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Dataset Title:	[AE1913 Protein Spectral Counts] - Scaffold-derived metaproteomic exclusive and total spectral counts associated with proteins from samples taken during R/ V Atlantic Explorer cruise AE1913 from the Sargasso Sea to Northeast US shelf waters in June of 2019 (Collaborative Research: Direct Characterization of Adaptive Nutrient Stress Responses in the Sargasso Sea using Protein Biomarkers and a Biogeochemical AUV)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_934706_v1)
Range:	longitude = -70.84278 to -64.16629°E, latitude = 31.66689 to 38.52837°N, depth = 10.0 to 4100.0m
Information:	Summary | License | FGDC | ISO 19115 | Metadata | Background | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks vectors X Axis:  spectral_count station_id depth minimum_filter_size_microns maximum_filter_size_microns latitude longitude Y Axis:  spectral_count station_id depth minimum_filter_size_microns maximum_filter_size_microns latitude longitude Color:  spectral_count station_id depth minimum_filter_size_microns maximum_filter_size_microns latitude longitude   Constraints Optional Constraint #1 Optional Constraint #2 row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude     != =~ <= >= = < >     != =~ <= >= = < > row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude     != =~ <= >= = < >     != =~ <= >= = < > row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude     != =~ <= >= = < >     != =~ <= >= = < > row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude     != =~ <= >= = < >     != =~ <= >= = < > row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude     != =~ <= >= = < >     != =~ <= >= = < >   Server-side Functions  distinct() orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude row_id protein_id kegg_id enzyme_comm_id protein_name pfams_id supergroup classification sample_id spectral_count cruise_id station_id depth minimum_filter_size_microns maximum_filter_size_microns date_y_m_d latitude longitude ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle Borderless Filled Square Borderless Filled Circle Borderless Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Draw land mask:  under over outline off Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

Click on the map to specify a new center point. Zoom:

 

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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.
   

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  row_id {
    String long_name "Row_id";
    String units "unitless";
  }
  protein_id {
    String long_name "Protein_id";
    String units "unitless";
  }
  kegg_id {
    String long_name "Kegg_id";
    String units "unitless";
  }
  enzyme_comm_id {
    String long_name "Enzyme_comm_id";
    String units "unitless";
  }
  protein_name {
    String long_name "Protein_name";
    String units "unitless";
  }
  pfams_id {
    String long_name "Pfams_id";
    String units "unitless";
  }
  supergroup {
    String long_name "Supergroup";
    String units "unitless";
  }
  classification {
    String long_name "Classification";
    String units "unitless";
  }
  sample_id {
    String long_name "Sample_id";
    String units "unitless";
  }
  spectral_count {
    Int32 actual_range 0, 2009;
    String long_name "Spectral_count";
    String units "unitless";
  }
  cruise_id {
    String long_name "Cruise_id";
    String units "unitless";
  }
  station_id {
    Int32 actual_range 1, 8;
    String long_name "Station_id";
    String units "unitless";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Int32 actual_range 10, 4100;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Depth_m";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  minimum_filter_size_microns {
    Float32 actual_range 0.2, 0.2;
    String long_name "Minimum_filter_size_microns";
    String units "microns (um)";
  }
  maximum_filter_size_microns {
    Float32 actual_range 51.0, 51.0;
    String long_name "Maximum_filter_size_microns";
    String units "microns (um)";
  }
  date_y_m_d {
    String long_name "Date_y_m_d";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 31.66689, 38.52837;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude_dd";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -70.84278, -64.16629;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude_dd";
    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.934706.1";
    Float64 Easternmost_Easting -64.16629;
    Float64 geospatial_lat_max 38.52837;
    Float64 geospatial_lat_min 31.66689;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -64.16629;
    Float64 geospatial_lon_min -70.84278;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 4100.0;
    Float64 geospatial_vertical_min 10.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-08T06:10:34Z (local files)
2024-11-08T06:10:34Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_934706_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/934706";
    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 38.52837;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 31.66689;
    String summary "These are the Scaffold-derived metaproteomic exclusive and total spectral counts associated with proteins.  Samples were taken during R/V Atlantic Explorer cruise AE1913 in Subtropical North Atlantic, beginning at the Bermuda Atlantic Time-series Station (BATS) of the Sargasso Sea  and ending in coastal Northeast US shelf waters in June of 2019.";
    String title "[AE1913 Protein Spectral Counts] - Scaffold-derived metaproteomic exclusive and total spectral counts associated with proteins from samples taken during R/V Atlantic Explorer cruise AE1913 from the Sargasso Sea to Northeast US shelf waters in June of 2019 (Collaborative Research: Direct Characterization of Adaptive Nutrient Stress Responses in the Sargasso Sea using Protein Biomarkers and a Biogeochemical AUV)";
    Float64 Westernmost_Easting -70.84278;
  }
}

 

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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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