BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[Polysaccharide Hydrolase Activities under Varying Hydrostatic Pressures near Helsingor in 2023] - Polysaccharide Hydrolase Activities in Danish Coastal Seawater and Sediments under Varying Hydrostatic Pressures on samples collected in September 2023 (Collaborative Research: Pressure effects on microbially- catalyzed organic matter degradation in the deep ocean)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_963382_v1)
Range:	longitude = 12.685 to 12.685°E, latitude = 55.975 to 55.975°N, depth = 20.0 to 26.0m, time = 2023-09-26T07:50:00Z to 2023-09-26T07:50:00Z
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| 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 {
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 55.975, 55.975;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 12.685, 12.685;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.6957146e+9, 1.6957146e+9;
    String axis "T";
    String ioos_category "Time";
    String long_name "Iso_datetime_utc";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  date {
    String long_name "Date";
    String units "unitless";
  }
  time_local_CEST {
    String long_name "Time_local_cest";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 20, 26;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth_actual";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  sample_type {
    String long_name "Sample_type";
    String units "unitless";
  }
  in_situ_T {
    Int32 actual_range 9, 13;
    String long_name "In_situ_t";
    String units "degrees Celsius";
  }
  in_situ_S {
    Float32 actual_range 32.5, 32.5;
    String long_name "In_situ_s";
    String units "psu";
  }
  incubation_T {
    Int32 actual_range 4, 4;
    String long_name "Incubation_t";
    String units "degrees Celsius";
  }
  unamended_amended {
    String long_name "Unamended_amended";
    String units "unitless";
  }
  pressure {
    Float32 actual_range 0.1, 40.0;
    String long_name "Pressure";
    String units "MPa";
  }
  substrate {
    String long_name "Substrate";
    String units "unitless";
  }
  timepoint_number {
    Int32 actual_range 0, 3;
    String long_name "Timepoint_number";
    String units "unitless";
  }
  timepoint_days {
    Int32 actual_range 0, 22;
    String long_name "Timepoint_days";
    String units "days";
  }
  rate_x_kc {
    Float32 actual_range 0.0, 0.0;
    String long_name "Rate_x_kc";
    String units "nmol L-1 hr-1";
  }
  rate_1_kc {
    Float32 actual_range 0.0, 255.5819;
    String long_name "Rate_1_kc";
    String units "nmol L-1 hr-1";
  }
  rate_2_kc {
    Float32 actual_range 0.0, 590.739;
    String long_name "Rate_2_kc";
    String units "nmol L-1 hr-1";
  }
  rate_3_kc {
    Float32 actual_range 0.0, 598.7959;
    String long_name "Rate_3_kc";
    String units "nmol L-1 hr-1";
  }
  rate_mean_kc {
    Float32 actual_range 0.0, 481.7056;
    String long_name "Rate_mean_kc";
    String units "nmol L-1 hr-1";
  }
  rate_sd_kc {
    Float32 actual_range 0.0, 199.1731;
    String long_name "Rate_sd_kc";
    String units "nmol L-1 hr-1";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.26008/1912/bco-dmo.963382.1";
    Float64 Easternmost_Easting 12.685;
    Float64 geospatial_lat_max 55.975;
    Float64 geospatial_lat_min 55.975;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 12.685;
    Float64 geospatial_lon_min 12.685;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 26.0;
    Float64 geospatial_vertical_min 20.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2025-08-25T16:27:26Z (local files)
2025-08-25T16:27:26Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_963382_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/963382";
    String institution "BCO-DMO";
    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.";
    Float64 Northernmost_Northing 55.975;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 55.975;
    String summary 
"The potential of the seawater or sedimentary microbial community to hydrolyze seven high-molecular-weight polysaccharides (arabinogalactan, chondroitin sulfate, fucoidan, laminarin, mannan, pullulan, and xylan) was investigated in a coastal station off the coast of Helsingor, Denmark. This investigation was part of the larger project to understand pressure effects on enzymatic activity. These samples were collected in September 2023 at a coastal station off the coast of Helsingor, Denmark, at a depth of 20 meters. 

Through our collaboration with the Danish Center for Hadal Research, we were able to use pressurization systems and in situ specialized equipment to investigate the effects of pressures characteristic of bathy- and abyssopelagic depths on microbial communities and their extracellular enzymes in the open North Atlantic Ocean.   

This dataset contains metadata on sample collection, environmental conditions, sample types and treatments, incubation conditions, substrate types, and kill-corrected enzymatic hydrolysis rates across timepoints.";
    String time_coverage_end "2023-09-26T07:50:00Z";
    String time_coverage_start "2023-09-26T07:50:00Z";
    String title "[Polysaccharide Hydrolase Activities under Varying Hydrostatic Pressures near Helsingor in 2023] - Polysaccharide Hydrolase Activities in Danish Coastal Seawater and Sediments under Varying Hydrostatic Pressures on samples collected in September 2023 (Collaborative Research: Pressure effects on microbially-catalyzed organic matter degradation in the deep ocean)";
    Float64 Westernmost_Easting 12.685;
  }
}

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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