BCO-DMO ERDDAP
Accessing BCO-DMO data

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Dataset Title:	[Parasite flow cytometry data] - Cell concentrations, percent of host infected, and bulk dissolved organic carbon (DOC) from laboratory experiments examining parasite-host metabolites in 2023 (Characterizing plankton parasite- host metabolites and the response of heterotrophic bacteria)
Institution:	BCO-DMO (Dataset ID: bcodmo_dataset_962736_v1)
Information:	Summary \| License \| 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 {
  Sample_name {
    String long_name "Sample_name";
    String units "unitless";
  }
  Infection_experiment {
    Int32 actual_range 4390, 4401;
    String long_name "Infection_experiment";
    String units "unitless";
  }
  Treatment {
    String long_name "Treatment";
    String units "unitless";
  }
  time_elapsed {
    Int32 actual_range 0, 4;
    String long_name "Time";
    String units "days";
  }
  Replicate {
    String long_name "Replicate";
    String units "unitless";
  }
  Date {
    String long_name "Date";
    String units "unitless";
  }
  Cell_concentration_host {
    Int32 actual_range 1240, 8160;
    String long_name "Cell_concentration_host";
    String units "Cells per ml (cells mL-1)";
  }
  Cell_concentration_spore {
    Float32 actual_range 23.6, 27400.0;
    String long_name "Cell_concentration_spore";
    String units "Cells per ml (cells mL-1)";
  }
  Percent_infected {
    Float32 actual_range 4.21, 42.49;
    String long_name "Percent_infected";
    String units "Percent infected hosts (%)";
  }
  DOC_concentration {
    Float32 actual_range 2.93, 5.38;
    String long_name "Doc_concentration";
    String units "Milligrams per liter (mg L-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 doi "10.26008/1912/bco-dmo.962736.1";
    String history 
"2025-06-24T14:35:23Z (local files)
2025-06-24T14:35:23Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_962736_v1.das";
    String infoUrl "https://osprey.bco-dmo.org/dataset/962736";
    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 "Laboratory experiments were carried out to characterize plankton infection dynamics and extracellular metabolites over an infection cycle in two parasite-host pairings. Data reported here are cell concentrations, percent of host infected, and bulk DOC concentrations measured daily over an infection cycle (four days) that coincides with collection of extracellular metabolites for analysis via liquid chromatography-mass spectrometry. Separate experiments were performed for two strains of the parasite Amoebophyra sp. (4390 and 4401) that infected the same host dinoflagellate species, Scrippsiella acuminata. Metabolomics data collected from these experiments will be available on MetaboLights (MTBLS11219).";
    String title "[Parasite flow cytometry data] - Cell concentrations, percent of host infected, and bulk dissolved organic carbon (DOC) from laboratory experiments examining parasite-host metabolites in 2023 (Characterizing plankton parasite-host metabolites and the response of heterotrophic bacteria)";
  }
}

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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