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Dataset Title:  [Cyanobacteria cultures used to generate DNA reference library] -
Cyanobacteria cultures used to generate DNA reference library from samples
collected from sites in Alpena and Monroe, Michigan and Palm Coast, Florida
between May and June 2022. (Collaborative Research: RUI: OCE-BO: Tango in the
Mat World: Biogeochemistry of diurnal vertical migration in microbial mats of
Lake Huron’s sinkholes)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_911338_v1)
Range: longitude = -83.32506 to -83.32453°E
Information:  Summary ? | License ? | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
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Constraints ? Optional
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Constraint #2 ?
       
       
       
       
       
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
 
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    [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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  NCBI_Accession {
    String long_name "Ncbi_accession";
    String units "unitless";
  }
  Culture_ID {
    String long_name "Culture_id";
    String units "unitless";
  }
  Genus {
    String long_name "Genus";
    String units "unitless";
  }
  Species {
    String long_name "Species";
    String units "unitless";
  }
  Media {
    String long_name "Media";
    String units "unitless";
  }
  Collection_Date {
    String long_name "Collection_date";
    String units "unitless";
  }
  Location {
    String long_name "Location";
    String units "unitless";
  }
  Sample_Type {
    String long_name "Sample_type";
    String units "unitless";
  }
  Lat {
    Float32 actual_range 45.08542, 45.19839;
    String long_name "Lat";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -83.32506, -83.32453;
    String axis "X";
    String ioos_category "Location";
    String long_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  }
 }
  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.911338.1";
    Float64 Easternmost_Easting -83.32453;
    Float64 geospatial_lon_max -83.32453;
    Float64 geospatial_lon_min -83.32506;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T06:11:18Z (local files)
2024-11-08T06:11:18Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_911338_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/911338";
    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 
"These data are the information for each of the cultures generated from samples collected from three sites in Alpena, Michigan, one site in Monroe, Michigan, and one site in Palm Coast, Florida. Data are for cultures sequenced using Sanger sequencing and include taxonomic identification, location and sample type for samples used to develop the cultures.
Each of these cultures was developed from high-sulfur, low-oxygen environments formed by underwater sinkholes and springs that create extreme habitats populated by microbial mat communities. Our study investigated previously undescribed diatom diversity in these habitats. Sequences from these cultures contribute to tying molecular data to morphologically identified isolates, providing a bridge between these two data types that can be used to improve metabarcoding analyses.";
    String title "[Cyanobacteria cultures used to generate DNA reference library] - Cyanobacteria cultures used to generate DNA reference library from samples collected from sites in Alpena and Monroe, Michigan and Palm Coast, Florida between May and June 2022. (Collaborative Research: RUI: OCE-BO: Tango in the Mat World: Biogeochemistry of diurnal vertical migration in microbial mats of Lake Huron’s sinkholes)";
    Float64 Westernmost_Easting -83.32506;
  }
}

 

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.

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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