BCO-DMO ERDDAP
Accessing BCO-DMO data

Make A Graph

Dataset Title:	[PXMI - Phytoplankton cell count data] - Phytoplankton cell count data from laboratory cultures of Crocosphaera watsonii, Micromonas commoda, Prochlorococcus marinus, Synechococcus, Gephyrocapsa huxleyi, and Thalassiosira pseudonana collected from September to December 2022 (Phytoplankton Exometabolites)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_991400_v1)
Information:	Summary \| License \| Metadata \| Background \| 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

)

[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 {
  species {
    String long_name "Species";
    String units "unitless";
  }
  strain {
    String long_name "Strain";
    String units "unitless";
  }
  day {
    Int32 actual_range 1, 16;
    String long_name "Day";
    String units "unitless";
  }
  replicate {
    Int32 actual_range 1, 10;
    String long_name "Replicate";
    String units "unitless";
  }
  RFUs {
    Float32 actual_range 1.29, 585.94;
    String long_name "Rfus";
    String units "unitlesss";
  }
  cells_per_mL {
    Float32 actual_range 533000.0, 2.6e+8;
    String long_name "Cells_per_ml";
    String units "cells per milliliter";
  }
 }
  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 doi "10.26008/1912/bco-dmo.991400.1";
    String history 
"2026-03-05T06:34:51Z (local files)
2026-03-05T06:34:51Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_991400_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/991400";
    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.";
    String sourceUrl "(local files)";
    String summary "Phytoplankton cell count data from laboratory cultures of Crocosphaera watsonii WH8501, Micromonas commoda RCC299, Prochlorococcus MIT9301, Synechococcus WH8102, Gephyrocapsa huxleyi CCMP371, and Thalassiosira pseudonana CCMP1335. Cultures were harvested during the exponential growth phase. Cell count data were used to determine growth rates, and data are used in support of exometabolite data harvested from these cultures (available at BCO-DMO project 984095). Cell count data were collected by Hanna Anderson and Eli Salcedo.";
    String title "[PXMI - Phytoplankton cell count data] - Phytoplankton cell count data from laboratory cultures of Crocosphaera watsonii, Micromonas commoda, Prochlorococcus marinus, Synechococcus, Gephyrocapsa huxleyi, and Thalassiosira pseudonana collected from September to December 2022 (Phytoplankton Exometabolites)";
  }
}

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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