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Dataset Title:  CTD summary data from phytoplankton monitoring sites in Juneau, AK sampled
from 2015-2016 (SEAK-AHAB project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_660308)
Range: longitude = -134.7903 to -134.6499°E, latitude = 58.3819 to 58.4916°N, depth = 1.1 to 38.93m, time = 2015-03-10T12:45:00Z to 2016-12-15T12:00:00Z
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | 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 {
  year {
    Int16 _FillValue 32767;
    Int16 actual_range 2015, 2016;
    String bcodmo_name "year";
    String description "Four digit year sample was taken; YYYY";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  investigator {
    String bcodmo_name "investigator";
    String description "Investigator responsible for collecting sample";
    String long_name "Investigator";
    String units "unitless";
  instrument {
    String bcodmo_name "instrument";
    String description "Instrument used to collect sample";
    String long_name "Instrument";
    String units "unitless";
  station {
    String bcodmo_name "station";
    String description "Station where sample was taken";
    String long_name "Station";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 58.3819, 58.4916;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    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 -134.7903, -134.6499;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    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";
  sampling_event {
    String bcodmo_name "event";
    String description "Sampling event ID";
    String long_name "Sampling Event";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/EVTAGFL/";
    String units "unitless";
  date {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20150310, 20161215;
    String bcodmo_name "date";
    String description "Date sample was taken; YYYYmmdd";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  time_zone {
    String bcodmo_name "timezone";
    String description "Time zone where sample was taken";
    String long_name "Time Zone";
    String units "unitless";
  time_local {
    String bcodmo_name "time_local";
    String description "Local time when sampling occurred; HH:MM";
    String long_name "Time Local";
    String units "unitless";
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 1.1, 38.93;
    String axis "Z";
    String bcodmo_name "depth_cast";
    String description "Bottom depth of cast";
    String ioos_category "Location";
    String long_name "Cast Depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  surface_temp {
    Float32 _FillValue NaN;
    Float32 actual_range -2.21, 16.1;
    String bcodmo_name "temp_ss";
    String description "Sea surface temperature";
    String long_name "Surface Temp";
    String units "celsius";
  s_salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 13.11, 31.13;
    String bcodmo_name "sal_ss";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "Surface salinity";
    String long_name "Sea Water Practical Salinity";
    String units "practical salinity units (PSU)";
  b_salinity {
    Float32 _FillValue NaN;
    Float32 actual_range 16.0, 31.53;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "Bottom salinity";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "practical salinity units (PSU)";
  s_density {
    Float32 _FillValue NaN;
    Float32 actual_range 1009.56, 1024.44;
    String bcodmo_name "density";
    String description "Surface density";
    String long_name "s density";
    String units "kilogram per meter cubed (kg/m3)";
  b_density {
    Float32 _FillValue NaN;
    Float32 actual_range 1011.65, 1024.9;
    String bcodmo_name "density";
    String description "Botton density";
    String long_name "B Density";
    String units "kilogram per meter cubed (kg/m3)";
  max_fluor {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 28.04;
    String bcodmo_name "fluorescence";
    String description "Maximum fluorescence";
    String long_name "Max Fluor";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLPM01/";
    String units "milligram per meter cubed (mg/m3)";
  data_quality {
    String bcodmo_name "comment";
    String description "Codes providing information about missing or flagged data";
    String long_name "Data Quality";
    String units "unitless";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.4259915e+9, 1.4818032e+9;
    String axis "T";
    String bcodmo_name "ISO_DateTime_Local";
    String description "DateTime local; YYYY-mm-dd HH:MM";
    String ioos_category "Time";
    String long_name "ISO Date Time Local";
    String source_name "ISO_DateTime_Local";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01T00:00:00Z";
    String units "seconds since 1970-01-01T00:00:00Z";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Dock-based CTD casts were completed at approximately weekly intervals at two
phytoplankton sampling stations, Auke Bay and Amalga Harbor, in Juneau, AK
using a SBE-25 Sealogger CTD equipped with a SBE-3 temperature sensor, SBE-4C
conductivity sensor, SBE-29 external pressure sensor, and a WETLabs
Fluorometer. The CTD was deployed down to ~1 meter above the seafloor. Local
date and time were recorded at the start of each sampling event.\\u00a0
The CTD instrument package was last serviced and calibrated by Sea-Bird
Electronics, Inc. in June 2015.";
    String awards_0_award_nid "565808";
    String awards_0_award_number "ICER-1415195";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1415195";
    String awards_0_funder_name "NSF Divsion of Integrative and Collaborative Education and Research";
    String awards_0_funding_acronym "NSF ICER";
    String awards_0_funding_source_nid "565809";
    String awards_0_program_manager "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"CTD summary data 
  E. Tobin, PI 
  Version History: 
  25 July 2017 - Update data for 2016 
  30 September 2016 - Data for 2015";
    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 "2016-09-30T18:31:41Z";
    String date_modified "2019-06-11T16:31:39Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.660308.1";
    Float64 Easternmost_Easting -134.6499;
    Float64 geospatial_lat_max 58.4916;
    Float64 geospatial_lat_min 58.3819;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -134.6499;
    Float64 geospatial_lon_min -134.7903;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 38.93;
    Float64 geospatial_vertical_min 1.1;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2021-10-21T10:32:24Z (local files)
2021-10-21T10:32:24Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_660308.das";
    String infoUrl "https://www.bco-dmo.org/dataset/660308";
    String institution "BCO-DMO";
    String instruments_0_acronym "CTD";
    String instruments_0_dataset_instrument_description "Dock based CTD casts were used in this survey";
    String instruments_0_dataset_instrument_nid "660325";
    String instruments_0_description "The Conductivity, Temperature, Depth (CTD) unit is an integrated instrument package designed to measure the conductivity, temperature, and pressure (depth) of the water column.  The instrument is lowered via cable through the water column and permits scientists observe the physical properties in real time via a conducting cable connecting the CTD to a deck unit and computer on the ship. The CTD is often configured with additional optional sensors including fluorometers, transmissometers and/or  radiometers.  It is often combined with a Rosette of water sampling bottles (e.g. Niskin, GO-FLO) for collecting discrete water samples during the cast.  This instrument designation is used when specific make and model are not known.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/130/";
    String instruments_0_instrument_name "CTD profiler";
    String instruments_0_instrument_nid "417";
    String instruments_0_supplied_name "SBE-25 Sealogger CTD";
    String instruments_1_acronym "SBE-4 Conductivity";
    String instruments_1_dataset_instrument_description "Equipped on CTD";
    String instruments_1_dataset_instrument_nid "660338";
    String instruments_1_description "The Sea-Bird SBE-4 conductivity sensor is a modular, self-contained instrument that measures conductivity from 0 to 7 Siemens/meter.  The sensors (Version 2; S/N 2000 and higher) have electrically isolated power circuits and optically coupled outputs to eliminate any possibility of noise and corrosion caused by ground loops. The sensing element is a cylindrical, flow-through, borosilicate glass cell with three internal platinum electrodes. Because the outer electrodes are connected together, electric fields are confined inside the cell, making the measured resistance (and instrument calibration) independent of calibration bath size or proximity to protective cages or other objects.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0417/";
    String instruments_1_instrument_name "Sea-Bird SBE-4 Conductivity Sensor";
    String instruments_1_instrument_nid "474";
    String instruments_1_supplied_name "SBE-4C conductivity sensor";
    String instruments_2_acronym "Pressure Sensor";
    String instruments_2_dataset_instrument_description "Equipped on CTD";
    String instruments_2_dataset_instrument_nid "660339";
    String instruments_2_description "A pressure sensor is a device used to measure absolute, differential, or gauge pressures.  It is used only when detailed instrument documentation is not available.";
    String instruments_2_instrument_name "Pressure Sensor";
    String instruments_2_instrument_nid "567";
    String instruments_2_supplied_name "SBE-29 external pressure sensor";
    String instruments_3_acronym "CTD-fluorometer";
    String instruments_3_dataset_instrument_description "Equipped on CTD";
    String instruments_3_dataset_instrument_nid "660340";
    String instruments_3_description "A CTD-fluorometer is an instrument package designed to measure hydrographic information (pressure, temperature and conductivity) and chlorophyll fluorescence.";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/113/";
    String instruments_3_instrument_name "CTD-fluorometer";
    String instruments_3_instrument_nid "580";
    String instruments_3_supplied_name "WETLabs fluorometer";
    String instruments_4_acronym "Water Temp Sensor";
    String instruments_4_dataset_instrument_description "Equipped on CTD";
    String instruments_4_dataset_instrument_nid "660337";
    String instruments_4_description "General term for an instrument that measures the temperature of the water with which it is in contact (thermometer).";
    String instruments_4_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/134/";
    String instruments_4_instrument_name "Water Temperature Sensor";
    String instruments_4_instrument_nid "647";
    String instruments_4_supplied_name "SBE-3 temperature sensor";
    String keywords "b_density, b_salinity, bco, bco-dmo, biological, cast, cast_depth, chemical, data, data_quality, dataset, date, density, depth, dmo, earth, Earth Science > Oceans > Salinity/Density > Salinity, erddap, event, fluor, instrument, investigator, iso, latitude, local, longitude, management, max, max_fluor, ocean, oceanography, oceans, office, practical, preliminary, quality, s_density, s_salinity, salinity, sampling, sampling_event, science, sea, sea_water_practical_salinity, seawater, station, surface, surface_temp, temperature, time, time_local, time_zone, water, year, zone";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/660308/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/660308";
    Float64 Northernmost_Northing 58.4916;
    String param_mapping "{'660308': {'lat': 'flag - latitude', 'lon': 'flag - longitude', 'cast_depth': 'flag - depth', 'ISO_DateTime_Local': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/660308/parameters";
    String people_0_affiliation "University of Alaska Fairbanks";
    String people_0_affiliation_acronym "UAF-Juneau";
    String people_0_person_name "Dr Elizabeth D. Tobin";
    String people_0_person_nid "565811";
    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 "Hannah Ake";
    String people_1_person_nid "650173";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Mathew Biddle";
    String people_2_person_nid "708682";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "SEAK-AHAB";
    String projects_0_acronym "SEAK-AHAB";
    String projects_0_description 
"Description from NSF award abstract:
The project is supported under the NSF Science, Engineering and Education for Sustainability Fellows (SEES Fellows) program, with the goal of helping to enable discoveries needed to inform actions that lead to environmental, energy and societal sustainability while creating the necessary workforce to address these challenges.
This project focuses on the sustainability of shelfish harvesting in Alaska. In Alaska, paralytic shellfish poisoning caused by the marine alga Alexandrium is a severe and persistent problem that significantly impacts human health and the availability of shellfish resources. This project aims to enhance sustainability of commercial, recreational and subsistence shellfish harvest in Southeast Alaska by addressing the ecology of Alexandrium harmful algal blooms and their sociocultural impacts. Despite the recognized impacts of paralytic shellfish poisoning, little research has been done on the causative organism, Alexandrium, and the sociocultural impacts of toxic Alexandrium blooms in the Southeast Alaska region. This study is a three-pronged effort. First, the project bolsters understanding of the ecological mechanisms that promote Alexandrium blooms by mapping cyst seedbeds (i.e., bloom initiation sites), monitoring cyst emergence, and identifying environmental conditions under which blooms form. This information adds to the body of scientific knowledge about Alexandrium bloom dynamics in coastal, fjord systems, provide early-warning information about toxic bloom development and help focus future paralytic shellfish poisoning testing and harmful algal bloom monitoring efforts in Southeast Alaska. Second, the application of novel in situ sensors will overcome previous benthic emergence monitoring challenges and has the potential to improve harmful algal bloom forecasting capabilities. Third, human dimensions research will generate critical information about how social systems can reduce vulnerability to harmful algal blooms and how local/traditional knowledge can support scientific efforts by establishing strong community partnerships.
The SEES Fellow, Dr. Elizabeth Tobin, works with host mentor Dr. Ginny Eckert at the University of Alaska Fairbanks, and with partner mentor Dr. Thomas Leschine at the University of Washington.";
    String projects_0_end_date "2017-08";
    String projects_0_geolocation "Southeast Alaska; 58 N, 134 W";
    String projects_0_name "Enhancing Sustainability of Shellfish Harvest in Alaska: Addressing the Ecology of Alexandrium Blooms and their Sociocultural Impacts";
    String projects_0_project_nid "565810";
    String projects_0_start_date "2014-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 58.3819;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "investigator,instrument,time_zone";
    String summary "CTD summary data from phytoplankton monitoring sites in Juneau, AK sampled from 2015-2016 (SEAK-AHAB project)";
    String time_coverage_end "2016-12-15T12:00:00Z";
    String time_coverage_start "2015-03-10T12:45:00Z";
    String title "CTD summary data from phytoplankton monitoring sites in Juneau, AK sampled from 2015-2016 (SEAK-AHAB project)";
    String version "1";
    Float64 Westernmost_Easting -134.7903;
    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
For example,
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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