cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/5b8f2b187a8a5
title: Soil surface condition DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil surface condition is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil surface condition is described when dry as defined by the National Committee on Soil and Terrain 2009 (NCST) surface condition descriptions. This raster data represents a modelled dataset of soil surface condition and is derived from field measured site data and environmental covariates. Data values are: 1 Self mulching or self mulching and cracking, 2 Loose and/or soft, 3 Firm and/or hardsetting, 4 Surface crust, 5 Cracking. Soil surface condition is a parameter used in land suitability assessments of soil physical factors and affects; water infiltration, seedling establishment and machinery workability. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.
The DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.
DOI: 10.5281/zenodo.1408563
title: Olympic Games 2020

description: This dataset includes CSV files about players of games. We gathered the list of games from  https://en.wikipedia.org/wiki/2020_Summer_Olympics. The data in the CSV files are gathered from the below resources:

 http://www.adventurestats.com/tables/8000ergeo.shtmlhttp://www.bbc.com/news/magazine-28363129https://www.statcrunch.com/app/index.php?dataid=614855http://www.stadiumguide.com/figures-and-statistics/lists/europes-largest-football-stadiums/https://data.world/sports/olympics/file/outturn%20sports-related%20costs%20of%20the%20Olympic%20Games%20.csvhttp://www.bbc.com/news/magazine-28363129https://owlcation.com/stem/TopTenMountainRangeshttps://github.com/jokecamp/FootballData/blob/master/MLS/MLS%20-%202015/mls_players_2015-01-12.csvhttp://www.topendsports.com/events/summer/sports/number.htmhttp://newsok.sportsdirectinc.com/golf/pga-players.aspx?page=/data/pga/players/A_players.html
DOI: 10.7910/dvn/ojbz67/4abmwd
title: 9826410_32_17173883_TP_0_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/7n3ewg
title: 9826419_31_1302591_TP_0_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/bqxalu
title: 9826410_32_17173883_TP_0_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/ez1hdp
title: 9826410_32_17173883_TP_0_VarLen_Wave500Hz_ECG II.txt
DOI: 10.7910/dvn/ojbz67/o1tc72
title: 9826410_32_17173883_TP_0_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/pkp4pa
title: 9826410_32_17173883_TP_0_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/tztuvc
title: 17723489_61_18949676_TP_0_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/wcufry
title: 17723489_61_18949676_TP_0_VarLen_Wave500Hz_ECG II.txt
DOI: 10.25919/5b8f2bfedf6d1
title: Soil surface ESP DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil surface ESP (exchangeable sodium percentage) is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil surface ESP indicates chemical properties of a soil that influence soil structure stability (potential for erosion)  and water infiltration. This soil surface ESP raster data represents modelled data of ESP of the soil surface (&lt;0.10m) expressed as a percent and is derived from analysed site data and environmental covariates. Soil surface ESP is a parameter used in land suitability assessments of factors impacting water infiltration and potential erosion eg high ESP soils have reduced surface infiltration of rainfall and irrigation water. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.
The DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.
DOI: 10.25919/5b8f2c795d038
title: Soil surface pH DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil surface pH is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil surface pH is used as a general indicator or proxy of conditions that affect the availability of plant nutrients and potential nutrient toxicities and/or deficiencies. This soil surface pH raster data represents a modelled dataset of pH of the soil surface (&lt;0.10m) measured in standard pH units and is derived from field measurements, analysed site data and environmental covariates. The soil surface pH is a parameter used in land suitability assessments for indicating availability of nutrients for plant use or nutrient deficiencies and/or toxicities eg strong acidity or alkalinity may lead to reduced plant growth. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.
The DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.
DOI: 10.7910/dvn/ojbz67/16goh4
title: 515767251 eyrTFrxCN 13544330_379_VarLen_Wave500Hz_ECG_II.txt
DOI: 10.7910/dvn/ojbz67/8dcdrk
title: 9826419_31_1302591_TP_0_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/edbd9v
title: 515767251 eyrTFrxCN 13544330_379_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/hjpo9f
title: 515767251 eyrTFrxCN 13544330_379_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/imnwbr
title: 515768255 tgAFoBjbG 24898238_339_VarLen_Wave500Hz_ECG_II.txt
DOI: 10.7910/dvn/ojbz67/ktxvsc
title: 9826419_31_1302591_TP_0_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/n4vdm9
title: 515767251 eyrTFrxCN 13544330_379_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.21227/fpkq-za03
title: A Gradient-Based Reinforcement Learning Algorithm for Multiple Cooperative Agents

description: The dataset contains the simulation results on two stochastic games -- box pushing and distributed sensor network (DSN). The setting of parameters is given in the manuscript named "A Gradient-Based Reinforcement Learning Algorithm for Multiple Cooperative Agents".
DOI: 10.25919/5b8f2fc5bda16
title: Soil surface salinity DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil surface salinity is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil salinity represents the salt content of the soil. This raster data represents a modelled dataset of salinity at the soil surface and is derived from field measured and laboratory analysed site data, and environmental covariates. Data values are: 1 Surface salinity present, 4 Surface salinity absent. Soil surface salinity is a parameter used in land suitability assessments as it hinders seed establishment and retards plant growth. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.
The DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.
DOI: 10.25919/5b8f303d644b9
title: Soil surface structure DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil surface structure is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil structure describes the size, shape and strength of peds (soil aggregates). This soil surface structure raster data represents a modelled dataset of soil structure for the major part of the A horizons (surface soil) and is derived from field measured site data and environmental covariates. Data values are: 1 Single grain, 2 Massive or weak, 3 Moderate/strong and fine, 4 Moderate/strong and coarse as defined by the National Committee on Soil and Terrain 2009 (NCST) structure descriptions. Soil surface structure is a parameter used in land suitability assessments of soil physical factors and affects; water infiltration, erosion, seedling establishment and machinery workability. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.
The DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.
DOI: 10.25919/5b8f30751cd38
title: Soil surface texture DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil surface texture is one of 18 attributes of soils chosen to underpin the land suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). Soil texture is determined by the percentage and size distribution of mineral (sand, silt and clay) particles of the soil finer than 2mm, carried out in the field. This soil surface texture raster data represents a modelled dataset of soil texture for the major part of the A horizons (surface soil) and is derived from field measured site data and environmental covariates. The soil texture classes are based on the field texture classes of the National Committee on Soil and Terrain 2009 (NCST) texture descriptions. Data values are: 1 Sandy, 2 Loamy, 3 Silty, 4 Clayey and the texture groupings behind these values are supplied in the word document READ_ME_Texture_Classes. Soil surface texture is a parameter used in land suitability assessments of soil physical factors and affects; water infiltration, water holding capacity, permeability, drainage, water and wind erosion, workability (soil adhesiveness), trafficability and soil nutrients levels. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options and was created within the ‘Land Suitability’ activity of the CSIRO NAWRA. A companion dataset and statistics reflecting reliability of this data are also provided and can be found described in the lineage section of this metadata record. Processing information is supplied in ranger R scripts and attributes were modelled using a Random Forest approach.
The DSM process is described in the CSIRO NAWRA published report ‘Digital soil mapping of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'. The land suitability assessment this dataset underpins is described in the CSIRO NAWRA published report ‘Land suitability of the Fitzroy, Darwin and Mitchell catchments. A technical report from the CSIRO Northern Australia Water Resource Assessment to the Government of Australia'.
DOI: 10.5517/ccdc.csd.cc1n4lm0
title: CCDC 1523762: Experimental Crystal Structure Determination

description: Related Article: Julie E. Niklas, Emily E. Hardy, Anne E. V. Gorden|2018|Chem.Commun.|54|11693|doi:10.1039/C8CC05242E
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.7910/dvn/ojbz67/act7ve
title: 515768255 tgAFoBjbG 24898238_339_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/akj6vy
title: 515769246 tYX 22294348_855_VarLen_Wave500Hz_ECG_II.txt
DOI: 10.7910/dvn/ojbz67/jhanpv
title: 515769246 tYX 22294348_855_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/pc13di
title: 515769253 ZnrMLHcbG 20322957_1454_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/qr4azo
title: 515768255 tgAFoBjbG 24898238_339_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/sudejo
title: 515768255 tgAFoBjbG 24898238_339_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/wgnsag
title: 515769246 tYX 22294348_855_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/ypmde7
title: 515769246 tYX 22294348_855_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.5281/zenodo.1408558
title: Construction, Validation And Application Of Nocturnal Pollen Transport Networks In An Agro-Ecosystem: Datasets Collected Using Light Microscopy And Dna Metabarcoding

description: This dataset contains all data required to reproduce the analyses conducted in Macgregor <em>et al. </em>(2018), using the R Notebook archived at doi: 10.5281/zenodo.1322712.

Specifically, the dataset contains details of pollen transport detected on two matched samples, each containing 311 moths of 41 species, using two methods: a traditional light microscopy approach and a novel DNA metabarcoding approach. Both raw and manually-curated versions of each dataset are archived for full clarity. The dataset additionally contains all metadata required to fully interpret these data, including the RGB tables used to prepare Fig 4 in Macgregor <em>et al. </em>(2018).

Macgregor <em>et al. </em>(2018) Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using light microscopy and DNA metabarcoding. <em>Ecological Entomology</em>, doi: 10.1111/een.12674.
description: This work was funded by the Natural Environment Research Council (grant ID: NE/K007394/1).
description: {"references": ["Macgregor\u00a0et al.\u00a0(2018) Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using light microscopy and DNA metabarcoding.\u00a0Ecological Entomology,\u00a0doi: 10.1111/een.12674."]}
DOI: 10.5281/zenodo.1408559
title: Construction, Validation And Application Of Nocturnal Pollen Transport Networks In An Agro-Ecosystem: Datasets Collected Using Light Microscopy And Dna Metabarcoding

description: This dataset contains all data required to reproduce the analyses conducted in Macgregor <em>et al. </em>(2018), using the R Notebook archived at doi: 10.5281/zenodo.1322712.

Specifically, the dataset contains details of pollen transport detected on two matched samples, each containing 311 moths of 41 species, using two methods: a traditional light microscopy approach and a novel DNA metabarcoding approach. Both raw and manually-curated versions of each dataset are archived for full clarity. The dataset additionally contains all metadata required to fully interpret these data, including the RGB tables used to prepare Fig 4 in Macgregor <em>et al. </em>(2018).

Macgregor <em>et al. </em>(2018) Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using light microscopy and DNA metabarcoding. <em>Ecological Entomology</em>, doi: 10.1111/een.12674.
description: This work was funded by the Natural Environment Research Council (grant ID: NE/K007394/1).
description: {"references": ["Macgregor\u00a0et al.\u00a0(2018) Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using light microscopy and DNA metabarcoding.\u00a0Ecological Entomology,\u00a0doi: 10.1111/een.12674."]}
DOI: 10.5517/ccdc.csd.cc1pnc4v
title: CCDC 1568697: Experimental Crystal Structure Determination

description: Related Article: Chenyang Zhao, Thomas Schwartz, Berthold Stöger, Fraser J. White, Jiangshan Chen, Dongge Ma, Johannes Fröhlich, Paul Kautny|2018|J.Mater.Chem.C|6|9914|doi:10.1039/C8TC03537G
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1q1t0l
title: CCDC 1580659: Experimental Crystal Structure Determination

description: Related Article: Mei-Ling Feng,  Debajit Sarma,  Yu-Jie Gao,  Xing-Hui Qi,  Wei-An Li,  Xiao-Ying Huang,  Mercouri G. Kanatzidis|2018|J.Am.Chem.Soc.|140|11133|doi:10.1021/jacs.8b07457
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1zp8xv
title: CCDC 1837708: Experimental Crystal Structure Determination

description: Related Article: Liam Hughes, Con McElroy, Adrian Whitwood, Andrew J. Hunt|2018|Green Chemistry|20|4423|doi:10.1039/C8GC01227J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1zp8yw
title: CCDC 1837709: Experimental Crystal Structure Determination

description: Related Article: Liam Hughes, Con McElroy, Adrian Whitwood, Andrew J. Hunt|2018|Green Chemistry|20|4423|doi:10.1039/C8GC01227J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1ztg4d
title: CCDC 1841714: Experimental Crystal Structure Determination

description: Related Article: Fei-Long Hu, Yan Mi, Chen Zhu, Brendan F. Abrahams, Pierre Braunstein, and Jian-Ping Lang|2018|Angew.Chem.,Int.Ed.|57|12696|doi:10.1002/anie.201806076
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.7910/dvn/ojbz67/9jmvg2
title: 515769253 ZnrMLHcbG 20322957_1454_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/cdeuz7
title: 515770244 qynHpusXZI 12108017_301_VarLen_Wave500Hz_ECG_II.txt
DOI: 10.7910/dvn/ojbz67/klst8w
title: 515769253 ZnrMLHcbG 20322957_1454_VarLen_Wave500Hz_Pleth-PLETH(-).txt
DOI: 10.7910/dvn/ojbz67/omc1q2
title: 515770250 tgAFMrxWx 20662028_2027_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/q2dxx0
title: 515769253 ZnrMLHcbG 20322957_1454_VarLen_Wave500Hz_ECG_II.txt
DOI: 10.7910/dvn/ojbz67/uhxuxz
title: 515770244 qynHpusXZI 12108017_301_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/y7lxri
title: 515770244 qynHpusXZI 12108017_301_VarLen_Trend4Hz_Pleth_PTT.txt