cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25919/5b8f22a214acf
title: Soil drainage DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil drainage 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 drainage describes local soil wetness conditions (rate of water movement from the site soil profile). This soil drainage raster data represents a modelled dataset of profile drainage as described by the National Committee on Soil and Terrain 2009 (NCST) and is derived from field measured site data and environmental covariates. Data values are: 1 Very poorly drained, 2 Poorly drained, 3 Imperfectly drained, 4 Moderately well drained, 5 Well drained, 6 Rapidly drained. Soil drainage is a parameter used in land suitability assessments of soil wetness in combination with soil permeability indicating site and soil conditions that result in poor soil aeration for plant growth eg excess water on the soil surface or in the soil profile caused from inadequate site drainage reduces crop growth and quality and restricts machinery use. 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.1408628
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS soy

description: This is model output from LPJ-GUESS for soy as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408633
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS sugar beet

description: This is model output from LPJ-GUESS for sugar beet as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5517/ccdc.csd.cc203m6z
title: CCDC 1850520: Experimental Crystal Structure Determination

description: Related Article: Wei Huang, You-Can Zhang, Rui Jin, Bai-Ling Chen, Zili Chen|2018|Organometallics|37|3196|doi:10.1021/acs.organomet.8b00524
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.cc204118
title: CCDC 1850918: Experimental Crystal Structure Determination

description: Related Article: Grace B. Panetti, Jerome R. Robinson, Patrick J. Carroll, Michael R. Gau, Brain C. Manor, Patrick J. Walsh, Eric J. Schelter|2018|Dalton Trans.|47|14408|doi:10.1039/C8DT03335H
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.cc204129
title: CCDC 1850919: Experimental Crystal Structure Determination

description: Related Article: Grace B. Panetti, Jerome R. Robinson, Patrick J. Carroll, Michael R. Gau, Brain C. Manor, Patrick J. Walsh, Eric J. Schelter|2018|Dalton Trans.|47|14408|doi:10.1039/C8DT03335H
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.cc20413b
title: CCDC 1850920: Experimental Crystal Structure Determination

description: Related Article: Grace B. Panetti, Jerome R. Robinson, Patrick J. Carroll, Michael R. Gau, Brain C. Manor, Patrick J. Walsh, Eric J. Schelter|2018|Dalton Trans.|47|14408|doi:10.1039/C8DT03335H
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.cc20414c
title: CCDC 1850921: Experimental Crystal Structure Determination

description: Related Article: Grace B. Panetti, Jerome R. Robinson, Patrick J. Carroll, Michael R. Gau, Brain C. Manor, Patrick J. Walsh, Eric J. Schelter|2018|Dalton Trans.|47|14408|doi:10.1039/C8DT03335H
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.cc20415d
title: CCDC 1850922: Experimental Crystal Structure Determination

description: Related Article: Grace B. Panetti, Jerome R. Robinson, Patrick J. Carroll, Michael R. Gau, Brain C. Manor, Patrick J. Walsh, Eric J. Schelter|2018|Dalton Trans.|47|14408|doi:10.1039/C8DT03335H
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.cc20416f
title: CCDC 1850923: Experimental Crystal Structure Determination

description: Related Article: Grace B. Panetti, Jerome R. Robinson, Patrick J. Carroll, Michael R. Gau, Brain C. Manor, Patrick J. Walsh, Eric J. Schelter|2018|Dalton Trans.|47|14408|doi:10.1039/C8DT03335H
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.cc204gtg
title: CCDC 1851345: Experimental Crystal Structure Determination

description: Related Article: Nian Zhao, Lun Yang, Bo Xie, Juanjuan Han, Qiyun Pan, Xiang Li, Meifeng Liu, Yu Wang, Xiuzhang Wang, Guangshan Zhu|2018|Chem.Commun.|54|11264|doi:10.1039/C8CC05404E
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/ojbz67/4wo9qs
title: 17723288_48_18232891_TP_0_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/ef1tr7
title: 17723364_51_17838712_TP_1_VarLen_Trend4Hz_IHR.txt
DOI: 10.7910/dvn/ojbz67/fpmseo
title: 17723288_48_18232891_TP_0_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/ftxpdm
title: 17723288_48_18232891_TP_0_VarLen_Trend4Hz_Pleth_PTT.txt
DOI: 10.7910/dvn/ojbz67/k6sdiy
title: 17723288_46_18460950_TP_0_VarLen_Wave500Hz_Pleth.txt
DOI: 10.7910/dvn/ojbz67/ndzlxs
title: 17723288_48_18232891_TP_0_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/yomlhj
title: 17723364_51_17838712_TP_1_VarLen_Trend4Hz_RRI_DN.txt
DOI: 10.7910/dvn/ojbz67/yuuho9
title: 17723288_48_18232891_TP_0_VarLen_Wave500Hz_ECG II.txt
DOI: 10.25919/5b8f2306087cf
title: Soil permeability DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Soil permeability 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 permeability describes the ability of a soil to transmit water internally by its least permeable layer (rate of water movement into and through the soil profile). This soil permeability raster data represents a modelled dataset of permeability as described by the National Committee on Soil and Terrain 2009 (NCST) and is derived from field measured site data and environmental covariates. Data values are: 1 Very slowly permeable, 2 Slowly permeable, 3 Moderately permeable, 4 Highly permeable. Soil permeability is a parameter used in land suitability assessments of irrigation efficiency and soil wetness (in combination with soil drainage indicating site and soil conditions that result in poor soil aeration for 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: 10.25919/5b8f235e3f853
title: Depth of A horizon DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Depth of A horizon 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). Depth of A horizon indicates the depth of the surface layers of soil (A horizon). This modelled raster data is presented as a positive number in meters eg a value of 0.12 shows the A horizon is 12 cm deep, and is derived from measured site data and environmental covariates. Depth of A horizon is a parameter used in land suitability assessments of soil physical factors for; plant growth (seedling establishment), machinery operations and potential degradation risks associated with sodic soils. 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: 10.25919/5b8f239ac9a8a
title: Maximum clay% to 2m soil depth DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: Maximum clay% to 2m soil depth is one attribute of soils chosen to underpin the ringtank suitability assessment of the Northern Australia Water Resource Assessment (NAWRA) through the digital soil mapping process (DSM). This data indicates the maximum clay content reached in the soil profile to 2m depth expressed as a percent and is derived from analysed soil site data and environmental covariates. Clay percent is a parameter applied in the ringtank suitability rules in relation to construction and engineering properties for ringtanks. This raster data provides improved soil information used to identify opportunities and promote detailed investigation for a range of sustainable regional development options. 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 ringtank suitability assessment and results of the ringtank analysis this dataset underpins is described in the CSIRO NAWRA published report ‘Assessment of surface water storage options in the Fitzroy, Darwin and Mitchell catchments. A technical report to the Australian Government from the CSIRO Northern Australia Water Resource Assessment, part of the National Water Infrastructure Development Fund: Water Resource Assessments. CSIRO, Australia. Petheram et al 2017.'
DOI: 10.25919/5b8f240c28d0f
title: PAWC to 100cm DSM data of the Fitzroy catchment WA, Darwin catchments and Mitchell catchment Qld generated by the Northern Australia Water Resource Assessment

description: PAWC to 100cm 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). PAWC (plant available water capacity) indicates the ability of a soil to retain and supply water for plant growth. This PAWC raster data represents a modelled dataset of PAWC to 100cm (mm of water to 100cm of soil depth) and is derived from analysed site data, spline calculations and environmental covariates. PAWC is a parameter used in land suitability assessments for rainfed cropping and for water use efficiency in irrigated land uses. 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.1408632
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS sugar beet

description: This is model output from LPJ-GUESS for sugar beet as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1408634
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: LPJ-GUESS sorghum

description: This is model output from LPJ-GUESS for sorghum as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8