Make A Graph

Dataset Title:	Summary presence/absence maps of macro-endobenthos in the greater North Sea, based on nearly 100,000 samples from 65 assembled monitoring data sets
Institution:	Deltares (Dataset ID: biology_benthos_6617_5e82_1108_e2c8)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Files

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Graph Type:
X Axis:
Y Axis:
Color:

Dimensions

Start

Stop

aphiaid (level)

specify just 1 value →

latitude (degrees_north)

longitude (degrees_east)

Graph Settings
Color Bar:	Continuity:	Scale:
Minimum:	Maximum:	N Sections:
Draw land mask:
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

)

Click on the map to specify a new center point.

Zoom:

[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 {
  aphiaid {
    Int32 actual_range 145, 1417307;
    String long_name "Life Science Identifier - World Register of Marine Species";
    String units "level";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 46.03571428571429, 65.96428571428571;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -15.916666666666666, 8.916666666666664;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  probability_occurrence {
    Float64 _FillValue -99999.9;
    String long_name "Probability of occurrence of biological entity";
    Float64 missing_value -99999.9;
  }
  NC_GLOBAL {
    String acknowledgement "European Marine Observation Data Network (EMODnet) Biology project (EASME/EMFF/2017/1.3.1.2/02/SI2.789013), funded by the European Union under Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund";
    String cdm_data_type "Grid";
    String citation "Herman, P.M.J., Stolte, W., van der Heijden, L. 2020. Summary presence/absence maps of macro-endobenthos in the greater North Sea, based on nearly 100,000 samples from 65 assembled monitoring data sets.";
    String comment "Uses attributes recommended by https://cfconventions.org";
    String Conventions "CF-1.8, COARDS, ACDD-1.3";
    String creator_email "peter.herman@deltares.nl";
    String creator_institution "Deltares";
    String creator_name "Peter Herman";
    String creator_type "person";
    String creator_url "www.deltares.nl";
    String date_created "2022-08-17";
    String date_issued "2020-12-24";
    String date_metadata_modified "2021-04-12";
    String date_modified "2021-04-12";
    Float64 Easternmost_Easting 8.916666666666664;
    Float64 geospatial_lat_max 65.96428571428571;
    Float64 geospatial_lat_min 46.03571428571429;
    Float64 geospatial_lat_resolution 0.07142857142857138;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 8.916666666666664;
    Float64 geospatial_lon_min -15.916666666666666;
    Float64 geospatial_lon_resolution 0.16666666666666663;
    String geospatial_lon_units "degrees_east";
    String grid_mapping_geographic_crs_name "WGS 84";
    String grid_mapping_GeoTransform "-180 0.08333333333333333 0 90 0 -0.08333333333333333";
    Float64 grid_mapping_inverse_flattening 298.257223563;
    String grid_mapping_long_name "Coordinate Reference System";
    Float64 grid_mapping_longitude_of_prime_meridian 0.0;
    String grid_mapping_name "latitude_longitude";
    String grid_mapping_prime_meridian_name "Greenwich";
    String grid_mapping_reference_ellipsoid_name "WGS 84";
    Float64 grid_mapping_semi_major_axis 6378137.0;
    Float64 grid_mapping_semi_minor_axis 6356752.314245179;
    String grid_mapping_spatial_ref "GEOGCS[\"WGS 84\",DATUM[\"WGS_1984\",SPHEROID[\"WGS 84\",6378137,298.257223563]],PRIMEM[\"Greenwich\",0],UNIT[\"degree\",0.0174532925199433,AUTHORITY[\"EPSG\",\"9122\"]],AXIS[\"Latitude\",NORTH],AXIS[\"Longitude\",EAST],AUTHORITY[\"EPSG\",\"4326\"]]";
    String history 
"https://github.com/EMODnet/EMODnet-Biology-Benthos_greater_North_Sea
2025-10-25T09:43:27Z (local files)
2025-10-25T09:43:27Z https://erddap.emodnet.eu/griddap/biology_benthos_6617_5e82_1108_e2c8.das";
    String infoUrl "https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=6617";
    String institution "Deltares";
    String keywords "absence, aphiaid, assembled, based, benthos, biological, data, deltares, endobenthos, entity, greater, macro, macro-endobenthos, maps, marine, marine ecology, marine/coastal, monitoring, nearly, north, north sea, occurrence, presence, probability, probability_occurrence, samples, sea, sets, summary";
    String license "CC-BY";
    String metadata_link "https://www.emodnet-biology.eu/data-catalog?module=dataset&dasid=6617";
    String naming_authority "emodnet-biology.eu";
    Float64 Northernmost_Northing 65.96428571428571;
    String product_version "1";
    String project "EMODnet-Biology";
    String publisher_email "bio@emodnet.eu";
    String publisher_institution "Flanders Marine Institute (VLIZ)";
    String publisher_name "EMODnet Biology Data Management Team";
    String publisher_type "group";
    String publisher_url "www.emodnet-biology.eu";
    String references "https://www.emodnet-biology.eu/blog/summary-presenceabsence-maps-macro-endobenthos-greater-north-sea";
    String sea_name "North Sea";
    String source "https://github.com/EMODnet/EMODnet-Biology-Benthos_greater_North_Sea";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 46.03571428571429;
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "The large databases of EMODNET Biology only store confirmed presences of species. However, when mapping species distribution, it is also important where the species did not occur: there is at least as much information in absences as in presences. Inferring absences from presence-only databases is difficult and always involves some guesswork. In this product we have used as much meta-information as possible to guide us in inferring absences.";
    String title "Summary presence/absence maps of macro-endobenthos in the greater North Sea, based on nearly 100,000 samples from 65 assembled monitoring data sets";
    Float64 Westernmost_Easting -15.916666666666666;
  }
}

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link)

Data Access Protocol (DAP) (external link)

and its projection 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. It makes 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.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2002-06-01T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.