ERDDAP > tabledap > Data Access Form

Dataset Title:	[Microbial diversity survey Axial Seamount 2023] - Metabarcoding data from microbial diversity survey at Axial Seamount aboard the R/V Thompson cruise TN420 in Jul 2022 and Jul 2023 (Characterizing and quantifying the impact of phagotrophic protists at hot spots of primary production at Axial Seamount)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_969102_v1)
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
Accession (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"SAMN48384644"	"SAMN48384733"
Sample_Name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"AXIAL_22_103_CTD00..."	"AXIAL_23_202_CTD00..."
NCBI_Organism_Name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"hydrothermal vent ..."	"hydrothermal vent ..."
NCBI_Tax_ID (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"652676"	"652676"
BioProject (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"PRJNA1259551"	"PRJNA1259551"
dive_ctd (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"CTD002"	"J21506"
site_name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"ASHES"	"Vixen"
collection_method (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"CTD"	"UFO"
sample_type (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"background"	"vent"
filter (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"GFF"	"sterivex"
processing (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"INSITU"	"SHIPBOARD"
primer (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"16S"	"CTRL"
target_population (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"microeukaryote"	"prokaryote"
location_name (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"ASHES"	"Vixen"
depth_category (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"30m above"	"under plume"
depth (m)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1540
fluid_origin (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"1434HSF15"	"shipboard"
AXIAL_YEAR (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"AXIAL_22"	"AXIAL_23"
latitude (degrees_north)	!= =~ <= >= = < >		!= =~ <= >= = < >		45.91623	45.93359
longitude (Long, degrees_east)	!= =~ <= >= = < >		!= =~ <= >= = < >		-130.0495	-129.9791
DATE (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2022-07-09"	"2023-07-25"

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" Accession Sample_Name NCBI_Organism_Name NCBI_Tax_ID BioProject dive_ctd site_name collection_method sample_type filter processing primer target_population location_name depth_category depth fluid_origin AXIAL_YEAR latitude longitude DATE Accession Sample_Name NCBI_Organism_Name NCBI_Tax_ID BioProject dive_ctd site_name collection_method sample_type filter processing primer target_population location_name depth_category depth fluid_origin AXIAL_YEAR latitude longitude DATE Accession Sample_Name NCBI_Organism_Name NCBI_Tax_ID BioProject dive_ctd site_name collection_method sample_type filter processing primer target_population location_name depth_category depth fluid_origin AXIAL_YEAR latitude longitude DATE Accession Sample_Name NCBI_Organism_Name NCBI_Tax_ID BioProject dive_ctd site_name collection_method sample_type filter processing primer target_population location_name depth_category depth fluid_origin AXIAL_YEAR latitude longitude DATE Accession Sample_Name NCBI_Organism_Name NCBI_Tax_ID BioProject dive_ctd site_name collection_method sample_type filter processing primer target_population location_name depth_category depth fluid_origin AXIAL_YEAR latitude longitude DATE ")

File type: (more information) .asc - View OPeNDAP-style ISO-8859-1 comma-separated text. .csv - Download a ISO-8859-1 comma-separated text table (line 1: names; line 2: units; ISO 8601 times). .csvp - Download a ISO-8859-1 .csv file with line 1: name (units). Times are ISO 8601 strings. .csv0 - Download a ISO-8859-1 .csv file without column names or units. Times are ISO 8601 strings. .dataTable - A JSON file formatted for use with the Google Visualization client library (Google Charts). .das - View the dataset's metadata via an ISO-8859-1 OPeNDAP Dataset Attribute Structure (DAS). .dds - View the dataset's structure via an ISO-8859-1 OPeNDAP Dataset Descriptor Structure (DDS). .dods - OPeNDAP clients use this to download the data in the DODS binary format. .esriCsv - Download a ISO_8859_1 .csv file for ESRI's ArcGIS 9.x and below (separate date and time columns). .fgdc - View the dataset's UTF-8 FGDC .xml metadata. .geoJson - Download longitude,latitude,otherColumns data as a UTF-8 GeoJSON .json file. .graph - View a Make A Graph web page. .help - View a web page with a description of tabledap. .html - View an OPeNDAP-style HTML Data Access Form. .htmlTable - View a UTF-8 .html web page with the data in a table. Times are ISO 8601 strings. .iso19115 - View the dataset's ISO 19115-2/19139 UTF-8 .xml metadata. .itx - Download an ISO-8859-1 Igor Text File. Each response column becomes a wave. .json - View a table-like UTF-8 JSON file (missing value = 'null'; times are ISO 8601 strings). .jsonlCSV1 - View a UTF-8 JSON Lines CSV file with column names on line 1 (mv = 'null'; times are ISO 8601 strings). .jsonlCSV - View a UTF-8 JSON Lines CSV file without column names (mv = 'null'; times are ISO 8601 strings). .jsonlKVP - View a UTF-8 JSON Lines file with Key:Value pairs (missing value = 'null'; times are ISO 8601 strings). .mat - Download a MATLAB binary file. .nc - Download a flat, table-like, NetCDF-3 binary file with COARDS/CF/ACDD metadata. .ncHeader - View the UTF-8 header (the metadata) for the NetCDF-3 .nc file. .ncCF - Download a NetCDF-3 CF Discrete Sampling Geometries file (Contiguous Ragged Array). .ncCFHeader - View the UTF-8 header (the metadata) for the .ncCF file. .ncCFMA - Download a NetCDF-3 CF Discrete Sampling Geometries file (Multidimensional Array). .ncCFMAHeader - View the UTF-8 header (the metadata) for the .ncCFMA file. .nccsv - Download a NetCDF-3-like 7-bit ASCII NCCSV .csv file with COARDS/CF/ACDD metadata. .nccsvMetadata - View the dataset's metadata as the top half of a 7-bit ASCII NCCSV .csv file. .ncoJson - Download a UTF-8 NCO lvl=2 JSON file with COARDS/CF/ACDD metadata. .odvTxt - Download longitude,latitude,time,otherColumns as an ISO-8859-1 ODV Generic Spreadsheet File (.txt). .subset - View an HTML form which uses faceted search to simplify picking subsets of the data. .tsv - Download a ISO-8859-1 tab-separated text table (line 1: names; line 2: units; ISO 8601 times). .tsvp - Download a ISO-8859-1 .tsv file with line 1: name (units). Times are ISO 8601 strings. .tsv0 - Download a ISO-8859-1 .tsv file without column names or units. Times are ISO 8601 strings. .wav - Download a .wav audio file. All columns must be numeric and of the same type. .xhtml - View a UTF-8 XHTML (XML) file with the data in a table. Times are ISO 8601 strings. .kml - View a .kml file, suitable for Google Earth. .smallPdf - View a small .pdf image file with a graph or map. .pdf - View a standard, medium-sized .pdf image file with a graph or map. .largePdf - View a large .pdf image file with a graph or map. .smallPng - View a small .png image file with a graph or map. .png - View a standard, medium-sized .png image file with a graph or map. .largePng - View a large .png image file with a graph or map. .transparentPng - View a .png image file (just the data, without axes, landmask, or legend).

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Accession {
    String long_name "Accession";
    String units "unitless";
  }
  Sample_Name {
    String long_name "Sample_name";
    String units "unitless";
  }
  NCBI_Organism_Name {
    String long_name "Ncbi_organism_name";
    String units "unitless";
  }
  NCBI_Tax_ID {
    String long_name "Ncbi_tax_id";
    String units "unitless";
  }
  BioProject {
    String long_name "Bioproject";
    String units "unitless";
  }
  dive_ctd {
    String long_name "Dive_ctd";
    String units "unitless";
  }
  site_name {
    String long_name "Site_name";
    String units "unitless";
  }
  collection_method {
    String long_name "Collection_method";
    String units "unitless";
  }
  sample_type {
    String long_name "Sample_type";
    String units "unitless";
  }
  filter {
    String long_name "Filter";
    String units "unitless";
  }
  processing {
    String long_name "Processing";
    String units "unitless";
  }
  primer {
    String long_name "Primer";
    String units "unitless";
  }
  target_population {
    String long_name "Target_population";
    String units "unitless";
  }
  location_name {
    String long_name "Location_name";
    String units "unitless";
  }
  depth_category {
    String long_name "Depth_category";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 0, 1540;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  fluid_origin {
    String long_name "Fluid_origin";
    String units "unitless";
  }
  AXIAL_YEAR {
    String long_name "Axial_year";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 45.91623, 45.93359;
    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 -130.0495, -129.9791;
    String axis "X";
    String ioos_category "Location";
    String long_name "Long";
    String standard_name "longitude";
    String units "degrees_east";
  }
  DATE {
    String long_name "Date";
    String units "unitless";
  }
 }
  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.969102.1";
    Float64 Easternmost_Easting -129.9791;
    Float64 geospatial_lat_max 45.93359;
    Float64 geospatial_lat_min 45.91623;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -129.9791;
    Float64 geospatial_lon_min -130.0495;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 1540.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2025-08-14T00:45:13Z (local files)
2025-08-14T00:45:13Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_969102_v1.html";
    String infoUrl "https://osprey.bco-dmo.org/dataset/969102";
    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 45.93359;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 45.91623;
    String summary "Microorganisms are the ancestral forms of life on our planet and have been instrumental in shaping all of Earth?s environments into what they are today. In the ocean, microbial prokaryotes and eukaryotes form the foundation of marine food webs through their activity and interactions. Single-celled microbial eukaryotes (or protists) are some of the most important species on the planet, yet our understanding of how their activities influence and regulate the ocean ecosystem is poorly constrained. At deep-sea hydrothermal vents in particular, our understanding of microbial food web dynamics is incomplete without including the role of microbial eukaryotes. In July 2023, we completed an ROV expedition to Axial Seamount (NE Pacific), where we used ROV Jason to collect low temperature diffuse vent fluid and surrounding plume and background seawater. These samples were filtered in situ or shipboard to collect the microbial communities. Data provided are the product of amplicon tag-sequencing using both 18S rRNA and 16S rRNA gene primers.";
    String title "[Microbial diversity survey Axial Seamount 2023] - Metabarcoding data from microbial diversity survey at Axial Seamount aboard the R/V Thompson cruise TN420 in Jul 2022 and Jul 2023 (Characterizing and quantifying the impact of phagotrophic protists at hot spots of primary production at Axial Seamount)";
    Float64 Westernmost_Easting -130.0495;
  }
}

 

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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 Data Access Protocol (DAP) and its selection constraints.

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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