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Dataset Title:	SOOS - ICE-LAPSE: Analysis of Antarctic benthos
Institution:	CNR-ISMAR (Dataset ID: ICE-LAPSE)
Range:	longitude = 164.10388 to 164.10388°E, latitude = -74.69017 to -74.69017°N, depth = 20.0 to 20.0m, time = 2017-01-23T23:15:14.000Z to 2017-11-15T19:44:38.000Z
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Subset \| 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:

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 {
  title {
    String long_name "Title";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.485213314e+9, 1.510775078e+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 "1970-01-01T00:00:00.000Z";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 20, 20;
    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";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range -74.690167, -74.690167;
    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";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range 164.103889, 164.103889;
    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";
  }
  url {
    String long_name "Url";
  }
 }
  NC_GLOBAL {
    String campaign "Deployment in Tethys bay - Mario Zucchelli Station- 2015";
    String cdm_data_type "Point";
    String citation "Marini, S., Bonofiglio, F., Corgnati, L.P. et al. Long-term High Resolution Image Dataset of Antarctic Coastal Benthic Fauna. Sci Data 9, 750 (2022). https://doi.org/10.1038/s41597-022-01865-7";
    String contact "simone.marini@cnr.it; andrea.peirano@enea.it; federico.bonofiglio@sp.ismar.cnr.it; stefano.schiaparelli@unige.it";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String copyright "contact simone.marini@cnr.it";
    String Dataset_DOI "10.5281/zenodo.731853";
    Float64 Easternmost_Easting 164.103889;
    String featureType "Point";
    Float64 geospatial_lat_max -74.690167;
    Float64 geospatial_lat_min -74.690167;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 164.103889;
    Float64 geospatial_lon_min 164.103889;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 20.0;
    Float64 geospatial_vertical_min 20.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-05-20T12:01:37Z (local files)
2024-05-20T12:01:37Z https://erddap.sochic-h2020.eu/tabledap/ICE-LAPSE.das";
    String illumination "mixed light";
    String image_sensor "GUARD1-PNRA-2015";
    String image_set_handle "https://hdl.handle.net/20.500.12085/ee277578-a911-484d-a515-9c781d79aa91@7f60d428-c696-4e1a-bbee-d54038e3cb75";
    String infoUrl "https://doi.org/10.1038/s41597-022-01865-7";
    String institution "CNR-ISMAR";
    String license "CC-BY";
    Float64 Northernmost_Northing -74.690167;
    String ORCID "Simone Marini:0000-0003-0665-7815; Andrea Peirano:0000-0001-8847-1760; Federico Bonofiglio:0000-0003-4085-9840; Stefano Schiaparelli:0000-0002-0137-3605";
    String pi "Simone Marini simone.marini@cnr.it 0000-0003-0665-7815";
    String project "ICE-LAPSE: Analysis of Antarctic benthos dynamics by using non-destructive monitoring devices and permanent stations, PNRA 2013/AZ1.16, funded by the Italian National Antarctic Program";
    String Pubblication_DOI "https://doi.org/10.1038/s41597-022-01865-7";
    String reference_system "EPSG:4326";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -74.690167;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String subsetVariables "depth, latitude, longitude";
    String summary "Long-term dataset consisting of 755 images, with fixed field of view, of Antarctic coastal benthic fauna acquired by using a non-invasive, autonomous imaging device. Antarctica is a remote place, the continent is covered by ice and its surrounding coastal areas are frozen for the majority of the year. Due to its peculiarity the observation of the underwater organisms is particularly difficult, complicated by logistic factors. We present a long-term dataset consisting of 755 images acquired by using a non-invasive, autonomous imaging device and encompassing both the Antarctic daylight and dark periods, including the corresponding transition phases. All images have the same field of view showing the benthic fauna and part of the water column above, including fishes present in the monitored period. All the images are manually annotated after a visual inspection performed by expert biologists. The extended monitoring period and the annotated images make the dataset a valuable benchmark suitable for studying the dynamics of the long-term Antarctic underwater fauna as well as for developing and testing algorithms for automated image analysis focused on the recognition and classification of the Antarctic organisms and the automated analysis of their long-term dynamics.";
    String time_coverage_end "2017-11-15T19:44:38.000Z";
    String time_coverage_start "2017-01-23T23:15:14.000Z";
    String title "SOOS - ICE-LAPSE: Analysis of Antarctic benthos";
    Float64 Westernmost_Easting 164.103889;
  }
}

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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