1.46510364e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  ID {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 21, 25;
    String ioos_category "Identifier";
    String long_name "ID";
  }
  DEPH {
    Float32 actual_range 1500.0, 2300.0;
    String ioos_category "Unknown";
    String long_name "DEPH";
  }
  PRES {
    Float32 actual_range 1510.73, 2355.793;
    String ioos_category "Pressure";
    String long_name "Pressure";
  }
  TEMP {
    Float32 actual_range 13.1374, 13.2768;
    String ioos_category "Temperature";
    String long_name "Temperature";
  }
  CNDC {
    Float32 actual_range 45.3923, 45.929;
    String ioos_category "Unknown";
    String long_name "CNDC";
  }
  DOX1 {
    Float32 actual_range 1.905, 9.368;
    String ioos_category "Unknown";
    String long_name "DOX1";
  }
  TPOT {
    Float64 actual_range 12.901295, 12.99994718;
    String ioos_category "Unknown";
    String long_name "TPOT";
  }
  DOX2 {
    Float64 actual_range 85.0750268, 418.36;
    String ioos_category "Unknown";
    String long_name "DOX2";
  }
  PSAL {
    Float64 actual_range 38.16046873, 38.62756103;
    String ioos_category "Unknown";
    String long_name "PSAL";
  }
  DENS {
    Float64 actual_range 28.86296162, 29.22373819;
    String ioos_category "Unknown";
    String long_name "DENS";
  }
 }
  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 
"2024-10-30T05:42:56Z (local files)
2024-10-30T05:42:56Z http://erddap.osupytheas.fr/tabledap/Emso_Western_Ligurian_Albatross_Microcat_CSV_2015.das";
    String infoUrl "http://www.emso-fr.org/EMSO-France";
    String institution "MIO UMR 7294 CNRS / OSU Pytheas";
    String keywords "2015-2016, albatross, cndc, cnrs, conductivity, csv, ctd, data, dens, deph, depth, dox1, dox2, emso, identifier, ligurian, microcat, mio, mooring, oregon, osu, PRES, pressure, psal, pytheas, sensor, sonde, state, TEMP, temperature, time, tpot, umr, university, western";
    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 "ID, DEPH";
    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 "2016-06-05T05:14Z";
    String time_coverage_start "2015-06-05T07:39Z";
    String title "EMSO Western Ligurian : Albatross mooring, MICROCAT sensor (CSV 2015-2016)";
  }
}

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.

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