cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc1pk99v
title: CCDC 1565757: Experimental Crystal Structure Determination

description: Related Article: Wei-Yi Lu, Hsiu-Wei Ou, Chieh-Ning Lee, Jaya Kishore Vandavasi, Hsuan-Ying Chen, Chu-Chieh Lin|2018|Polymer|139|1|doi:10.1016/j.polymer.2018.02.002
description: Related Article: Hsuan Chen|2017|CSD Communication|||
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.cc1pk9cx
title: CCDC 1565759: Experimental Crystal Structure Determination

description: Related Article: Wei-Yi Lu, Hsiu-Wei Ou, Chieh-Ning Lee, Jaya Kishore Vandavasi, Hsuan-Ying Chen, Chu-Chieh Lin|2018|Polymer|139|1|doi:10.1016/j.polymer.2018.02.002
description: Related Article: Hsuan Chen|2017|CSD Communication|||
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.cc1pk9dy
title: CCDC 1565760: Experimental Crystal Structure Determination

description: Related Article: Wei-Yi Lu, Hsiu-Wei Ou, Chieh-Ning Lee, Jaya Kishore Vandavasi, Hsuan-Ying Chen, Chu-Chieh Lin|2018|Polymer|139|1|doi:10.1016/j.polymer.2018.02.002
description: Related Article: Hsuan Chen|2017|CSD Communication|||
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.cc1pk9fz
title: CCDC 1565761: Experimental Crystal Structure Determination

description: Related Article: Wei-Yi Lu, Hsiu-Wei Ou, Chieh-Ning Lee, Jaya Kishore Vandavasi, Hsuan-Ying Chen, Chu-Chieh Lin|2018|Polymer|139|1|doi:10.1016/j.polymer.2018.02.002
description: Related Article: Hsuan Chen|2017|CSD Communication|||
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.cc1pk9g0
title: CCDC 1565762: Experimental Crystal Structure Determination

description: Related Article: Wei-Yi Lu, Hsiu-Wei Ou, Chieh-Ning Lee, Jaya Kishore Vandavasi, Hsuan-Ying Chen, Chu-Chieh Lin|2018|Polymer|139|1|doi:10.1016/j.polymer.2018.02.002
description: Related Article: Hsuan Chen|2017|CSD Communication|||
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: 10.4225/08/597fc4d49ee2d
title: Potential vegetation distribution: New South Wales - 3arcsecond gridded 1990-centred baseline predictions of the pre-clearing extents of "Keith" Vegetation Classes using kernel regression with GDM-scaled environments for Vascular Plants

description: This collection contains 3-arcsecond gridded datasets (ESRI binary float format in WGS84) showing the baseline (1990-centred) predicted potential distribution of 102 (class numbers range between 1 and 125) "Keith" Vegetation Classes for New South Wales based on their correlation with baseline ecological environments (c.1990 climates, substrate and landform). The vegetation patterns and classification derive from a map for NSW compiled by David Keith. A kernel regression was used with a geographically even sample of 9,951 locations of training classes for the 102 classes attributed with 21 GDM-scaled environmental predictors for Vascular Plants representing baseline ecological environments. The training class data input to the kernel regression is provided with this package. The GDM-scaled environmental predictors, source biological data and model fit parameters are also provided with the data package. Using the 1990 baseline training class data, and without constraining the prediction to pre-existing map boundaries, the kernel regression predicted the potential distribution of the 102 Vegetation Classes using 1990-centred (30 year average) baseline climates derived from ANUCLIM v6.1 (Xu and Hutchinson 2011) and soil/geology/landform attributes. The kernel regression generates unconstrained probabilities varying in the range from 0 and up to 1 for each of the 102 classes. The data are provided as 3-arcsecond (approximately 90m), ESRI binary float grid format in WGS84. Each class is denoted “UNCON###”, where the number refers to the code originally assigned to that class in the vegetation map. A lookup table linking the vegetation classes to the output codes and descriptive title is provided. The methods are described in "Doerr, VAJ, Williams, KJ, Drielsma, M, Doerr, ED, Davies, MJ, Love, J, Langston, A, Low Choy, S, Manion, G, Cawsey, EM, McGinness, HM, Jovanovic, T, Crawford, D, Austin, M & Ferrier, S 2013, Designing landscapes for biodiversity under climate change: Final report, National Climate Change Adaptation Research Facility, Gold Coast, 260 pp.". A plain English description of the method used (but applied Nationally) can be found in the AdaptNRM Guide “Helping biodiversity adapt to climate change: a community-level modelling approach”, available online at: www.adaptnrm.org. Source of vegetation class data: KEITH, D. A. (2002) A compilation map of native vegetation for New South Wales. NSW Biodiversity Strategy, New South Wales Government. KEITH, D. A. (2004) Ocean shores to desert dunes, Hurstville, Department of Environment and Conservation (NSW).
DOI: 10.15129/3878b808-70e6-4d45-b3b3-972cb08ce4b9
title: Pitch angle scattering of relativistic electrons near EMIC resonances in diverging magnetic fields

description: The dataset contains simulation data of the propagation of electromagnetic ion cyclotron (EMIC) waves in a plasma with diverging magnetic field. The data is part of a theoretical and numerical investigation of the pitch angle scattering of relativistic electrons on EMIC waves with relevance to the Earth's radiation belts in the ionosphere where trapped energetic particles constitute a hazard for satellites, and to laboratory experiments at the UCLA LAPD plasma chamber where EMIC wave propagation and pitch angle scattering can be studied experimentally.
DOI: 10.24388/gal_fl_5
title: Experimental and theoretical combustion data based on the article Bradley, Lawes, D.M., Liu, K., Verhelst, S., Woolley, R., Combustion and Flame 2007, (149), (1-2), 162-172., Fig. 10., open circle, 1 MPa

description: Initial composition: H2 O2 N2
DOI: 10.6078/m74q7s2x
title: Differentiating local from nonlocal ceramic production at Iron Age Sardis using NAA
DOI: 10.4225/08/597fca7f9f1fb
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected March 2016 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.4225/08/597fcac766eee
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected July 2016 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.4225/08/597fcb04f0dda
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected May 2016 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.4225/08/597fcb48cffce
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected March 2017 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.4225/08/597fcb8ce7fde
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected September 2016 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.4225/08/597fcbc946387
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected November 2016 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.4225/08/597fcc0797a16
title: Discrete Total Alkalinity and Total Carbon Dioxide measurements collected June 2017 onboard the RTM Wakmatha on the Great Barrier Reef, Australia.

description: The Future Reef 2.0 project monitors ocean chemistry along the entire length of the Great Barrier Reef using the Rio Tinto ship, RTM Wakmatha. The research is targeted at providing information on the CO2 uptake, controls on ocean acidification change in the region, and providing data on reef health. It is providing foundation data needed to assess the vulnerability of the Great Barrier Reef to ocean acidification. This project is a partnership between Rio Tinto, the Great Barrier Reef Foundation and CSIRO. 
This dataset contains quality controlled discrete samples for total dissolved inorganic carbon dioxide (TCO2) and total alkalinity (TA) measured following techniques developed for measurements in ocean waters on WOCE/CLIVAR sections. Certified reference materials (CRMs) from the Scripps Institution of Oceanography are analysed to determine the accuracy and precision of the measurements are analysed to determine the accuracy and precision of the measurements.  Detailed analytical procedures are provided in Dickson et al (2007).
The data management and distribution of these data were supported by the CSIRO Carbon Collaboration Cluster and the Australian Coastal Ecosystem Facility.

References:
Dickson, A.G., Sabine, C.L and Christian, J.R. (Eds) (2007). Guide to Best Practices for Ocean CO2 Measurements. PICES Special Publication 3.
DOI: 10.5281/zenodo.7312986
title: Data set for "Landscape-variability of the carbon balance across managed boreal forests"

description: This data set is a compilation of biometric- and chamber-based annual CO<sub>2</sub> flux estimates obtained during the period 2016–2018. Data were collected in 50 main forest stands within the Krycklan Catchment Study (KCS, https://www.slu.se/Krycklan), a multi-scale long-term monitored boreal catchment spanning 68 km<sup>2</sup> in northern Sweden. Seven additional old forest stands were also included with the aim to reconcile our CO<sub>2</sub> flux estimates for the old age class. Selected forest stands encompassed different landscape attributes: 1) soil type (i.e., sediment and till), 2) dominant tree species (i.e., pine and spruce), and 3) stand age class (i.e., initiation, young, middle-aged, mature, and old stands). Annual CO<sub>2</sub> fluxes included are the following: net ecosystem production (NEP), net primary production (NPP), net primary production of trees (NPP<sub>t</sub>), net primary production of understory (NPP<sub>u</sub>) as well as total heterotrophic respiration (RH) and its soil and dead wood components (RH<sub>s</sub> and RH<sub>dw</sub>, respectively). All component CO<sub>2</sub> fluxes are presented as positive terms, whereas positive and negative NEP refers to net C sink and source, respectively. It also includes a set of potential abiotic and biotic drivers controlling NEP and its component fluxes at the landscape-scale. This data set is composed of three Microsoft Excel worksheets: readme, metadata, and data. More details can be found in Peichl et al. (2022) Landscape-variability of the carbon balance across managed boreal forests. Global Change Biology, 00, 1–14. https://doi.org/10.1111/gcb.16534. Contact information: Professor Matthias Peichl (Matthias.Peichl@slu.se) Ph.D. Eduardo Martínez García (Eduardo.Martinez@slu.se, edu.martinez.garcia@gmail.com) Department of Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), Skogsmarksgränd 17, SE-901 83, Umeå, Sweden
DOI: 10.5281/zenodo.7312985
title: Data set for "Landscape-variability of the carbon balance across managed boreal forests"

description: This data set is a compilation of biometric- and chamber-based annual CO<sub>2</sub> flux estimates obtained during the period 2016–2018. Data were collected in 50 main forest stands within the Krycklan Catchment Study (KCS, https://www.slu.se/Krycklan), a multi-scale long-term monitored boreal catchment spanning 68 km<sup>2</sup> in northern Sweden. Seven additional old forest stands were also included with the aim to reconcile our CO<sub>2</sub> flux estimates for the old age class. Selected forest stands encompassed different landscape attributes: 1) soil type (i.e., sediment and till), 2) dominant tree species (i.e., pine and spruce), and 3) stand age class (i.e., initiation, young, middle-aged, mature, and old stands). Annual CO<sub>2</sub> fluxes included are the following: net ecosystem production (NEP), net primary production (NPP), net primary production of trees (NPP<sub>t</sub>), net primary production of understory (NPP<sub>u</sub>) as well as total heterotrophic respiration (RH) and its soil and dead wood components (RH<sub>s</sub> and RH<sub>dw</sub>, respectively). All component CO<sub>2</sub> fluxes are presented as positive terms, whereas positive and negative NEP refers to net C sink and source, respectively. It also includes a set of potential abiotic and biotic drivers controlling NEP and its component fluxes at the landscape-scale. This data set is composed of three Microsoft Excel worksheets: readme, metadata, and data. More details can be found in Peichl et al. (2022) Landscape-variability of the carbon balance across managed boreal forests. Global Change Biology, 00, 1–14. https://doi.org/10.1111/gcb.16534. Contact information: Professor Matthias Peichl (Matthias.Peichl@slu.se) Ph.D. Eduardo Martínez García (Eduardo.Martinez@slu.se, edu.martinez.garcia@gmail.com) Department of Forest Ecology and Management, Swedish University of Agricultural Sciences (SLU), Skogsmarksgränd 17, SE-901 83, Umeå, Sweden
DOI: 10.5281/zenodo.7400548
title: maxillicosta_whitleyi_ragtag_01.fasta.gz

description: .
DOI: 10.5281/zenodo.7400547
title: maxillicosta_whitleyi_ragtag_01.fasta.gz

description: .
DOI: 10.6084/m9.figshare.21674528
title: Orthographically transcribed elicited spoken data

description: The data was elicited by some speech tasks
DOI: 10.6084/m9.figshare.21674528.v1
title: Orthographically transcribed elicited spoken data

description: The data was elicited by some speech tasks
DOI: 10.5281/zenodo.7395829
title: Idealized simulations of marine ice sheet instability

description: Ensemble of idealized simulations of the unstable retreat of an outlet glacier with the Parallel Ice Sheet Model (PISM). Varied parameters are the width, length and depth of the glacier, the softness of the ice and the basal friction.
DOI: 10.6084/m9.figshare.21674543
title: downy mildew on spinach chr3

description: spinach, downy mildew, disease resistance,molecular marker; breeding
DOI: 10.18712/ess10cf
title: ESS10 - data from Contact forms, edition 2.0