ERDDAP > tabledap > Make A Graph

Dataset Title:	ECoSS - DB of enhanced4AI sounds - METADATA
Institution:	ECoSS project   (Dataset ID: ecoss_db_enhanced4AI_sounds_metadata)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks vectors X Axis:  longitude latitude Enhanced4AI Test Train N_channels amplification_gain system_frequency hydrophone_number sensitivity depth EDMO Bathymetric_Depth Y Axis:  longitude latitude Enhanced4AI Test Train N_channels amplification_gain system_frequency hydrophone_number sensitivity depth EDMO Bathymetric_Depth Color:  longitude latitude Enhanced4AI Test Train N_channels amplification_gain system_frequency hydrophone_number sensitivity depth EDMO Bathymetric_Depth   Constraints Optional Constraint #1 Optional Constraint #2 UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path     != =~ <= >= = < >     != =~ <= >= = < > UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path     != =~ <= >= = < >     != =~ <= >= = < > UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path     != =~ <= >= = < >     != =~ <= >= = < > UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path     != =~ <= >= = < >     != =~ <= >= = < > UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path     != =~ <= >= = < >     != =~ <= >= = < >   Server-side Functions  distinct() orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path UniqueID longitude latitude File Enhanced4AI Test Train Label_source Label_class Label_description Label_type Recorder Recorder_no N_channels amplification_gain startdate system_frequency hydrophone hydrophone_number sensitivity depth Campaign EDMO CountryCode Bathymetric_Depth file_folder file_path ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle Borderless Filled Square Borderless Filled Circle Borderless Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid EK80  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Draw land mask:  under over outline off Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .parquet .parquetWMeta .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

Click on the map to specify a new center point. Zoom:

 

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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.
   

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  UniqueID {
    String ioos_category "Identifier";
    String long_name "Unique ID";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  File {
    String ioos_category "Unknown";
    String long_name "File";
  }
  Enhanced4AI {
    Int32 _FillValue 2147483647;
    Int32 actual_range 1, 1;
    String ioos_category "Unknown";
    String long_name "enhanced4AI";
  }
  Test {
    Int32 _FillValue 2147483647;
    Int32 actual_range 0, 1;
    String ioos_category "Unknown";
    String long_name "Original Audio File Test";
  }
  Train {
    Int32 _FillValue 2147483647;
    Int32 actual_range 0, 1;
    String ioos_category "Unknown";
    String long_name "Original Audio File Train";
  }
  Label_source {
    String ioos_category "Unknown";
    String long_name "Label Source";
  }
  Label_class {
    String ioos_category "Unknown";
    String long_name "Label Class";
  }
  Label_description {
    String ioos_category "Unknown";
    String long_name "Label Description";
  }
  Label_type {
    String ioos_category "Unknown";
    String long_name "Label Type";
  }
  Recorder {
    String ioos_category "Taxonomy";
    String long_name "Recorder";
  }
  Recorder_no {
    String ioos_category "Taxonomy";
    String long_name "Recorder No";
  }
  N_channels {
    Int32 _FillValue 2147483647;
    String ioos_category "Statistics";
    String long_name "N Channels";
  }
  amplification_gain {
    Float32 _FillValue NaN;
    String ioos_category "Unknown";
    String long_name "Amplification Gain";
  }
  startdate {
    String ioos_category "Unknown";
    String long_name "Startdate";
  }
  system_frequency {
    Float32 _FillValue NaN;
    String ioos_category "Unknown";
    String long_name "System Frequency";
  }
  hydrophone {
    String ioos_category "Unknown";
    String long_name "Hydrophone";
  }
  hydrophone_number {
    Int32 _FillValue 2147483647;
    Int32 colorBarMaximum 100000;
    Int32 colorBarMinimum 0;
    String ioos_category "Statistics";
    String long_name "Hydrophone Number";
  }
  sensitivity {
    Float32 _FillValue NaN;
    String ioos_category "Unknown";
    String long_name "Sensitivity";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 _FillValue NaN;
    String axis "Z";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Campaign {
    String ioos_category "Unknown";
    String long_name "Campaign";
  }
  EDMO {
    Int32 _FillValue 2147483647;
    Int32 actual_range 2764, 2764;
    String ioos_category "Unknown";
    String long_name "EDMO";
  }
  CountryCode {
    String ioos_category "Location";
    String long_name "Country Code";
  }
  Bathymetric_Depth {
    Float64 _FillValue NaN;
    String ioos_category "Bathymetry";
    String long_name "Bathymetric Depth";
  }
  file_folder {
    String ioos_category "Unknown";
    String long_name "File Folder";
  }
  file_path {
    String ioos_category "Unknown";
    String long_name "File Path";
  }
 }
  NC_GLOBAL {
    String annotation_procedure "https://ssc.s4oceandata.eu/Document_standards_annotations.pdf";
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.10, ACDD-1.3";
    String geospatial_lat_units "degrees_north";
    String geospatial_lon_units "degrees_east";
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2025-02-05T09:56:45Z (local files)
2025-02-05T09:56:45Z https://ssc.s4oceandata.eu/tabledap/ecoss_db_enhanced4AI_sounds_metadata.das";
    String infoUrl "https://ecoss.ctnaval.com/";
    String institution "ECoSS project";
    String keywords "amplification, amplification_gain, audio, bathymetric, Bathymetric_Depth, bathymetry, campaign, channels, check, code, compressed, contact, count, country, CountryCode, data, dataset, date, depth, duration, file, floor, format, frequency, gain, hydrophone, hydrophone_number, identifier, institution, label, LabelClass, LabelDescription, LabelSource, LabelType, latitude, local, longitude, max, merged, metadata, metadata_quality, min, N_channels, name, noise, noise_floor, number, owner, path, quality, rate, recorder, sample, sample_width, sensitivity, signal, sound, source, start, start_time, startdate, station, statistics, system, system_frequency, table, test, time, train, type, width, zone";
    String license "Creative Commons Attribution Share-Alike http://www.opendefinition.org/licenses/cc-by-sa";
    String project "The primary goal of the ECoSS project is to develop an open library containing a curated and continuously growing digital catalogue, along with an AI-based classifier for individual sound signatures from the marine underwater soundscape in shallow waters (CINEA/2022/OP/0019).";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "This database is dedicated to synthetic sounds, i.e. real sounds that have been cut and pasted to create clean sources for AI training. These soundtracks consist of real underwater acoustic emissions repeated twice, already labelled and with fixed features such as sampling rate, duration, and signal-to-noise ratio (S/N). The synthetic sounds database served as the primary training dataset.";
    String title "ECoSS - DB of enhanced4AI sounds - METADATA";
  }
}

 

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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 Data Access Protocol (DAP) and its selection constraints.

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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