ERDDAP > tabledap > Data Access Form

Dataset Title:	[Acropora cervicornis white band exposure experiment survival outcomes] - Acropora cervicornis genomic/trancriptomic sequence accessions with associated data on tank exposure to white band disease and survival outcomes with corals collected from Florida, USA and Bocas del Toro, Panama in 2021 (Multi-omic bases of coral disease resistance)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_922006_v1)
Information:	Summary | License | Metadata | Background | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
Tank (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"D1"	"H5"
Treatment (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"D"	"H"
Location (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Florida"	"Panama"
Genotype (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"B10"	"U98"
Day_1_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_1_PM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_2_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_2_PM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_3_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_3_PM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_4_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_4_PM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_5_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_5_PM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_6_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_6_PM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1
Day_7_AM (untiless)	!= =~ <= >= = < >		!= =~ <= >= = < >		0	1

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" Tank Treatment Location Genotype Day_1_AM Day_1_PM Day_2_AM Day_2_PM Day_3_AM Day_3_PM Day_4_AM Day_4_PM Day_5_AM Day_5_PM Day_6_AM Day_6_PM Day_7_AM Tank Treatment Location Genotype Day_1_AM Day_1_PM Day_2_AM Day_2_PM Day_3_AM Day_3_PM Day_4_AM Day_4_PM Day_5_AM Day_5_PM Day_6_AM Day_6_PM Day_7_AM Tank Treatment Location Genotype Day_1_AM Day_1_PM Day_2_AM Day_2_PM Day_3_AM Day_3_PM Day_4_AM Day_4_PM Day_5_AM Day_5_PM Day_6_AM Day_6_PM Day_7_AM Tank Treatment Location Genotype Day_1_AM Day_1_PM Day_2_AM Day_2_PM Day_3_AM Day_3_PM Day_4_AM Day_4_PM Day_5_AM Day_5_PM Day_6_AM Day_6_PM Day_7_AM Tank Treatment Location Genotype Day_1_AM Day_1_PM Day_2_AM Day_2_PM Day_3_AM Day_3_PM Day_4_AM Day_4_PM Day_5_AM Day_5_PM Day_6_AM Day_6_PM Day_7_AM ")

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 {
  Tank {
    String long_name "Tank";
    String units "untiless";
  }
  Treatment {
    String long_name "Treatment";
    String units "untiless";
  }
  Location {
    String long_name "Location";
    String units "untiless";
  }
  Genotype {
    String long_name "Genotype";
    String units "untiless";
  }
  Day_1_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_1_am";
    String units "untiless";
  }
  Day_1_PM {
    Int32 actual_range 0, 1;
    String long_name "Day_1_pm";
    String units "untiless";
  }
  Day_2_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_2_am";
    String units "untiless";
  }
  Day_2_PM {
    Int32 actual_range 0, 1;
    String long_name "Day_2_pm";
    String units "untiless";
  }
  Day_3_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_3_am";
    String units "untiless";
  }
  Day_3_PM {
    Int32 actual_range 0, 1;
    String long_name "Day_3_pm";
    String units "untiless";
  }
  Day_4_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_4_am";
    String units "untiless";
  }
  Day_4_PM {
    Int32 actual_range 0, 1;
    String long_name "Day_4_pm";
    String units "untiless";
  }
  Day_5_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_5_am";
    String units "untiless";
  }
  Day_5_PM {
    Int32 actual_range 0, 1;
    String long_name "Day_5_pm";
    String units "untiless";
  }
  Day_6_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_6_am";
    String units "untiless";
  }
  Day_6_PM {
    Int32 actual_range 0, 1;
    String long_name "Day_6_pm";
    String units "untiless";
  }
  Day_7_AM {
    Int32 actual_range 0, 1;
    String long_name "Day_7_am";
    String units "untiless";
  }
 }
  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.922006.1";
    String history 
"2024-11-21T08:40:14Z (local files)
2024-11-21T08:40:14Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_922006_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/922006";
    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 
"Genomic data was collected from 96 Acropora cervicornis samples, 48 of which were collected from the Coral restoration foundation nursery in Florida in June 2021 and the other 48 were collected from Bocas del Toro Panama in November 2021. All samples were sequenced using illumina short read sequencing to create whole genome sequencing profiles of the DNA with one of the Florida samples, the K2 genotype, being sequenced using additional Nanopore long reads to assemble and annotate an A. cervicornis genome. All genotypes were used in a disease exposure assay to assess individual genotype disease resistance with a further, 16 colonies from Florida being sequenced at two timepoints across disease exposed and healthy colonies (total 48 sequences) using RNAseq to identify patterns in differential gene expression based on disease resistance.

This dataset includes sample metadata, treatment information, and disease state for corals in the exposure experiment. Sample metadata and accession identifiers for sequences at The National Center for Biotechnology Information (NCBI) are included as a supplemental file.";
    String title "[Acropora cervicornis white band exposure experiment survival outcomes] - Acropora cervicornis genomic/trancriptomic sequence accessions with associated data on tank exposure to white band disease and survival outcomes with corals collected from Florida, USA and Bocas del Toro, Panama in 2021 (Multi-omic bases of coral disease resistance)";
  }
}

 

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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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