cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.5813779
title: Daily Rainfall Anomalies in the Brazilian Northeast (DRA-BNE)

description: This dataset contains the daily precipitation anomalies in the Brazilian northeast calculated from the GPCP dataset (combined sources of precipitation measurement) in the period from 1996-10-01 to 2021-07-31, in the geographic boundaries 42°W - 30°W/20.5°S - 0°. The GPCP dataset has an original resolution of 1 degree, but this dataset was interpolated by the bilinear method, obtaining a resolution of 0.25 degrees.
description: This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – through the project Ciências do Mar II, AUXPE 1979/2014 and a pos doc grant to H. L. Varona. Finance Code 001. Humberto L. Varona and Moacyr Araujo acknowledges the support of the Brazilian Research Network on Global Climate Change-Rede CLIMA (FINEP grants 01.13.0353-00). This work is a contribution to the Projects INCT AmbTropic–Brazilian National Institute of Science and Technology for Tropical Marine Environments (grants 565054/2010-4, 625 8936/2011, and 465634/2014-1, CNPq/FAPESB/CAPES), and to the International Joint Laboratory TAPIOCA (IRD-UFPE-UFRPE).
description: {"references": ["H. L. Varona. (2021). mNC: A tool for Oceanographers and Meteorologists to easily create their NetCDF files using Matlab (1.0). Zenodo. https://doi.org/10.5281/zenodo.5572749", "H. L. Varona. (2021). CalcPlotAnomaly: Matlab function set for the calculation and plotting of anomalies (1.01). Zenodo. https://doi.org/10.5281/zenodo.5576889"]}
DOI: 10.5281/zenodo.5559237
title: Daily Rainfall Anomalies in the Brazilian Northeast (DRA-BNE)

description: This dataset contains the daily precipitation anomalies in the Brazilian northeast calculated from the GPCP dataset (combined sources of precipitation measurement) in the period from 1996-10-01 to 2021-07-31, in the geographic boundaries 42°W - 30°W/20.5°S - 0°. The GPCP dataset has an original resolution of 1 degree, but this dataset was interpolated by the bilinear method, obtaining a resolution of 0.25 degrees.
description: This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – through the project Ciências do Mar II, AUXPE 1979/2014 and a pos doc grant to H. L. Varona. Finance Code 001. Humberto L. Varona and Moacyr Araujo acknowledges the support of the Brazilian Research Network on Global Climate Change-Rede CLIMA (FINEP grants 01.13.0353-00). This work is a contribution to the Projects INCT AmbTropic–Brazilian National Institute of Science and Technology for Tropical Marine Environments (grants 565054/2010-4, 625 8936/2011, and 465634/2014-1, CNPq/FAPESB/CAPES), and to the International Joint Laboratory TAPIOCA (IRD-UFPE-UFRPE).
description: {"references": ["H. L. Varona. (2021). mNC: A tool for Oceanographers and Meteorologists to easily create their NetCDF files using Matlab (1.0). Zenodo. https://doi.org/10.5281/zenodo.5572749", "H. L. Varona. (2021). CalcPlotAnomaly: Matlab function set for the calculation and plotting of anomalies (1.01). Zenodo. https://doi.org/10.5281/zenodo.5576889"]}
DOI: 10.5281/zenodo.5559266
title: Monthly Anomalies of Oceanographic Parameters in the Brazilian Northeast (MAOP-BNE)

description: This dataset is formed by the anomalies of the main oceanic parameters: potential temperature, salinity, surface heat flux, mixed layer depth, sea surface height, density, wind forcings and marine currents, this is calculated from the monthly mean dataset SODA with an original resolution of 1/2 degree, which was interpolated with the bilinear method at 1/4 degree. The time period is from 1980-01-16 to 2017-12-12 and is geographically limited by 42°W - 30°W / 20°S - 0°. In this dataset, the coordinate system of the currents and the wind forcings are different from the coordinate system of the rest of the variables, for that reason they are in separate files.
description: This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – through the project Ciências do Mar II, AUXPE 1979/2014 and a pos doc grant to H. L. Varona. Finance Code 001. Humberto L. Varona and Moacyr Araujo acknowledges the support of the Brazilian Research Network on Global Climate Change-Rede CLIMA (FINEP grants 01.13.0353-00). This work is a contribution to the Projects INCT AmbTropic–Brazilian National Institute of Science and Technology for Tropical Marine Environments (grants 565054/2010-4, 625 8936/2011, and 465634/2014-1, CNPq/FAPESB/CAPES), and to the International Joint Laboratory TAPIOCA (IRD-UFPE-UFRPE).
description: {"references": ["H. L. Varona. (2021). mNC: A tool for Oceanographers and Meteorologists to easily create their NetCDF files using Matlab (1.0). Zenodo. https://doi.org/10.5281/zenodo.5572749", "H. L. Varona. (2021). CalcPlotAnomaly: Matlab function set for the calculation and plotting of anomalies (1.01). Zenodo. https://doi.org/10.5281/zenodo.5576889"]}
DOI: 10.5281/zenodo.5559265
title: Monthly Anomalies of Oceanographic Parameters in the Brazilian Northeast (MAOP-BNE)

description: This dataset is formed by the anomalies of the main oceanic parameters: potential temperature, salinity, surface heat flux, mixed layer depth, sea surface height, density, wind forcings and marine currents, this is calculated from the monthly mean dataset SODA with an original resolution of 1/2 degree, which was interpolated with the bilinear method at 1/4 degree. The time period is from 1980-01-16 to 2017-12-12 and is geographically limited by 42°W - 30°W / 20°S - 0°. In this dataset, the coordinate system of the currents and the wind forcings are different from the coordinate system of the rest of the variables, for that reason they are in separate files.
description: This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – through the project Ciências do Mar II, AUXPE 1979/2014 and a pos doc grant to H. L. Varona. Finance Code 001. Humberto L. Varona and Moacyr Araujo acknowledges the support of the Brazilian Research Network on Global Climate Change-Rede CLIMA (FINEP grants 01.13.0353-00). This work is a contribution to the Projects INCT AmbTropic–Brazilian National Institute of Science and Technology for Tropical Marine Environments (grants 565054/2010-4, 625 8936/2011, and 465634/2014-1, CNPq/FAPESB/CAPES), and to the International Joint Laboratory TAPIOCA (IRD-UFPE-UFRPE).
description: {"references": ["H. L. Varona. (2021). mNC: A tool for Oceanographers and Meteorologists to easily create their NetCDF files using Matlab (1.0). Zenodo. https://doi.org/10.5281/zenodo.5572749", "H. L. Varona. (2021). CalcPlotAnomaly: Matlab function set for the calculation and plotting of anomalies (1.01). Zenodo. https://doi.org/10.5281/zenodo.5576889"]}
DOI: 10.7934/p4160
title: Fossil coleoid cephalopod from the Mississippian Bear Gulch Lagerstätte sheds light on early vampyropod evolution (project)
DOI: 10.6084/m9.figshare.17035481.v1
title: Appendix F - Filtered ASV Results and Summary Table

description: This dataset is the filtered ASV reads provided by MetagenomBio Inc. This is the "raw" data that was used for analysis of the effect of glyphosate on the bacterial component of freshwater biofilms. <br>This dataset is a part of Lauren Koiter’s M.Sc. Thesis through the University of Waterloo Department of Biology. The thesis is researching the effects of glyphosate on the bacteria and archaea community composition of freshwater biofilms in North America. Full information on the materials and methods used in data collection is available in the thesis through the University of Waterloo. <br>
DOI: 10.5281/zenodo.6339575
title: Cluj Airport - Data related to interdependencies and to Quality of Life

description: <strong>Data on interdependencies</strong> The case study about interdependencies between noise, emissions (CO2, CO, NOx) was performed within the local context of Cluj-Napoca (Avram Iancu) International Airport (Romania) by COMOTI (Romania). <br> Airline data and support was provided by Blue Air Aviation and Getsafe Aviation Solutions and Cluj-Napoca Airport.<br> The sample provided here shows an example of data used to perform analyses in order to outline their effect in terms of noise and emissions. Further, the aim was to inform relevant stakeholders (e.g. airport, airlines, ANSP) about these outcomes and to provide insights about possible methods to protect the population within the area during planning of operations phases. <br> This data set contains two examples of some flight data, one related to departure and another to arrival operations.<br> More information about the case study can be read in the publication "D2.11 Recommendations from exemplification case studies summary and implications for BP dissemination" (https://doi.org/10.5281/zenodo.5604651) <strong>Data on Quality of Life</strong> The case study about the quality of life around Cluj-Napoca (Avram Iancu) International Airport (Romania) was developed by COMOTI (Romania), in partnership with Cluj-Napoca Airport (Romania), NLR (The Netherlands), ZEUS (Germany) and MMU (United Kingdom). Its aim was to identify possible opportunities of an airport to increase the quality-of-life of residents living near the airport. <br> This is a sample of data collected from the population feedback to questions formulated around quality of life dimensions and indicators. <br> More information about the case study can be read in the publication "D2.11 Recommendations from exemplification case studies summary and implications for BP dissemination" (https://doi.org/10.5281/zenodo.5604651).
DOI: 10.5281/zenodo.6339574
title: Cluj Airport - Data related to interdependencies and to Quality of Life

description: <strong>Data on interdependencies</strong> The case study about interdependencies between noise, emissions (CO2, CO, NOx) was performed within the local context of Cluj-Napoca (Avram Iancu) International Airport (Romania) by COMOTI (Romania). <br> Airline data and support was provided by Blue Air Aviation and Getsafe Aviation Solutions and Cluj-Napoca Airport.<br> The sample provided here shows an example of data used to perform analyses in order to outline their effect in terms of noise and emissions. Further, the aim was to inform relevant stakeholders (e.g. airport, airlines, ANSP) about these outcomes and to provide insights about possible methods to protect the population within the area during planning of operations phases. <br> This data set contains two examples of some flight data, one related to departure and another to arrival operations.<br> More information about the case study can be read in the publication "D2.11 Recommendations from exemplification case studies summary and implications for BP dissemination" (https://doi.org/10.5281/zenodo.5604651) <strong>Data on Quality of Life</strong> The case study about the quality of life around Cluj-Napoca (Avram Iancu) International Airport (Romania) was developed by COMOTI (Romania), in partnership with Cluj-Napoca Airport (Romania), NLR (The Netherlands), ZEUS (Germany) and MMU (United Kingdom). Its aim was to identify possible opportunities of an airport to increase the quality-of-life of residents living near the airport. <br> This is a sample of data collected from the population feedback to questions formulated around quality of life dimensions and indicators. <br> More information about the case study can be read in the publication "D2.11 Recommendations from exemplification case studies summary and implications for BP dissemination" (https://doi.org/10.5281/zenodo.5604651).
DOI: 10.6084/m9.figshare.17035481
title: Appendix F - Filtered ASV Results and Summary Table

description: This dataset is the filtered ASV reads provided by MetagenomBio Inc. This is the "raw" data that was used for analysis of the effect of glyphosate on the bacterial component of freshwater biofilms. <br>This dataset is a part of Lauren Koiter’s M.Sc. Thesis through the University of Waterloo Department of Biology. The thesis is researching the effects of glyphosate on the bacteria and archaea community composition of freshwater biofilms in North America. Full information on the materials and methods used in data collection is available in the thesis through the University of Waterloo. <br>
DOI: 10.6084/m9.figshare.17035481.v3
title: Appendix F - Filtered ASV Results and Summary Table

description: This dataset is the filtered ASV reads provided by MetagenomBio Inc. This is the "raw" data that was used for analysis of the effect of glyphosate on the bacterial component of freshwater biofilms. <br>This dataset is a part of Lauren Koiter’s M.Sc. Thesis through the University of Waterloo Department of Biology. The thesis is researching the effects of glyphosate on the bacteria and archaea community composition of freshwater biofilms in North America. Full information on the materials and methods used in data collection is available in the thesis through the University of Waterloo. <br>
DOI: 10.6084/m9.figshare.17035481.v2
title: Appendix F - Filtered ASV Results and Summary Table, Table 3 Supplementary Table

description: This dataset is the filtered ASV reads provided by MetagenomBio Inc. This is the "raw" data that was used for analysis of the effect of glyphosate on the bacterial component of freshwater biofilms. <br>This dataset is a part of Lauren Koiter’s M.Sc. Thesis through the University of Waterloo Department of Biology. The thesis is researching the effects of glyphosate on the bacteria and archaea community composition of freshwater biofilms in North America. Full information on the materials and methods used in data collection is available in the thesis through the University of Waterloo. <br>
DOI: 10.6084/m9.figshare.17012252
title: Appendix G - Diversity Analyses (Richness and Shannon Weiner Index)

description: This dataset includes the calculations for the richness and Shannon Weiner Diversity Index results used in the thesis. <br>This dataset is a part of Lauren Koiter’s M.Sc. Thesis through the University of Waterloo Department of Biology. The thesis is researching the effects of glyphosate on the bacteria and archaea community composition of freshwater biofilms in North America. Full information on the materials and methods used in data collection is available in the thesis through the University of Waterloo. <br>
DOI: 10.6084/m9.figshare.17012252.v1
title: Appendix G - Diversity Analyses (Richness and Shannon Weiner Index)

description: This dataset includes the calculations for the richness and Shannon Weiner Diversity Index results used in the thesis. <br>This dataset is a part of Lauren Koiter’s M.Sc. Thesis through the University of Waterloo Department of Biology. The thesis is researching the effects of glyphosate on the bacteria and archaea community composition of freshwater biofilms in North America. Full information on the materials and methods used in data collection is available in the thesis through the University of Waterloo. <br>
DOI: 10.5281/zenodo.6339580
title: FiNER-139

description: FiNER-139 is published with the article: FiNER: Financial Numeric Entity Recognition for XBRL Tagging In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022.
DOI: 10.5281/zenodo.6339579
title: FiNER-139

description: FiNER-139 is published with the article: FiNER: Financial Numeric Entity Recognition for XBRL Tagging In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022.
DOI: 10.21227/wmmx-2073
title: SARP

description: The dataset consists of images
DOI: 10.5066/p9hb0rfe
title: Database for the Surficial Geologic Map of the Charleston Region, Berkeley, Charleston, Colleton, Dorchester, and Georgetown Counties, South Carolina

description: This database portrays the surface and shallow subsurface geology of the greater Charleston, S.C. region east of 80 degrees 30' west and south of 33 degrees 15' north. The region covers the entirety of Charleston County and portions of Berkeley, Colleton, Dorchester, and Georgetown Counties. Units locally exposed at the surface range in age from middle Eocene to Holocene, but most of the area is covered by Quaternary interglacial deposits. These are, from oldest to youngest, the Okefenokee, Waccamaw, Penholoway, Ladson, Ten Mile Hill, and Wando Formations and the Silver Bluff beds. Two cross sections (not included in the database), one running southeast from Harleyville to the coastline on James Island and the other running along the coastal barrier islands from the town of Edisto Beach to the northeast end of Bull Island at the southwest edge of Bull Bay, portray the complex geometry of the Paleogene and Neogene marine units that directly lie beneath the Quaternary units. These older units include the Santee Limestone, Tupelo Bay, Parkers Ferry, Ashley, Chandler Bridge, Edisto, Parachucla, and Marks Head Formations, the Goose Creek Limestone, and the Raysor Formation. The estimated locations of deeply buried active basement faults are shown which are responsible for ongoing modern seismicity in the Charleston, S.C. area.
DOI: 10.5517/ccdc.csd.cc229v9k
title: CCDC 1916088: Experimental Crystal Structure Determination

description: Related Article: Charlotte Lorton,  Thomas Castanheiro,  Arnaud Voituriez|2019|J.Am.Chem.Soc.|141|10142|doi:10.1021/jacs.9b02539
DOI: 10.5517/ccdc.csd.cc294tmx
title: CCDC 2119799: Experimental Crystal Structure Determination

description: Related Article: Fangjun Ye|2021|CSD Communication|||
description: Related Article: Fangjun Ye, Chengzhen Shen, Jianxin Guan, Yiming Liu, Xiaoge Wang, Jingtian Wang, Ming Cong, Weibin Wang, Ting Zhang, Bo Zou, Junrong Zheng, Yuguo Ma|2022|J.Mater.Chem.C|10|3560|doi:10.1039/D1TC05810J
DOI: 10.25345/c56688n5q
title: MassIVE MSV000089022 - Mouse_brown_white_beige_primary_adipocytes_PROTEOME
title: Identification of Proteins and smORF-encoded microproteins in the proteomes of Brown Adipocytes and subcutaneous white adipocytes differentiated to both a white and beige phenotype.
DOI: 10.5066/p98283oi
title: Gage Height data from February through September for years 2016-19 at Gunnison River near Grand Junction, Colorado

description: Gage height values from U.S. Geological Survey (USGS) streamflow-gaging station 09152500 for the specified period are presented in comma separated value (CSV) format. Values encompass the monthly date range from February 1st to September 30th for each year, 2016 through 2019.
DOI: 10.5281/zenodo.6339605
title: FiNER-139: A Financial Numeric Entity Recognition Dataset

description: FiNER-139 is published with the article: FiNER: Financial Numeric Entity Recognition for XBRL Tagging In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022. We release FiNER-139, a dataset of 1.1M sentences with gold XBRL tags. Unlike typical entity extraction datasets, FiNER-139 uses a much larger label set of 139 entity types. Most annotated tokens are numeric, with the correct tag per token depending mostly on context, rather than the token itself.
DOI: 10.5281/zenodo.6339604
title: FiNER-139: A Financial Numeric Entity Recognition Dataset

description: FiNER-139 is published with the article: FiNER: Financial Numeric Entity Recognition for XBRL Tagging In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022. We release FiNER-139, a dataset of 1.1M sentences with gold XBRL tags. Unlike typical entity extraction datasets, FiNER-139 uses a much larger label set of 139 entity types. Most annotated tokens are numeric, with the correct tag per token depending mostly on context, rather than the token itself.
DOI: 10.5281/zenodo.6337923
title: A Deep Neural Network Based SMAP Soil Moisture Product

description: The soil moisture datasets here are based on a deep neural network (DNN) that utilizes the merits of a suite of existing satellite and reanalysis products to produce a new SM product with minimum (maximum) bias (correlation) -- using NASA’s Soil Moisture Active Passive (SMAP) data and ERA5 reanalysis. The benchmark of the network is a bias-adjusted SM with maximum correlation with in situ data over each land-cover type. The bias is adjusted to the product that exhibits a minimum bias over each land-cover type. Consistent with the laws of L-band microwave propagation in soil and canopy, the input variables include polarized SMAP brightness temperatures, incidence angles, vegetation scattering albedo, surface roughness parameter, surface water fraction, effective soil temperatures, bulk density, clay fraction, and vegetation optical depth from the normalized difference vegetation index (NDVI) climatology. The DNN is trained and validated using two years (04/2015--03/2017) of global data and deployed for assessment of its performance from 04/2017 to 03/2021. The testing results against in situ measurements demonstrate that the DNN outputs typically exhibit improved error quality metrics over most land cover types and climate regimes and can properly capture SM temporal dynamics, beyond each SMAP product across regional to continental scales.
description: {"references": ["Gao Lun (2022). A Deep Neural Network Based SMAP Soil Moisture Product (under review of RSE)"]}
DOI: 10.5281/zenodo.6337863
title: A Deep Neural Network Based SMAP Soil Moisture Product

description: The soil moisture datasets here are based on a deep neural network (DNN) that utilizes the merits of a suite of existing satellite and reanalysis products to produce a new SM product with minimum (maximum) bias (correlation) -- using NASA’s Soil Moisture Active Passive (SMAP) data and ERA5 reanalysis. The benchmark of the network is a bias-adjusted SM with maximum correlation with in situ data over each land-cover type. The bias is adjusted to the product that exhibits a minimum bias over each land-cover type. Consistent with the laws of L-band microwave propagation in soil and canopy, the input variables include polarized SMAP brightness temperatures, incidence angles, vegetation scattering albedo, surface roughness parameter, surface water fraction, effective soil temperatures, bulk density, clay fraction, and vegetation optical depth from the normalized difference vegetation index (NDVI) climatology. The DNN is trained and validated using two years (04/2015--03/2017) of global data and deployed for assessment of its performance from 04/2017 to 03/2021. The testing results against in situ measurements demonstrate that the DNN outputs typically exhibit improved error quality metrics over most land cover types and climate regimes and can properly capture SM temporal dynamics, beyond each SMAP product across regional to continental scales.
description: {"references": ["Gao Lun (2022). A Deep Neural Network Based SMAP Soil Moisture Product (under review of RSE)"]}
DOI: 10.25345/c52f7jv1k
title: MassIVE MSV000089023 - Mouse_brown_white_beige_primary_adipocytes_SECRETOME
title: Identification of Proteins and smORF-encoded microproteins in the secretomes of Brown Adipocytes and subcutaneous white adipocytes differentiated to both a white and beige phenotype.