Datasets

This page contains information about the Datasets data source in the Dimensions BigQuery project.

See also

Dimensions DSL API Documentation for this type is also available from here.

Datasets Schema

Field

Type

Description

Example

associated_grant_ids

Array of < Literal: String >

Dimensions IDs of the grants linked to the publication the dataset is associated with.

 
      ["grant.7874194", "grant.7874966"]

associated_publication_arxiv_id

Literal: String

The arXiv id of the associated publication.

 
      "arXiv:2008.09840"

associated_publication_doi

Literal: String

The DOI of the publication linked to the dataset (single value).

 
      "10.3389/fmars.2019.00580"

associated_publication_id

Literal: String

The Dimensions ID of the publication linked to the dataset (single value).

 
      "pub.1121114008"

associated_publication_pmid

Literal: String

The PubMed id of the associated publication.

 
      "27212461"

authors

Array of < Entity: Author >

Ordered list of the dataset authors. ORCIDs are included if available.

 
      [{"name": "Sarah Foster", "orcid": "0000-0003-1325-8708"}, {"name": "Robinson W. Fulweiler", "orcid": "0000-0003-0871-4246"}]

categories

Entity: VersionedCategories

Versioned categorisations.

 
      {"bra_v1": {"values": ["Public Health"], "full": [{"id": "4003", "value": "Public Health"}]}, "for_v1": {"first_level": {"codes": ["11", "16"], "full": [{"id": "2211", "code": "11", "name": "Medical and Health Sciences"}, {"id": "2216", "code": "16", "name": "Studies in Human Society"}]}, "second_level": {"codes": ["1117", "1608"], "full": [{"id": "3177", "code": "1117", "name": "Public Health and Health Services"}, {"id": "3448", "code": "1608", "name": "Sociology"}]}}, "hra_v1": {"values": ["Population & Society"], "full": [{"id": "3903", "value": "Population & Society"}]}, "hrcs_hc_v1": {"values": ["Generic health relevance"], "full": [{"id": "890", "value": "Generic health relevance"}]}, "hrcs_rac_v1": {"codes": ["6.1"], "full": [{"id": "10601", "code": "6.1", "name": "Pharmaceuticals"}]}, "icrp_cso_v1": {"codes": ["6.2"], "full": [{"id": "3773", "code": "6.2", "name": "Surveillance"}]}, "icrp_ct_v1": {"values": ["Not Site-Specific Cancer"], "full": [{"id": "3816", "value": "Not Site-Specific Cancer"}]}, "rcdc_v1": {"values": ["Biotechnology", "Genetics"], "full": [{"id": "338", "value": "Biotechnology"}, {"id": "526", "value": "Genetics"}]}, "sdg_v1": {"codes": ["3"], "full": [{"id": "40003", "code": "3", "name": "Good Health and Well Being"}]}, "uoa_v1": {"codes": ["C23"], "full": [{"id": "30023", "code": "C23", "name": "Education"}]}}

category_bra

Entity: SimpleCategorization

Broad Research Areas

 
      {"values": ["Public Health"], "full": [{"id": "4003", "value": "Public Health"}]}

category_for

Entity: ComplexSystematicCategorization

ANZSRC Fields of Research classification

 
      {"first_level": {"codes": ["09", "06", "04", "03"], "full": [{"id": "2209", "code": "09", "name": "Engineering"}, {"id": "2206", "code": "06", "name": "Biological Sciences"}, {"id": "2204", "code": "04", "name": "Earth Sciences"}, {"id": "2203", "code": "03", "name": "Chemical Sciences"}]}, "second_level": {"codes": ["0402", "0602", "0907", "0399"], "full": [{"id": "2503", "code": "0402", "name": "Geochemistry"}, {"id": "2597", "code": "0602", "name": "Ecology"}, {"id": "2878", "code": "0907", "name": "Environmental Engineering"}, {"id": "2486", "code": "0399", "name": "Other Chemical Sciences"}]}}

category_hra

Entity: SimpleCategorization

Health Research Areas

 
      {"values": ["Population & Society"], "full": [{"id": "3903", "value": "Population & Society"}]}

category_hrcs_hc

Entity: SimpleCategorization

HRCS - Health Categories

 
      {"values": ["Generic health relevance"], "full": [{"id": "890", "value": "Generic health relevance"}]}

category_hrcs_rac

Entity: SystematicCategorization

HRCS – Research Activity Codes

 
      {"codes": ["6.1"], "full": [{"id": "10601", "code": "6.1", "name": "Pharmaceuticals"}]}

category_icrp_cso

Entity: SystematicCategorization

ICRP Common Scientific Outline

 
      {"codes": ["6.2"], "full": [{"id": "3773", "code": "6.2", "name": "Surveillance"}]}

category_icrp_ct

Entity: SimpleCategorization

ICRP Cancer Types

 
      {"values": ["Not Site-Specific Cancer"], "full": [{"id": "3816", "value": "Not Site-Specific Cancer"}]}

category_rcdc

Entity: SimpleCategorization

Research, Condition, and Disease Categorization

 
      {"values": ["Biotechnology", "Genetics"], "full": [{"id": "338", "value": "Biotechnology"}, {"id": "526", "value": "Genetics"}]}

category_sdg

Entity: SystematicCategorization

SDG - Sustainable Development Goals

 
      {"codes": ["3"], "full": [{"id": "40003", "code": "3", "name": "Good Health and Well Being"}]}

concepts

Array of < Entity: Concept >

Concepts describing the main topics of a data set (note: automatically derived from the dataset text using machine learning).

 
      [{"concept": "DNA sequences", "relevance": "0.10298167853055835"}, {"concept": "sequence", "relevance": "0.08457519859328573"}, {"concept": "FASTA files", "relevance": "0.09875481205292"}, {"concept": "files", "relevance": "0.023955839650273369"}, {"concept": "OTU sequences", "relevance": "0.10561150286661591"}, {"concept": "dietary wheat", "relevance": "0.063607839460135179"}, {"concept": "wheat", "relevance": "0.0761585837729135"}, {"concept": "methane yield", "relevance": "0.068767580994771219"}, {"concept": "yield", "relevance": "0.057067732157359365"}, {"concept": "microbiome changes", "relevance": "0.087884496982233828"}, {"concept": "changes", "relevance": "0.052670022933715421"}, {"concept": "dairy cows", "relevance": "0.05511030251178467"}, {"concept": "cows", "relevance": "0.051129654968860037"}, {"concept": "et al", "relevance": "0.039058701954300119"}, {"concept": "al", "relevance": "0.027543928035514365"}]

created_date

Literal: Timestamp

The creation date of the dataset.

 
      "2020-03-10"

date

Literal: Timestamp

The publication date of the dataset.

 
      "2019-01-07 00:00:00 UTC"

date_imported_gbq

Literal: Timestamp

Timestamp when the dataset was last imported into BigQuery. Incremental changes can be determined using this field. Note, however at certain times all records may be reimported.

 
      "2020-08-04 02:00:34 UTC"

date_modified

Literal: Timestamp

The last modification date of the dataset.

 
      "2019-01-07 00:00:00 UTC"

description

Literal: String

Description of the dataset.

 
      "On 7 occasions over the course of 3 years (2011-2013) we conducted hypoxic static core incubations on sediments and water collected in Waquoit Bay Massachusetts (USA) from four stations:  Childs River Estuary, Metoxit Point, South Basin, & Sage Lot Pond.  The goal of this study was quantify sediment metabolism under water column hypoxia in a shallow, temperate estuarine system.  Here we provide a comprehensive dataset of dissolved nutrient (i.e., inorganic nitrogen, phosphorus, and silica) and gas (i.e., di-nitrogen, nitrous oxide, and methane) fluxes across the sediment-water interface measured from static core incubations under hypoxic conditions (defined as oxygen concentrations \u226494 \u03bcM, 3 mg/L). Note that these fluxes are published (Foster & Fulweiler 2019).We collected triplicate or quadruplicate sediment cores in PVC tubes (10 cm inner diameter, 30 cm height) from the side of a boat using a pole corer equipped with a one-way valve (Fulweiler et al. 2010; Foster & Fulweiler 2014).  We also collected in situ bottom water from each site and filtered onboard (nominally to 0.2\u03bcm).  We then transported cores and water back to our Boston University laboratory and placed them in a water-bath inside an environmental chamber set to ambient bottom water temperatures.  We conducted static core incubations in the dark to determine fluxes across the sediment-water interface (e.g., Banta et al. 1995; Giblin et al. 1997; Fields et al. 2014).  Core lids were equipped with magnetic stir bars (Dornblaser et al. 1989) which provided gentle (45 rpm) mixing of the overlying water with minimal suspension of sediments (Hopkinson et al. 2001; Renaud et al. 2008; Heiss et al. 2012). In order to simulate hypoxic conditions we used the natural aerobic respiration of the sediments to consume dissolved oxygen and bring each core to hypoxia.  The duration of hypoxic incubations were typically around 1 day (median 22 h, range 7.2-36 h).  The median final oxygen concentrations measured in the cores at the end of the hypoxic incubation was 0.85 mg/L.Dissolved inorganic nutrient concentrations were determined with high-resolution digital colorimetry on a SEAL Auto Analyzer 3 with segmented flow injection using standard techniques and chemical analyses (Solorzano 1969; Johnson & Petty 1983; Grasshoff et al. 1999).  We directly measured N2 on a quadrupole membrane inlet mass spectrometer (MIMS) using the N2/Ar technique developed by Kana et al. (1994).  On four occasions we also collected additional duplicate water samples for the analysis of dissolved greenhouse gases, N2O and CH4. We directly measured dissolved N2O and CH4 using a headspace equilibration technique (Kling et al. 1991; Foster & Fulweiler 2016).  We analyzed the vial headspace (after water sample \u2013 headspace equilibration) using a gas chromatograph (Shimadzu GC-2014) equipped with a flame ionization detector (FID, for CH4) and an electron capture detector (ECD, for N2O).  We measured oxygen concentrations using an optical Luminescent Dissolved Oxygen sensor (Hach LDO 101).  Note that on one occasion (6 Aug 2012), absolute N2O flux rates were 1-3 orders of magnitude greater than on the other dates and were significant outliers in the dataset (Foster & Fulweiler 2016). These data are designated with a star (*). In addition, on 2 dates in 2012 there was an issue with the instrument analysis of N2, therefore they are designated as having a measurement issue (m.i.) and were not able to be used in our analyses.  Nutrient and greenhouse gas parameters were not measured (n.m.) prior to 2012.  In a few instances flux rates we could not determine (c.n.d.) flux rates because there was not a predictable linear relationship between concentration change and time.Please email with questions:  sqfoster@bu.eduSampling StationsCRE = Childs River Estuary (41\u00b0 34.805\u2019 N 70\u00b031.826\u2019 W, 1.2 m deep, bottom water salinity 27.3-29.7 psu) MP =  Metoxit Point (41\u00b0 34.134\u2019 N 70\u00b0 31.272\u2019 W, 2.2 m deep, bottom water salinity 29.6-31.3 psu) SB = South Basin (41\u00b0 33.404\u2019 N 70\u00b0 31.442\u2019 W, 1.8 m deep, bottom water salinity 30.6-31.3 psu)SLP = Sage Lot Pond (41\u00b0 33.270\u2019 N 70\u00b0 30.584\u2019 W, 1.2 m deep, bottom water salinity 28.9-30.4 psu)Units Incubation Temperature = degrees CelsiusO2 uptake = di-oxygen per mole O2 (micromoles per meter squared per hour)NH4+ Flux = ammonium (micromoles per meter squared per hour)DSi Flux = dissolved silica  (micromoles per meter squared per hour)PO43- Flux = phosphate  (micromoles per meter squared per hour)N2-N Flux = di-nitrogen gas per mol N  (micromoles per meter squared per hour)N2O Flux = nitrous oxide  (nanomoles per meter squared per hour)CH4 Flux = methane (nanomoles per meter squared per hour)Abbreviations & SymbolsDate = dd (day)- month - yy (year)* = outlier value m.i. = measurement issuen.m. = not measuredc.n.d. = could not determineAcknowledgmentsThere are numerous people who contributed to this project.  We would like to thank the Waquoit Bay National Estuarine Research Reserve (WBNERR) for their continued multi-year support of our research.  All water and sediment samples for this study were collected using WBNERR boats.  We are particularly grateful to the following WBNERR employees who assisted with the fieldwork:  M.K. Fox, A. Lescher, J. Mora, C. Weidman.  We would also like to thank several Fulweiler Lab members and Boston University Marine Program (BUMP) students for their assistance with fieldwork and the laboratory-based core incubation experiments:  S. Andrews, A. Banks, S. Buckley, K. Czapla, S. Donovan, D. Forest, E. Heiss, J. Luthringer, M. McCarthy, S. Newell, M.K. Rogener, R. Schweiker, K. Yoshimura.  M.K. Rogener and E. Heiss also helped analyze samples for N2/Ar concentrations on the Membrane Inlet Mass Spectrometer (MIMS).  K. Czapla and A. Al-Haj conducted analyses for nutrient concentrations using a SEAL auto-analyzer. We also thank Boston University Earth and Environment Department for use of their facilities and their general academic and logistical research support.Text CitationsBanta GT, AE Giblin, JE Hobbie, and J Tucker. 1995. Benthic respiration and nitrogen release in Buzzards Bay, Massachusetts. Journal of Marine Research 53: 107\u2013135.Dornblaser MM, J Tucker, GT Banta, KH Foreman, MC O'Brien, and AE Giblin. 1989. Obtaining undisturbed sediment cores for biogeochemical process studies using SCUBA. In, eds. M A Lang and W C Jaap, 97\u2013104. Costa Mesa, CA, USA.Fields L, SW Nixon, C Oviatt, and RW Fulweiler. 2014. Benthic metabolism and nutrient regeneration in hydrographically different regions on the inner continental shelf of Southern New England. Estuarine, Coastal and Shelf Science 148. Academic Press: 14\u201326.Foster SQ, and RW Fulweiler. 2019. Estuarine sediments exhibit dynamic and variable biogeochemical responses to hypoxia. Journal of Geophysical Research: Biogeosciences, 124. https://doi.org/10.1029/2018JG004663Foster SQ, and RW Fulweiler. 2016. Sediment nitrous oxide fluxes are dominated by uptake in a temperate estuary. Frontiers in Marine Science 3: Article 40. https://doi.org/10.3389/fmars.2016.00040Foster SQ, and RW Fulweiler. 2014. Spatial and historic variability of benthic nitrogen cycling in an anthropogenically impacted estuary. Frontiers in Marine Science 1: Article 56. https://doi.org/10.3389/fmars.2014.00056.Fulweiler RW, SW Nixon, and BA Buckley. 2010. Spatial and temporal variability of benthic oxygen demand and nutrient regeneration in an anthropogenically impacted New England estuary. Estuaries and Coasts 33: 1377\u20131390. https://doi.org/10.1007/s12237-009-9260-y.Giblin AE, CS Hopkinson, and J Tucker. 1997. Benthic metabolism and nutrient cycling in Boston Harbor, Massachusetts. Estuaries 20: 346\u2013364.Grasshoff K, K Kremling, and M Ehrhardt. 1999. Determination of Nutrients. In Methods of Seawater Analysis, eds. K Grasshoff, K Kremling, and M Ehrhardt, 3rd ed., 159\u2013226. Weinheim, Germany: Wiley-VCH, Verlag GmbH, D-69469.Heiss EM, L Fields, and RW Fulweiler. 2012. Directly measured net denitrification rates in offshore New England sediments. Continental Shelf Research 45: 78\u201386.Hopkinson CS, AE Giblin, and J Tucker. 2001. Benthic metabolism and nutrient regeneration on the continental shelf of Eastern Massachusetts, USA. Marine Ecology Progress Series 224: 1\u201319.Johnson KS, and RL Petty. 1983. Determination of nitrate and nitrite in seawater by flow injection analysis. Limnology and Oceanography 28: 1260\u20131266.Kling GW, GW Kipphut, and MC Miller. 1991. Arctic lakes and streams as gas conduits to the atmosphere: Implications for tundra carbon budgets. Science 251: 298-301.Renaud PE, N Morata, ML Carroll, SG Denisenko, and M Reigstad. 2008. Pelagic\u2013benthic coupling in the western Barents Sea: processes and time scales. Deep-Sea Research Part II 55: 2372\u20132380.Solorzano L. 1969. Determination of ammonia in natural waters by the phenolypochlorite method. Limnology and Oceanography 14: 799\u2013801."

doi

Literal: String

Dataset DOI.

 
      "10.6084/m9.figshare.7371110.v1"

embargo_date

Literal: Timestamp

The embargo date of the dataset.

 
      "2021-06-30"

id

Literal: String

Clustering field

Dimensions Dataset ID.

 
      "7371110"

license

Entity: License

The dataset license details, including the name and corresponding URL of the license if available (eg. ‘CC BY 4.0’ and ‘https://creativecommons.org/licenses/by/4.0/’).

 
      {"name": "CC BY-NC 4.0", "url": "https://creativecommons.org/licenses/by-nc/4.0/"}

repository_id

Literal: String

The ID of the repository of the dataset.

 
      "portal_415"

repository_name

Literal: String

The name of the repository of the dataset.

 
      "Federation University Australia"

repository_url

Literal: String

Repository item URL for the dataset.

 
      "https://federation.figshare.com/articles/dataset/Challenges_for_ECRs_in_STEMM_-_data_supporting_eLife_manuscript_A_survey_of_early-career_researchers_in_Australia_/13151147"

research_org_cities

Array of < Literal: Integer >

City of the organisations the associated publication authors are affiliated to, expressed as GeoNames ID.

 
      [6943568, 2174003, 2177091, 4348599]

research_org_countries

Array of < Literal: String >

Country of the organisations the associated publication authors are affiliated to, identified using GeoNames codes.

 
      ["US", "AU"]

research_org_state_codes

Array of < Literal: String >

State of the organisations the associated publication authors are affiliated to, expressed as GeoNames codes (ISO-3166-2).

 
      ["AU-VIC", "AU-QLD", "US-MD"]

research_orgs

Array of < Literal: String >

GRID organisations linked to the publication associated to the dataset.

 
      ["grid.466960.b", "grid.410445.0", "grid.170693.a", "grid.452188.2"]

researcher_ids

Array of < Literal: String >

Dimensions researchers IDs associated to the dataset’s associated publication.

 
      ["ur.01051011505.94", "ur.014730567367.46"]

title

Literal: String

Title of the dataset.

 
      "Nutrient and dissolved gas fluxes across the sediment-water interface under hypoxic conditions in Waquoit Bay, Massachusetts (USA)"

year

Literal: Integer

Partitioning field

Year of publication of the dataset.

 
      2019

Auxiliary Entities

Author

Field

Type

Description

name

Literal: String

Name of a dataset author (if present)

orcid

Literal: String

ORCID Identifier for a dataset author (if present)

role

Literal: String

Role for a dataset author (if present)

ComplexSystematicCategorization

Field

Type

Description

first_level

Entity: SystematicCategoryLevel

second_level

Entity: SystematicCategoryLevel

Concept

Field

Type

Description

concept

Literal: String

relevance

Literal: Float

License

Field

Type

Description

name

Literal: String

The dataset licence name, e.g. ‘CC BY 4.0’.

url

Literal: String

The dataset licence URL, e.g. ‘https://creativecommons.org/licenses/by/4.0/’.

SimpleCategorization

Field

Type

Description

full

Array of < Entity: SimpleCategory >

values

Array of < Literal: String >

SimpleCategory

Field

Type

Description

id

Literal: String

value

Literal: String

SystematicCategorization

Field

Type

Description

codes

Array of < Literal: String >

full

Array of < Entity: SystematicCategory >

SystematicCategory

Field

Type

Description

code

Literal: String

id

Literal: String

name

Literal: String

SystematicCategoryLevel

Field

Type

Description

codes

Array of < Literal: String >

full

Array of < Entity: SystematicCategory >

VersionedCategories

Field

Type

Description

bra_v2020

Entity: SimpleCategorization

for_2020_v2022

Entity: ComplexSystematicCategorization

hra_v1

Entity: SimpleCategorization

hrcs_hc_v2020

Entity: SimpleCategorization

hrcs_rac_v2020

Entity: SystematicCategorization

icrp_cso_v2020

Entity: SystematicCategorization

icrp_ct_v2020

Entity: SimpleCategorization

rcdc_v2023

Entity: SimpleCategorization

sdg_v2021

Entity: SystematicCategorization

deprecated bra_v1

Entity: SimpleCategorization

Deprecated in favor of: bra_v2020

deprecated for_v1

Entity: ComplexSystematicCategorization

Deprecated in favor of: for_2020_v2022

deprecated for_v2020

Entity: ComplexSystematicCategorization

Deprecated in favor of: for_2020_v2022

deprecated hrcs_hc_v1

Entity: SimpleCategorization

Deprecated in favor of: hrcs_hc_v2020

deprecated hrcs_rac_v1

Entity: SystematicCategorization

Deprecated in favor of: hrcs_rac_v2020

deprecated icrp_cso_v1

Entity: SystematicCategorization

Deprecated in favor of: icrp_cso_v2020

deprecated icrp_ct_v1

Entity: SimpleCategorization

Deprecated in favor of: icrp_ct_v2020

deprecated rcdc_v1

Entity: SimpleCategorization

Deprecated in favor of: category_rcdc

deprecated sdg_v1

Entity: SystematicCategorization

Deprecated in favor of: sdg_v2021

deprecated uoa_v1

Entity: SystematicCategorization

Deprecated with no recommended replacement.

Datasets Deprecations

This section lists fields that have been deprecated and should no longer be used within queries. In time, deprecated fields will be removed from the data source’s corresponding schema in BigQuery.

Deprecated Fields

Field

Type

Description

category_uoa

Entity: SystematicCategorization

Deprecated with no recommended replacement.