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Dataset Title:  Surface water total dissolvable lead concentrations near Station ALOHA from
1997 to 2013
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_792783)
Range: longitude = -158.13 to -158.0°E, latitude = 22.47 to 22.77°N, depth = 0.0 to 39.0m
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | 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:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Expedition {
    String bcodmo_name "unknown";
    String description "expedition identifier";
    String long_name "Expedition";
    String units "unitless";
  }
  Deployment {
    String bcodmo_name "deploy";
    String description "deployment identifier";
    String long_name "Deployment";
    String units "unitless";
  }
  Sample_Date {
    String bcodmo_name "date";
    String description "date of sampling events";
    String long_name "Sample Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  ISO_Date {
    String bcodmo_name "date";
    String description "date of sampling events in ISO8601 format";
    String long_name "ISO Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "ISO_Date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 22.47, 22.77;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude of sampling events";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -158.13, -158.0;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude of sampling events";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 39.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth of sampling events";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Pb_TD_CONC {
    Float32 _FillValue NaN;
    Float32 actual_range 24.0, 55.7;
    String bcodmo_name "Pb";
    String description "total dissolvable lead concentration";
    String long_name "Pb TD CONC";
    String units "picomole per kilogram (pmol/kg)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Lead samples from 1997-2013 were collected using the MITESS (Moored In situ
Trace Element Serial Sampler) moored sampler (Bell et al., 2002) (1997-2005)
and ATE shipboard sampling from HOT occupations (1997-2012), the HOE-DYLAN
cruises (2012), and the HOE-PhoR cruises (2013). Samples from 1997-2000 were
analyzed as described by Boyle et al. (2005) and samples after that by the
method described by Lee et al. (2011). The 1997-2013 Pb samples were measured
as tdPb, that is analysis of an acidified unfiltered seawater sample. Since
dissolved Pb (dPb) in pelagic settings is typically >90% of tdPb (Boyle et
al., 2005), the tdPb concentrations from the Station ALOHA time-series are
directly comparable to the 2015 KM1513 dPb data, i.e. filtered at 0.4
\\u03bcm.\\u00a0";
    String awards_0_award_nid "636498";
    String awards_0_award_number "EF-0424599";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0424599";
    String awards_0_funder_name "NSF Emerging Frontiers Division";
    String awards_0_funding_acronym "NSF EF";
    String awards_0_funding_source_nid "392";
    String awards_0_program_manager "Matthew Kane";
    String awards_0_program_manager_nid "535514";
    String cdm_data_type "Other";
    String comment 
"Surface water total dissolvable lead concentrations near Station ALOHA from 1997 to 2013 
  PI: Edward Boyle 
  Version: 2020-02-11";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2020-02-11T16:10:28Z";
    String date_modified "2020-02-28T20:33:37Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.792783.1";
    Float64 Easternmost_Easting -158.0;
    Float64 geospatial_lat_max 22.77;
    Float64 geospatial_lat_min 22.47;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -158.0;
    Float64 geospatial_lon_min -158.13;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 39.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2022-08-08T21:51:38Z (local files)
2022-08-08T21:51:38Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_792783.das";
    String infoUrl "https://www.bco-dmo.org/dataset/792783";
    String institution "BCO-DMO";
    String instruments_0_acronym "Niskin bottle";
    String instruments_0_dataset_instrument_description "Standard Niskin bottle rosettes were used for thorium sampling.";
    String instruments_0_dataset_instrument_nid "792794";
    String instruments_0_description "A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends.  The bottles can be attached individually on a hydrowire or deployed in 12, 24 or 36 bottle Rosette systems mounted on a frame and combined with a CTD.  Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_0_instrument_name "Niskin bottle";
    String instruments_0_instrument_nid "413";
    String instruments_0_supplied_name "Niskin bottle";
    String instruments_1_dataset_instrument_description "The MIT Automated Trace Element (ATE) sampler (Bell et al., 2002) was used for trace metal sampling.";
    String instruments_1_dataset_instrument_nid "792793";
    String instruments_1_description 
"Automated trace element sampler (MITESS or ATE unit).

Bell, J., J. Betts, and E. Boyle (2002) MITESS: A Moored In-situ Trace Element Serial Sampler for Deep-Sea Moorings, Deep-Sea Research I: 49:2103-2118 (pdf)

More description: http://boyle.mit.edu/~ed/MITESS/MITESShomepage.html";
    String instruments_1_instrument_name "Trace element sampler";
    String instruments_1_instrument_nid "639027";
    String instruments_1_supplied_name "MIT Automated Trace Element (ATE) sampler";
    String instruments_2_dataset_instrument_description "Lead samples from 1997-2013 were collected using the MITESS (Moored In situ Trace Element Serial Sampler) moored sampler (Bell et al., 2002) (1997-2005).";
    String instruments_2_dataset_instrument_nid "792803";
    String instruments_2_description 
"Automated trace element sampler (MITESS or ATE unit).

Bell, J., J. Betts, and E. Boyle (2002) MITESS: A Moored In-situ Trace Element Serial Sampler for Deep-Sea Moorings, Deep-Sea Research I: 49:2103-2118 (pdf)

More description: http://boyle.mit.edu/~ed/MITESS/MITESShomepage.html";
    String instruments_2_instrument_name "Trace element sampler";
    String instruments_2_instrument_nid "639027";
    String instruments_2_supplied_name "MITESS";
    String keywords "bco, bco-dmo, biological, chemical, conc, data, dataset, date, deployment, depth, dmo, erddap, expedition, iso, latitude, longitude, management, oceanography, office, Pb_TD_CONC, preliminary, sample, Sample_Date, time";
    String license "https://www.bco-dmo.org/dataset/792783/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/792783";
    Float64 Northernmost_Northing 22.77;
    String param_mapping "{'792783': {'Lat': 'flag - latitude', 'Depth': 'flag - depth', 'Lon': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/792783/parameters";
    String people_0_affiliation "Massachusetts Institute of Technology";
    String people_0_affiliation_acronym "MIT";
    String people_0_person_name "Edward A. Boyle";
    String people_0_person_nid "50984";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Mathew Biddle";
    String people_1_person_nid "708682";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "C-MORE";
    String projects_0_acronym "C-MORE";
    String projects_0_description 
"Project summary
The Center for Microbial Oceanography: Research and Education (C-MORE) is a recently established (August 2006; NSF award: EF-0424599) NSF-sponsored Science and Technology Center designed to facilitate a more comprehensive understanding of the diverse assemblages of microorganisms in the sea, ranging from the genetic basis of marine microbial biogeochemistry including the metabolic regulation and environmental controls of gene expression, to the processes that underpin the fluxes of carbon, related bioelements and energy in the marine environment. Stated holistically, C-MORE's primary mission is: Linking Genomes to Biomes.
We believe that the time is right to address several major, long-standing questions in microbial oceanography. Recent advances in the application of molecular techniques have provided an unprecedented view of the structure, diversity and possible function of sea microbes. By combining these and other novel approaches with more well-established techniques in microbiology, oceanography and ecology, it may be possible to develop a meaningful predictive understanding of the ocean with respect to energy transduction, carbon sequestration, bioelement cycling and the probable response of marine ecosystems to global environmental variability and climate change. The strength of C-MORE resides in the synergy created by bringing together experts who traditionally have not worked together and this, in turn, will facilitate the creation and dissemination of new knowledge on the role of marine microbes in global habitability.
The new Center will design and conduct novel research, broker partnerships, increase diversity of human resources, implement education and outreach programs, and utilize comprehensive information about microbial life in the sea. The Center will bring together teams of scientists, educators and community members who otherwise do not have an opportunity to communicate, collaborate or design creative solutions to long-term ecosystem scale problems. The Center's research will be organized around four interconnected themes:
(Theme I) microbial biodiversity,
(Theme II) metabolism and C-N-P-energy flow,
(Theme III) remote and continuous sensing and links to climate variability, and
(Theme IV) ecosystem modeling, simulation and prediction.
  Each theme will have a leader to help coordinate the research programs and to facilitate interactions among the other related themes. The education programs will focus on pre-college curriculum enhancements, in service teacher training and formal undergraduate/graduate and post-doctoral programs to prepare the next generation of microbial oceanographers. The Center will establish and maintain creative outreach programs to help diffuse the new knowledge gained into society at large including policymakers. The Center's activities will be dispersed among five partner institutions:
Massachusetts Institute of Technology,
Woods Hole Oceanographic Institution,
Monterey Bay Aquarium Research Institute,
University of California at Santa Cruz and
Oregon State University
and will be coordinated at the University of Hawaii at Manoa.
Related Files:
Strategic plan (PDF file)";
    String projects_0_end_date "2017-07";
    String projects_0_geolocation "North Pacific Subtropical Gyre (large region around 22 45 N, 158 W)";
    String projects_0_name "Center for Microbial Oceanography: Research and Education";
    String projects_0_project_nid "2093";
    String projects_0_project_website "http://cmore.soest.hawaii.edu/";
    String projects_0_start_date "2006-08";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 22.47;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Lead samples from 1997-2013 were collected using the MITESS (Moored In situ Trace Element Serial Sampler) moored sampler (Bell et al., 2002) (1997-2005) and ATE shipboard sampling from HOT occupations (1997-2012), the HOE-DYLAN cruises (2012), and the HOE-PhoR cruises (2013).";
    String title "Surface water total dissolvable lead concentrations near Station ALOHA from 1997 to 2013";
    String version "1";
    Float64 Westernmost_Easting -158.13;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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