cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2hfshm
title: Occurrence Download

description: A dataset containing 168415 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Observation.org, Nature data from around the World",
 "Country is Sweden"
 ]
}

 The dataset includes 168415 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012601-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.2909/ec45177f-56a7-41a2-bb22-ef6fe8b83ab8
title: Water Layer 2021 (raster 100 m), Europe, 3-yearly

description: This is the metadata covering the Water Layer (WL) product. The WL is one of the products of the pan-European High-Resolution Water Snow & Ice portfolio (HR-WSI), which are provided at high spatial resolution from the Sentinel-2 and Sentinel-1 constellations data from September 1, 2016 onwards..
The WL is generated for the 2021 reference year. It is a a multi-annual product based on the information covering the period 2016-2021. In the context of the HR-WSI, the water and dry frequency masks are derived from intermediate outputs of the WCD workflow, the monthly surface water masks in combination with the WIC S2 NRT product. It provides detailed information about the presence and condition of water surfaces across Europe.
It is also generated in different spatial resolutions (10m and 100m) and projections (LAEA & WGS84/UTM).
The High Resolution Water Layer portfolio consists of the WL, the Water Presence Index (WPI), the Water confidence layer (WCL) and the Rolling archive (WLRA).

There are 5 major classes like:
- Dry (always or mostly dry with minor instances of wet)
- permanent water (always contains water)
- temporary water ( temporary water surfaces, aliteration of dry and water)
- sea water (oceans and sea)
- clouds
DOI: 10.5281/zenodo.7889165
title: AusEFlux: Empirical upscaling of OzFlux eddy covariance flux tower data over Australia

description: Important Note: In this version of the dataset (v1.0) there was a mistake discovered in the modelling of Ecosystem Respiration. Please instead use version 2.0:  doi.org/10.5281/zenodo.14942139

AusEFlux (Australian Empirical Fluxes) is a high resolution (500 metre) gridded estimate of Gross Primary Productivity (GPP), Ecosystem Respiration (ER), Net Ecosystem Exchange (NEE), and Evapotranspiration over the Australian continent for the period January 2003 to Present.  These datasets provide a benchmark for assessment against Land Surface Model simulations, and a means for monitoring of Australia’s terrestrial carbon cycle at an unprecedented high-resolution.

Version 2.0 of AusEFlux has just been released (as of March 2025) and was created to operationalise the research datasets published in this EGU Biogeosciences publication. In order to operationalise these datasets, changes to the input datasets were required to align the data sources with datasets that are regularly and reliably updated, along with general improvements. The datasets provided on Zenodo have been reprojected to 5 km resolution to facilitate easier uploading and sharing, but full resolution datasets (both v1.1 and v2.0) can be accessed freely through NCI's THREDDS portal.

Two Jupyter Notebooks have been created (one for GPP and one for NEE) that demonstrate the differences between the research datasets (v1.1) and the operational datasets (v2.0), including showing the differences in specifications and inputs.  You can view/download these notebooks using the links below:

GPP comparison between versions

NEE comparisons between versions

Each dataset contains three variables:



"<flux>_median": represents the 'best-estimate' of a given flux, the units are gC/m2/mon-1

"<flux>_25th_percentile": represents the lower uncertainty bound, the units are gC/m2/mon-1

"<flux>_75th_percentile": represents the upper uncertainty bound, the units are gC/m2/mon-1


Version Guide:

v1.0: DO NOT USE THIS VERSION. There was a mistake in the modelling of ecosystem respiration, so this version of the dataset should not be used.  As of version 1.1, the error has been rectified.

v1.1: This version of the datasets are those used to inform the EGU Publication linked above. Its time range is 2003-July 2022, and its spatial resolution is 5 km on Zenodo, but the 1 km resolution datasets can be accessed through NCI's THREDDS portal.

V2.0 This is the operational version of the dataset, its includes several improvements over version 1.1. Its time-range is 2003-2024 (and will be updated annually), and its spatial resolution is 500m.  A 5 km reprojected version of the dataset is included here on Zenodo, but the 500 metre datasets can be accessed through NCI's THREDDS portal.
DOI: 10.5281/zenodo.7947265
title: AusEFlux: Empirical upscaling of OzFlux eddy covariance flux tower data over Australia

description: AusEFlux (Australian Empirical Fluxes) is a high resolution (500 metre) gridded estimate of Gross Primary Productivity (GPP), Ecosystem Respiration (ER), Net Ecosystem Exchange (NEE), and Evapotranspiration over the Australian continent for the period January 2003 to Present.  These datasets provide a benchmark for assessment against Land Surface Model simulations, and a means for monitoring of Australia’s terrestrial carbon cycle at an unprecedented high-resolution.

Version 2.0 of AusEFlux has just been released (as of March 2025) and was created to operationalise the research datasets published in this EGU Biogeosciences publication. In order to operationalise these datasets, changes to the input datasets were required to align the data sources with datasets that are regularly and reliably updated, along with general improvements. The datasets provided on Zenodo have been reprojected to 5 km resolution to facilitate easier uploading and sharing, but full resolution datasets (both v1.1 and v2.0) can be accessed freely through NCI's THREDDS portal.

Two Jupyter Notebooks have been created (one for GPP and one for NEE) that demonstrate the differences between the research datasets (v1.1) and the operational datasets (v2.0), including showing the differences in specifications and inputs.  You can view/download these notebooks using the links below:

GPP comparison between versions

NEE comparisons between versions

Each dataset contains three variables:



"<flux>_median": represents the 'best-estimate' of a given flux, the units are gC/m2/mon-1

"<flux>_25th_percentile": represents the lower uncertainty bound, the units are gC/m2/mon-1

"<flux>_75th_percentile": represents the upper uncertainty bound, the units are gC/m2/mon-1


Version Guide:

v1.0: DO NOT USE THIS VERSION. There was a mistake in the modelling of ecosystem respiration, so this version of the dataset should not be used.  As of version 1.1, the error has been rectified.

v1.1: This version of the datasets are those used to inform the EGU Publication linked above. Its time range is 2003-July 2022, and its spatial resolution is 5 km on Zenodo, but the 1 km resolution datasets can be accessed through NCI's THREDDS portal.

V2.0 This is the operational version of the dataset, its includes several improvements over version 1.1. Its time-range is 2003-2024 (and will be updated annually), and its spatial resolution is 500m.  A 5 km reprojected version of the dataset is included here on Zenodo, but the 500 metre datasets can be accessed through NCI's THREDDS portal.
DOI: 10.15468/dl.auq9tz
title: Occurrence Download

description: A dataset containing 1539 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Uroteuthis"
 ]
}

 The dataset includes 1539 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048788-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4cafhe
title: Occurrence Download

description: A dataset containing 145 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.28_1",
 "TaxonKey is Phragmites australis"
 ]
}

 The dataset includes 145 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048791-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5683/sp3/lgoh6d
title: Vocal performance increases rapidly during the dawn chorus in Adelaide’s warbler

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p&gt;&lt;span lang="EN-US"&gt;Many songbirds sing intensely during the early morning, resulting in a phenomenon known as the dawn chorus. We tested the hypothesis that male Adelaide’s warblers (&lt;em&gt;Setophaga&lt;/em&gt; &lt;em&gt;adelaidae&lt;/em&gt;) warm up their voices during the dawn chorus. If warming up the voice is one of the functions of the dawn chorus, we predicted that vocal performance would increase more rapidly during the dawn chorus compared to the rest of the morning and that high song rates during the dawn chorus period contribute to the increase in vocal performance. The performance metrics &lt;em&gt;recovery time, voiced frequency modulation&lt;/em&gt;, and &lt;em&gt;unvoiced&lt;/em&gt; &lt;em&gt;frequency&lt;/em&gt; &lt;em&gt;modulation&lt;/em&gt; were low when birds first began singing, increased rapidly during the dawn chorus, and then leveled off or gradually diminished after dawn. These changes are attributable to increasing performance within song types. Reduction in the duration of the silent gap between notes is the primary driver of improved performance during the dawn chorus. Simulations indicated that singing at a high rate during the dawn chorus period increases performance in two of the three performance measures (&lt;em&gt;recovery&lt;/em&gt; &lt;em&gt;time&lt;/em&gt; and &lt;em&gt;unvoiced&lt;/em&gt; &lt;em&gt;frequency&lt;/em&gt; &lt;em&gt;modulation&lt;/em&gt;) relative to singing at a low rate during this period. These findings are consistent with the hypothesis that vocal warm-up is one benefit of participation in the dawn chorus. &lt;/span&gt;&lt;/p&gt;
description: <b>Dryad version number:</b> 4
<b>Version status:</b> submitted
<b>Dryad curation status:</b> Published
<b>Sharing link:</b> http://datadryad.org/stash/dataset/doi:10.5061/dryad.5x69p8d7z
<b>Storage size:</b> 27243395
<b>Visibility:</b> public
DOI: 10.5683/sp3/bz38qc
title: Watershed DOC uptake occurs mostly in lakes in the summer and in rivers in the winter: The CUPS-OF-DOC model

description: &lt;b&gt;Abstract&lt;/b&gt;&lt;br/&gt;&lt;p&gt;River networks transport dissolved organic carbon (DOC) from terrestrial uplands to the coastal ocean. The extent to which a reach or lake within a river network uptakes DOC depends on the stream order, the seasonal conditions, and the flow. At the watershed scale, it remains unclear whether DOC uptake is dominated by biological processes such as respiration, or abiotic processes like photomineralization. The partitioning of DOC uptake in lakes versus rivers is also unclear. In this study, we present a new model that unifies year-round controls on DOC cycling for an entire river network, including river-lake connectivity, to elucidate the importance of biotic vs. abiotic controls on DOC uptake. We present the &lt;strong&gt;C&lt;/strong&gt;atchment &lt;strong&gt;Up&lt;/strong&gt;take and &lt;strong&gt;S&lt;/strong&gt;inks by &lt;strong&gt;S&lt;/strong&gt;eason, &lt;strong&gt;O&lt;/strong&gt;rder, and &lt;strong&gt;F&lt;/strong&gt;low for &lt;strong&gt;DOC&lt;/strong&gt; (CUPS-OF-DOC) model, which quantifies terrestrial DOC loading, gross primary productivity (GPP), and uptake via microbes and photomineralization. The model is applied to the Connecticut River Watershed and accounts for cascading reach- and lake-scale DOC cycling across ninety-eight scenarios spanning combinations of flows, seasons, and stream orders. We show that riverine DOC uptake is nearly constant with stream order, but the proportion of DOC uptake from photomineralization varies. Photomineralization dominates in rivers in most flow conditions and stream orders, especially in winter, accounting for at least half of whole-watershed DOC uptake in February across all flows. Whole-watershed summer DOC uptake occurs mostly via biomineralization in lakes, accounting for 80% of DOC uptake during the growing season, despite accounting for less than 6% of watershed open water surface area.&lt;/p&gt;
description: &lt;b&gt;Methods&lt;/b&gt;&lt;br /&gt;&lt;p&gt;This data contains code and output from the CUPS-OF-DOC model. Please refer to the 2023 publication by the same name in Limnology &amp; Oceanography for complete methods, doi: 10.1002/lno.12306.&lt;/p&gt;
description: &lt;b&gt;Usage notes&lt;/b&gt;&lt;br /&gt;&lt;p&gt;Please see the READ_ME file for instructions on how to run this code.&lt;/p&gt;
description: <b>Dryad version number:</b> 8
<b>Version status:</b> submitted
<b>Dryad curation status:</b> Published
<b>Sharing link:</b> http://datadryad.org/stash/dataset/doi:10.5061/dryad.tb2rbp02h
<b>Storage size:</b> 174753964
<b>Visibility:</b> public
DOI: 10.5683/sp3/zcurad
title: IEA Renewables Information Statistics. OECD - Renewables balance, 1990-2022

description: This dataset focuses on the renewables market while providing full balance data such as primary energy supply, transformation sector and final consumption based in kilotonne and terajoule of renewables equivalent for OECD countries and OECD country aggregate. [Dataset editions 2015-2023].
description: IEA Renewables Information Statistics
DOI: 10.21410/7e4/annpob/ywthzd
title: China Internet Regulations 1988-2022 déposé.xls

description: :unav
DOI: 10.5683/sp3/wyoagv
title: IEA Renewables Information Statistics. OECD - Renewables supply and consumption, 1990-2022

description: This comparative tables presents figures on the renewable energy supply and consumption market amongst OECD member countries by analyzing renewable products in terms of production, import and exports. [Dataset editions 2015-2023].
description: IEA Renewables Information Statistics
DOI: 10.21410/7e4/annpob
title: Chinese Internet Regulations 1988-2022

description: Ce jeu de données contient toutes les lois, régulations, lignes directrices et décisions proclamées par les régulateurs chinois au niveau national entre 1988 et 2022.
DOI: 10.5683/sp3/l0nsto
title: IEA Renewables Information Statistics. World - Renewable and Waste Energy Statistics, 1990-2022

description: This dataset comprises statistics regarding various renewable and waste energy while presenting trade statistics of various renewable energy products as well as figures for those products in terms of electricity output (GWh) and heat output(TJ). [Dataset editions 2015-2023].
description: IEA Renewables Information Statistics
DOI: 10.5683/sp3/gcykip
title: IEA Renewables Information Statistics. World - Renewable and Waste Energy Supply (Ktoe), 1990-2022

description: This dataset figures representing various renewable and waste energy supply statistics while showcasing the renewable energy market’s products as well as figures for those products in terms of electricity output (GWh, heat output(TJ), domestic supply and stock changes. [Dataset editions 2015-2023].
description: IEA Renewables Information Statistics
DOI: 10.5683/sp3/4t16vr
title: IEA World Energy Statistics and Balances. Conversions Factors for Energy Statistics, 1960-2017

description: This dataset provides conversion factors in terms of trade, production and consumption of energy within various industries. [Dataset editions 2015-2017, 2019].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/3ai95p
title: Medline search hedge for "qualitative research"

description: &lt;h1&gt;Medline (Ovid)&lt;/h1&gt;
 &lt;p&gt;&lt;code&gt;CONCEPT 1: Terms relating to qualitative research&lt;/code&gt;&lt;/p&gt;
 &lt;OL&gt;
 &lt;LI&gt;exp Qualitative Research/&lt;/LI&gt;
 &lt;LI&gt;(qualitative adj (research or stud$3)).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;(mixed adj (method* or studies)).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;"Surveys and Questionnaires"/&lt;/LI&gt;
 &lt;LI&gt;exp Interviews as Topic/&lt;/LI&gt;
 &lt;LI&gt;interview*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;focus groups/&lt;/LI&gt;
 &lt;LI&gt;focus group*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;self report/&lt;/LI&gt;
 &lt;LI&gt;((action or participatory) and research).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;exp Community-Based Participatory Research/&lt;/LI&gt;
 &lt;LI&gt;grounded theory/&lt;/LI&gt;
 &lt;LI&gt;grounded theory.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;phenomenolog*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;exp Narration/&lt;/LI&gt;
 &lt;LI&gt;narrat*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;conversation*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;discourse*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;(ethnograph* or ethnomethodolog* or ethno methodolog* or autoethnograph*).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;hermeneutic*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;constructivis*.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;((case or field) adj (study or studies)).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;((participant* or field) adj observ*).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;((purpos* or theoretical or judg?ment or "maximum variation" or convenience or "critical case" or "deviant case" or "key informant" or snowball or cluster) adj sampl*).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;(experience* or perspective* or perception* or meaning* or view? or viewpoint*).ti.&lt;/LI&gt;
 &lt;LI&gt;((lived or life or personal* or patient? or survivor*) adj3 (experience* or perspective* or perception* or meaning* or view? or viewpoint*)).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;((thematic or content) adj analys*).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;"group discussion*".ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;(cope or copes or coping or thrive or thrives or thriving).ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;finding?.ti,ab,kf.&lt;/LI&gt;
 &lt;LI&gt;or/1-30&lt;/LI&gt;
 &lt;/OL&gt;
description: This is a search hedge written for Medline (Ovid) designed to isolate qualitative research from a broader set of articles. It has not been formally validated but has been used in published articles.

Original date of development: early 2016
DOI: 10.5683/sp3/x62lyx
title: IEA World Energy Statistics and Balances. Extended world energy balances, 1960-2022

description: This table contains an extended set of data on the energy supply, trade and consumption of coal, oil, energy output, gas, electricity, heat, combustible renewables and waste, expressed in thousand tonnes of oil equivalent (ktoe). [Dataset editions 2015-2023].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/wbsztl
title: IEA World Energy Statistics and Balances. Oil demand by product for non-OECD countries, 1971-2021

description: This dataset contains data on oil demand and consumption by product such as aviation fuels, motor gasoline, diesel oil, kerosene, naphtha, petroleum and refinery fuel for non-OECD countries. [Dataset editions 2015-2023].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/mbftoy
title: IEA World Energy Statistics and Balances. World conversion factors, 1960-2022

description: This dataset provides conversion factors in terms of trade, production and consumption of energy within various industries. [Dataset editions 2015-2021, 2023].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/d7ovun
title: IEA World Energy Statistics and Balances. World energy balances, 1960-2022

description: This table contains data on the energy trade, supply and consumption of coal, oil, gas, electricity, heat, combustible renewables and waste, expressed in thousand tonnes of oil equivalent (ktoe). [Dataset editions 2015-2021, 2023].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/8vfxpx
title: IEA World Energy Statistics and Balances. World energy statistics, 1960-2022

description: This table contains data on energy supply, trade and consumption in original units (1000 metric tonnes, terajoules and gigawatt hours) for coal, oil, gas, electricity, heat, combustible renewables, biogasoline, energy, refinery gas, charcoal, waste. [Dataset editions 2015-2023].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/f2lx4n
title: IEA World Energy Statistics and Balances. World Indicators, 1960-2022

description: This dataset provides data on energy world indicators in terms of world supply, consumption and trade. [Dataset editions 2015-2023].
description: IEA World Energy Statistics and Balances
DOI: 10.5683/sp3/9c5tu0
title: Place Types in Canada based on Aggregate Dissemination Areas

description: In a research note published in CJPS, we propose a new typology of geographic places for use in advancing Canadian politics research on the political effects of place. We use hierarchical cluster analysis to inductively derive place types from Aggregate Dissemination Areas (ADAs), a fine-grained unit of geography covering all of Canada, newly available from Statistics Canada. Using this approach, we uncover seven distinct place types, adding nuance to earlier more aggregated approaches focused on urban-rural (or urban-suburban-rural) distinctions. Here, we make these data available for other researchers
DOI: 10.5683/sp3/aproek
title: Archive de réplication de l'étude : Réforme de l'imposition du gain en capital de 2024 : Qui sont les contribuables touchant des gains de 250 000 $ ou plus?

description: Codes utilisés pour produire les tableaux de l'étude et résultats bruts extraits du centre d'accès aux données de recherche.
DOI: 10.5683/sp3/ii56am
title: SEM_data

description: Simulated SEM results (`SEM_data`).
DOI: 10.5683/sp3/emood4
title: The COVID-19 Pandemic Among Sexual and Gender Marginalized Populations in Canada: Physical Distancing Impacts, SARS-CoV-2 Seroprevalence, and Health and Wellness Needs [2SLGBTQQIAplus-COVID-19, study data contributed to the CITF Databank]

description: &lt;b&gt;Background:&lt;/b&gt; Two-Spirit, lesbian, gay, bisexual, trans, queer, questioning, intersex, asexual, and other sexual- and gender-marginalized people experience health inequities that may have resulted in greater impact of COVID-19 disease and public health measures. &lt;br&gt;

 

&lt;b&gt;Aims of the CITF co-funded study:&lt;/b&gt;The study aimed to conduct an online survey of 2SLGBTQQIA+ individuals across urban and non-urban regions in Canada to evaluate the impact of COVID-19 on their health, wellness, stigma, and material security. &lt;br&gt;

 

&lt;b&gt;Methods:&lt;/b&gt; This cross-sectional study recruited individuals who identified as a gender or sex minority or a sexual orientation minority, were at least 15 years old, and resided in Canada during the COVID-19 pandemic. Participants were recruited via media advertisements. Researchers collected information via an online survey offered in English, French, and Spanish, and used a community-based approach to engage participants. Participants over the age of 18 were given the option to provide a self-collected dried blood spot (DBS) via a mailed kit to test for SARS-CoV-2. &lt;br&gt;

 

&lt;b&gt;Contributed dataset contents:&lt;/b&gt; The datasets include 4013 participants who completed baseline interviews between April 2022 and September 2022. 30% of participants gave one blood sample for SARS-CoV-2 serology between March 2022 and February 2023. Variables include data in the following areas of information: demographics (age, gender, race-ethnicity and indigeneity, province), general health (chronic conditions; flu vaccine), SARS-CoV-2 vaccination, and serology.
description: Data Access Portal (https://portal.citf.mcgill.ca/data-access-process)