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Dataset Title:  Deployment history of sensors recording dissolved oxygen from Massachusetts
from 2012.
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_669673)
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 {
  pond {
    Byte _FillValue 127;
    Byte actual_range 1, 3;
    String description "Pond ID number";
    String ioos_category "Unknown";
    String long_name "Pond";
    String units "unitless";
  }
  date_start {
    String description "Sampling start date; mm/dd/yyyy";
    String ioos_category "Time";
    String long_name "Date Start";
    String source_name "date_start";
    String units "unitless";
  }
  date_end {
    String description "Sampling end date; mm/dd/yyyy";
    String ioos_category "Time";
    String long_name "Date End";
    String units "unitless";
  }
  deployment {
    Byte _FillValue 127;
    Byte actual_range 1, 13;
    String description "Deployment ID number";
    String ioos_category "Unknown";
    String long_name "Deployment";
    String units "unitless";
  }
  instrument1 {
    String description "Instrument used";
    String ioos_category "Unknown";
    String long_name "Instrument1";
    String units "unitless";
  }
  instrument2 {
    String description "Instrument used";
    String ioos_category "Unknown";
    String long_name "Instrument2";
    String units "unitless";
  }
  instrument3 {
    String description "Instrument used";
    String ioos_category "Unknown";
    String long_name "Instrument3";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"EXO2, YSI TIDE1, YSI PIE1, YSI PIE2, HOBODO1, and HOBODO2 recorded dissolved
oxygen concentrations and temperature.
 
EXO2, YSI TIDE1, YSI PIE1, YSI PIE2, HOBO Cond848 and HOBO Cond2 recorded
conductivity
 
HOBOpendant loggers recorded light (lumens) and temperature.\\u00a0
 
All instruments recorded data in 15 min intervals.\\u00a0";
    String awards_0_award_nid "529582";
    String awards_0_award_number "OCE-1233678";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1233678";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "Dr David  L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Deployment Information 
  Amanda Spivak, PI 
  Version 8 December 2016";
    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 2.2d  13 Jun 2019";
    String date_created "2016-12-10T00:46:45Z";
    String date_modified "2019-04-05T17:18:44Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.669673.1";
    String history 
"2019-08-24T16:00:10Z (local files)
2019-08-24T16:00:10Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_669673.das";
    String infoUrl "https://www.bco-dmo.org/dataset/669673";
    String institution "BCO-DMO";
    String instruments_0_acronym "Water Temp Sensor";
    String instruments_0_dataset_instrument_description "Recorded dissolved oxygen concentrations and temperature.";
    String instruments_0_dataset_instrument_nid "669690";
    String instruments_0_description "General term for an instrument that measures the temperature of the water with which it is in contact (thermometer).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/134/";
    String instruments_0_instrument_name "Water Temperature Sensor";
    String instruments_0_instrument_nid "647";
    String instruments_0_supplied_name "EXO2, YSI TIDE1, YSI PIE1, YSI PIE2, HOBODO1, and HOBODO2";
    String instruments_1_acronym "Light Meter";
    String instruments_1_dataset_instrument_description "Recorded light (lumens) and temperature.";
    String instruments_1_dataset_instrument_nid "669692";
    String instruments_1_description "Light meters are instruments that measure light intensity. Common units of measure for light intensity are umol/m2/s or uE/m2/s (micromoles per meter squared per second or microEinsteins per meter squared per second). (example: LI-COR 250A)";
    String instruments_1_instrument_name "Light Meter";
    String instruments_1_instrument_nid "703";
    String instruments_1_supplied_name "HOBOpendant loggers";
    String instruments_2_acronym "Dissolved Oxygen Sensor";
    String instruments_2_dataset_instrument_description "Recorded dissolved oxygen concentrations and temperature.";
    String instruments_2_dataset_instrument_nid "669689";
    String instruments_2_description "An electronic device that measures the proportion of oxygen (O2) in the gas or liquid being analyzed";
    String instruments_2_instrument_name "Dissolved Oxygen Sensor";
    String instruments_2_instrument_nid "705";
    String instruments_2_supplied_name "EXO2, YSI TIDE1, YSI PIE1, YSI PIE2, HOBODO1, and HOBODO2";
    String instruments_3_acronym "Conductivity Meter";
    String instruments_3_dataset_instrument_description "Recorded conductivity";
    String instruments_3_dataset_instrument_nid "669691";
    String instruments_3_description "Conductivity Meter - An electrical conductivity meter (EC meter) measures the electrical conductivity in a solution. Commonly used in hydroponics, aquaculture and freshwater systems to monitor the amount of nutrients, salts or impurities in the water.";
    String instruments_3_instrument_name "Conductivity Meter";
    String instruments_3_instrument_nid "719";
    String instruments_3_supplied_name "EXO2, YSI TIDE1, YSI PIE1, YSI PIE2, HOBO Cond848 and HOBO Cond2";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, date, date_end, deployment, dmo, end, erddap, instrument1, instrument2, instrument3, management, oceanography, office, pond, preliminary, start, time";
    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 metadata_source "https://www.bco-dmo.org/api/dataset/669673";
    String param_mapping "{'669673': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/669673/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Amanda Spivak";
    String people_0_person_nid "529580";
    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 project "Eutrophication Effects on Sediment Metabolism and Benthic Algal-bacterial Coupling: An Application of Novel Techniques in a LTER Estuary";
    String projects_0_acronym "benthic_PP_at_TIDE";
    String projects_0_description 
"Extracted from the NSF award abstract:
This project will address how rates of benthic microalgal production respond to eutrophication and geomorphological changes in human-impacted tidal creeks. Excess nutrient loading increases benthic algal biomass and likely stimulates production rates but the magnitude of nutrient and geomorphological effects on rates of production is unknown. Will changes in benthic algal productivity affect algal-bacterial coupling? Furthermore, how is algal-bacterial coupling affected by geomorphological changes, which may be exacerbated by excess nutrient loading but can also occur in pristine marshes?
This project will take advantage of the infrastructure of the TIDE project, a long-term saltmarsh eutrophication experiment at the Plum Island Ecosystem - Long Term Ecological Research site in Northeastern Massachusetts. Specifically, the PIs will measure benthic metabolism and examine algal- bacterial coupling in fertilized and ambient nutrient tidal creeks in the first field season. The following field season, they will compare sediment metabolism and carbon dynamics on slumped tidal creek walls (i.e. areas where low marsh has collapsed into the tidal creek) to that on the bottom of tidal creeks. In both years, gross and net production will be determined using an innovative triple oxygen isotope technique and traditional dissolved oxygen and inorganic carbon flux measurements. Comparisons between these methods will be useful in informing studies of sediment metabolism. Lipid biomarkers will be used to characterize the sources of organic matter to creek sediments, and stable isotope analysis of bacterial specific biomarkers to identify the sources of organic carbon utilized by sediment bacteria. The biomarkers will reveal whether sediment bacteria use organic matter substrates, such as benthic microalgal carbon, selectively or in proportion to availability. Overall, results from the proposed study will provide important information about how sediment carbon dynamics in shallow tidal creeks respond to long term eutrophication. Furthermore, findings will enhance understanding of the role of tidal creeks in coastal biogeochemistry.";
    String projects_0_end_date "2015-08";
    String projects_0_geolocation "Plum Island Estuary, Rowley Massachusetts";
    String projects_0_name "Eutrophication Effects on Sediment Metabolism and Benthic Algal-bacterial Coupling: An Application of Novel Techniques in a LTER Estuary";
    String projects_0_project_nid "529583";
    String projects_0_start_date "2012-09";
    String publisher_name "Hannah Ake";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Deployment history of sensors recording dissolved oxygen from Massachusetts from 2012.";
    String title "Deployment history of sensors recording dissolved oxygen from Massachusetts from 2012.";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5-beta";
  }
}

 

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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