cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1774946.08fu
title: SH1774946.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh408544.07fu
title: SH408544.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh408545.07fu
title: SH408545.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1774947.08fu
title: SH1774947.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1774948.08fu
title: SH1774948.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1774949.08fu
title: SH1774949.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh408546.07fu
title: SH408546.07FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.6084/m9.figshare.13378943.v1
title: Supporting Information Data 4_Prunus-specific pathogens

description: Data for <i>Prunus</i>-specific pathogens.
DOI: 10.34740/kaggle/dsv/1807419
title: reddit_AVexchange_price_2020
DOI: 10.6084/m9.figshare.13378943
title: Supporting Information Data 4_Prunus-specific pathogens

description: Data for <i>Prunus</i>-specific pathogens.
DOI: 10.5281/zenodo.4412026
title: 3D CMT catalogue of moderate size offshore earthquakes along the Nankai Trough

description: 3D CMT inversion solutions of moderate-size earthquakes along the Nankai Trough, <strong>version 3.1. </strong> Analyzed periods: <strong>January 2003 to December 2020</strong> The catalog version 3, containing CMT solutions from January 2003 to April 2020. The catalog version 2.2, which is containing CMT solutions from April 2004 to August 2019, has been published in GJI (Takemura, Okuwaki et al. 2020 doi:10.1093/gji/ggaa238). The method is described in Takemura, Okuwaki, et al., 2020, GJI, doi:10.1093/gji/ggaa238 the submitted preprint. If you use this version, you should cite the appropriate DOI and Takemura, Okuwaki, et al. 2020 GJI. <strong>Included files</strong> YYYYMMDDHHMM_25-100s__CMT.dat<br> CMT solutions at all selected source grids for an earthquake that occurred at HH:MM on DDth MM YYYY (JST). Latitude, longitude, depth, VR [%], M<sub>rr</sub>, M<sub>tt</sub>, M<sub>ff</sub>, M<sub>rt</sub>, M<sub>rf</sub>, M<sub>tf</sub>, exponent (dyne-cm), Mo [Nm], strike1, dip1, rake1, strike2, dip2, rake2, Mw, index of source grid (internal parameter), and centroid time are listed. YYYYMMDDHHMM_25-100s__CMTparam.dat<br> Input directory (internal parameter), Green's function directory (internal parameter), the number of source grids, the number of used stations, station names used in CMT inversion, frequency range, initial epicenter and distance range are listed. 3DCMTcatalog_v3.csv<br> CSV format file of the 3D CMT catalog for earthquakes with Mw of 4.3-6.5 catalog3DCMT_Takemura2019_Mw7.2_7.5SEKii.csv<br> CSV format file of the 3D CMT catalog for the Mw 7.2 and 7.5 southeast off the Kii Peninsula earthquake occurred on 19:07 and 23:57 5th September 2004 (JST), respectively.
DOI: 10.5281/zenodo.3523582
title: 3D CMT catalogue of moderate size offshore earthquakes along the Nankai Trough

description: 3D CMT inversion solutions of moderate-size earthquakes along the Nankai Trough, <strong>version 3.1. </strong> Analyzed periods: <strong>January 2003 to December 2020</strong> The catalog version 3, containing CMT solutions from January 2003 to April 2020. The catalog version 2.2, which is containing CMT solutions from April 2004 to August 2019, has been published in GJI (Takemura, Okuwaki et al. 2020 doi:10.1093/gji/ggaa238). The method is described in Takemura, Okuwaki, et al., 2020, GJI, doi:10.1093/gji/ggaa238 the submitted preprint. If you use this version, you should cite the appropriate DOI and Takemura, Okuwaki, et al. 2020 GJI. <strong>Included files</strong> YYYYMMDDHHMM_25-100s__CMT.dat<br> CMT solutions at all selected source grids for an earthquake that occurred at HH:MM on DDth MM YYYY (JST). Latitude, longitude, depth, VR [%], M<sub>rr</sub>, M<sub>tt</sub>, M<sub>ff</sub>, M<sub>rt</sub>, M<sub>rf</sub>, M<sub>tf</sub>, exponent (dyne-cm), Mo [Nm], strike1, dip1, rake1, strike2, dip2, rake2, Mw, index of source grid (internal parameter), and centroid time are listed. YYYYMMDDHHMM_25-100s__CMTparam.dat<br> Input directory (internal parameter), Green's function directory (internal parameter), the number of source grids, the number of used stations, station names used in CMT inversion, frequency range, initial epicenter and distance range are listed. 3DCMTcatalog_v3.csv<br> CSV format file of the 3D CMT catalog for earthquakes with Mw of 4.3-6.5 catalog3DCMT_Takemura2019_Mw7.2_7.5SEKii.csv<br> CSV format file of the 3D CMT catalog for the Mw 7.2 and 7.5 southeast off the Kii Peninsula earthquake occurred on 19:07 and 23:57 5th September 2004 (JST), respectively.
DOI: 10.6073/pasta/7d26ea91634aa494c79822d3ffef2304
title: SBC LTER: Ocean: Time-series: nearshore dissolved oxygen and temperature outside of reefs, ongoing since 2011

description: Dissolved oxygen (miniDOT sensors) data was collected from 6 reefs in the Santa Barbara Channel along with in situ temperature. Most dissolved oxygen sensors are deployed together with SBC long-term mooring instruments. Data collection intervals and miniDOT sensor depths vary based on the site location.
DOI: 10.34740/kaggle/dsv/1807599
title: reddit_AVexchange_price_2020
DOI: 10.6084/m9.figshare.13514521
title: Raw data of SNP dataset for genome-wide analysis of Eucalyptus cladocalyx

description: 480 selected trees of 49 half-sib families (~10 individuals per family) were genotyped on the Illumina Infinium 60 K SNP array (Illumina, CA, USA).<br>
DOI: 10.6084/m9.figshare.13514521.v1
title: Raw data of SNP dataset for genome-wide analysis of Eucalyptus cladocalyx

description: 480 selected trees of 49 half-sib families (~10 individuals per family) were genotyped on the Illumina Infinium 60 K SNP array (Illumina, CA, USA).<br>
DOI: 10.5281/zenodo.4412033
title: Nanomechanical topological insulators with an auxiliary orbital degree of freedom - source data

description: This data set contains the source data and the matlab scripts applied to obtain the results published in "Nanomechanical topological insulators with an auxiliary orbital degree of freedom". For details of the experimental procedure please refer to the main text of the article, as well as the supplementary information.
DOI: 10.6084/m9.figshare.13514527
title: The dependence of Chinese green and conventional bond markets under extreme and normal market conditions

description: The database of The dependence of Chinese green and conventional bond markets under extreme and normal market conditions
DOI: 10.6084/m9.figshare.13514527.v1
title: The dependence of Chinese green and conventional bond markets under extreme and normal market conditions

description: The database of The dependence of Chinese green and conventional bond markets under extreme and normal market conditions
DOI: 10.6084/m9.figshare.13514554
title: Additional file 2 of Prevalence of and reasons for women’s, family members’, and health professionals’ preferences for cesarean section in Iran: a mixed-methods systematic review

description: Additional file 2: Data extraction form.
DOI: 10.6084/m9.figshare.13514557.v1
title: Additional file 3 of Prevalence of and reasons for women’s, family members’, and health professionals’ preferences for cesarean section in Iran: a mixed-methods systematic review

description: Additional file 3: Completed data extraction (quantitative papers).
DOI: 10.6084/m9.figshare.13514557
title: Additional file 3 of Prevalence of and reasons for women’s, family members’, and health professionals’ preferences for cesarean section in Iran: a mixed-methods systematic review

description: Additional file 3: Completed data extraction (quantitative papers).
DOI: 10.6084/m9.figshare.13514616.v1
title: Additional file 1 of GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

description: Additional file 1: Table S1. Pedigree information for F 3:6 Nebraska Duplicate Nursery winter wheat. Table S2. List of SNPs generated from GBS data. Table S3. The genotypes performance for GY under nine environments. Table S4. Average high and low monthly temperatures, total monthly precipitation, and total snowfall in all environments except Grant and Kansas for growing season (2016 /2017). Table S5. Details of GWAS analysis for grain yield using mixed linear model (MLM) at the significance level of 5% bonferroni correction using 11,991 SNPs. Table S6. gene annotation and candidate genes for the high LD genomic regions. Table S7. The presence (1) and absence (0) of all alleles associated with high yielding detected by GWAS in 13 selected genotypes in all environments. Table S8. The distance matrix based on genotypic data between the best high yielding genotypes. Table S9. The different allele effects matrix among the 13 selected genotypes.
DOI: 10.6084/m9.figshare.13514616
title: Additional file 1 of GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

description: Additional file 1: Table S1. Pedigree information for F 3:6 Nebraska Duplicate Nursery winter wheat. Table S2. List of SNPs generated from GBS data. Table S3. The genotypes performance for GY under nine environments. Table S4. Average high and low monthly temperatures, total monthly precipitation, and total snowfall in all environments except Grant and Kansas for growing season (2016 /2017). Table S5. Details of GWAS analysis for grain yield using mixed linear model (MLM) at the significance level of 5% bonferroni correction using 11,991 SNPs. Table S6. gene annotation and candidate genes for the high LD genomic regions. Table S7. The presence (1) and absence (0) of all alleles associated with high yielding detected by GWAS in 13 selected genotypes in all environments. Table S8. The distance matrix based on genotypic data between the best high yielding genotypes. Table S9. The different allele effects matrix among the 13 selected genotypes.
DOI: 10.5281/zenodo.4412039
title: Nanomechanical topological insulators with an auxiliary orbital degree of freedom - source data

description: This data set contains the source data and the matlab scripts applied to obtain the results published in "Nanomechanical topological insulators with an auxiliary orbital degree of freedom". For details of the experimental procedure please refer to the main text of the article, as well as the supplementary information.
DOI: 10.5281/zenodo.4405044
title: Nanomechanical topological insulators with an auxiliary orbital degree of freedom - source data

description: This data set contains the source data and the matlab scripts applied to obtain the results published in "Nanomechanical topological insulators with an auxiliary orbital degree of freedom". For details of the experimental procedure please refer to the main text of the article, as well as the supplementary information.
DOI: 10.6084/m9.figshare.12378608.v2
title: The Dog That Barks Appendices_v20200527.docx

description: Appendix I: Data CollectionAppendix II: Borderline Media CampaignsAppendix III: Intercoder Reliability<br>
DOI: 10.6084/m9.figshare.12378608
title: The Dog That Barks Appendices_v20201130

description: Appendix I: Data CollectionAppendix II: Measurement of DV – The Adoption/Non-Adoption of Media CampaignsAppendix III: Measurement of IVs (State Foreign Policy Intent and Existing Public Opinion) and Intercoder Reliability<br>Appendix IV: Case DescriptionsAppendix V: Cases with Shifted State Policy Intent – A Further Examination of Reversed CausalityAppendix VI: A Non-Exhaustive List of Occasions that Provoked China’s Public Relations Responses and the Provoked ResponsesAppendix VII: A Non-Exhaustive List of People’s Daily Articles That Quoted Foreign-Bashing Rhetoric from Non-Chinese Experts
DOI: 10.6084/m9.figshare.12378608.v4
title: The Dog That Barks Appendices_v20201130

description: Appendix I: Data CollectionAppendix II: Measurement of DV – The Adoption/Non-Adoption of Media CampaignsAppendix III: Measurement of IVs (State Foreign Policy Intent and Existing Public Opinion) and Intercoder Reliability<br>Appendix IV: Case DescriptionsAppendix V: Cases with Shifted State Policy Intent – A Further Examination of Reversed CausalityAppendix VI: A Non-Exhaustive List of Occasions that Provoked China’s Public Relations Responses and the Provoked ResponsesAppendix VII: A Non-Exhaustive List of People’s Daily Articles That Quoted Foreign-Bashing Rhetoric from Non-Chinese Experts
DOI: 10.6084/m9.figshare.12378608.v3
title: The Dog That Barks Appendices_v20201130

description: Appendix I: Data CollectionAppendix II: Measurement of DV – The Adoption/Non-Adoption of Media CampaignsAppendix III: Measurement of IVs (State Foreign Policy Intent and Existing Public Opinion) and Intercoder Reliability<br>Appendix IV: Case DescriptionsAppendix V: Cases with Shifted State Policy Intent – A Further Examination of Reversed CausalityAppendix VI: A Non-Exhaustive List of Occasions that Provoked China’s Public Relations Responses and the Provoked ResponsesAppendix VII: A Non-Exhaustive List of People’s Daily Articles That Quoted Foreign-Bashing Rhetoric from Non-Chinese Experts
DOI: 10.6084/m9.figshare.13514554.v1
title: Additional file 2 of Prevalence of and reasons for women’s, family members’, and health professionals’ preferences for cesarean section in Iran: a mixed-methods systematic review

description: Additional file 2: Data extraction form.
DOI: 10.6084/m9.figshare.13514728.v1
title: ETROT for public sharing.xls

description: Deidentified dataset of PLHIV in western Kenya, screened for TB
DOI: 10.6084/m9.figshare.13514728
title: ETROT for public sharing.xls

description: Deidentified dataset of PLHIV in western Kenya, screened for TB
DOI: 10.21227/zcja-1973
title: Coronavirus (COVID-19) Geo-tagged Tweets Dataset

description: This dataset contains IDs and sentiment scores of the geo-tagged tweets related to the COVID-19 pandemic. The tweets are captured by an on-going project deployed at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. Complying with Twitter's content redistribution policy, only the tweet IDs are shared. You can re-construct the dataset by hydrating these IDs. The tweet IDs in this dataset belong to the tweets tweeted providing an exact location.The paper associated with this dataset is available here: Design and analysis of a large-scale COVID-19 tweets dataset-------------------------------------Related datasets: (a) Coronavirus (COVID-19) Tweets Sentiment Trend (Global)(b) Tweets Originating from India During COVID-19 Lockdowns-------------------------------------Below is the quick overview of this dataset.— Dataset name: GeoCOV19Tweets Dataset— Number of tweets : 291,668 tweets— Coverage : Global— Language : English (EN)— Dataset usage terms : By using this dataset, you agree to (i) use the content of this dataset and the data generated from the content of this dataset for non-commercial research only, (ii) remain in compliance with Twitter's Developer Policy and (iii) cite the following paper:Lamsal, R. Design and analysis of a large-scale COVID-19 tweets dataset. Applied Intelligence (2020). https://doi.org/10.1007/s10489-020-02029-z— Primary dataset : Coronavirus (COVID-19) Tweets Dataset (COV19Tweets Dataset)— Dataset updates : Everyday— Active keywords and hashtags: keywords.tsvPlease visit this page (primary dataset) for details regarding the collection date and time (and other notes) of each CSV file present in this dataset.
DOI: 10.5281/zenodo.4396302
title: Wikidata Dump geocoordinates

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4396301
title: Wikidata Dump geocoordinates

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4396304
title: Wikidata Dump geocoordinates

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4396303
title: Wikidata Dump geocoordinates

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4397063
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 38
DOI: 10.5281/zenodo.4397062
title: Wikidata Dump

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 38