cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh2081500.08fu
title: SH2081500.08FU

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/sh2653959.08fu
title: SH2653959.08FU

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/sh2653960.08fu
title: SH2653960.08FU

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/sh2081501.08fu
title: SH2081501.08FU

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/sh2081502.08fu
title: SH2081502.08FU

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/sh2653961.08fu
title: SH2653961.08FU

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: 10.5281/zenodo.6645357
title: Citizen Science Initiatives in Bulgaria

description: This dataset contains original mapping data developed in the process of the Bulgarian Citizen Science landscape review. In total, 20 Bulgarian Citizen Science projects were analysed according to a common framework. During the mapping process, we weren’t always able to find information on things that interested us e.g. project impact, stakeholder engagement, the size of the volunteering force. But just because we couldn’t find something does not mean the results or activities did not happen. It goes without saying that absence of evidence is not evidence of absence. Failure to find some information on our part can be explained by the fact that we worked primarily with internet sources, so we had to make do with whatever publicly available information we could find within reasonable time.
DOI: 10.5281/zenodo.6645356
title: Citizen Science Initiatives in Bulgaria

description: This dataset contains original mapping data developed in the process of the Bulgarian Citizen Science landscape review. In total, 20 Bulgarian Citizen Science projects were analysed according to a common framework. During the mapping process, we weren’t always able to find information on things that interested us e.g. project impact, stakeholder engagement, the size of the volunteering force. But just because we couldn’t find something does not mean the results or activities did not happen. It goes without saying that absence of evidence is not evidence of absence. Failure to find some information on our part can be explained by the fact that we worked primarily with internet sources, so we had to make do with whatever publicly available information we could find within reasonable time.
DOI: 10.5281/zenodo.6645417
title: Experimental data of manuscript "A new DL sea ice detection model OceanTDLx for SAR image"

description: Experimental data of manuscript.
DOI: 10.5281/zenodo.6645416
title: Experimental data of manuscript "A new DL sea ice detection model OceanTDLx for SAR image"

description: Experimental data of manuscript.
DOI: 10.5281/zenodo.6645414
title: Data from: Using functional traits to identify conservation priorities for the world's crocodylians

description: Over half of all crocodylians are threatened with extinction, with many species considered to be functionally extinct throughout their historical ranges. How such losses impact crocodylian functional diversity (FD) and its conservation is poorly understood, but can be investigated using measurable traits. Where such information is unavailable, phylogenetic diversity (PD) has been proposed as an effective strategy to capture FD, but this assumption is not well tested. We constructed a global trait database for 28 extant crocodylians [uploaded here], and quantified their functional diversity, distinctiveness and groupings. Functionally distinctive crocodylians include the most and least evolutionarily distinct species, likely because unusual trait values and combinations can be produced by both evolutionary isolation and evolutionarily recent adaptive radiation. We identified four functional groups of crocodylians, within which species have similar ecological roles. Highly distinctive species, such as the gharial, fit less well into functional groups. We combined functional distinctiveness and threat ranking scores to prioritise species for conservation. The metric is termed EcoDGE (Ecologically Distinct and Globally Endangered), and we tested how well it operates to preserve crocodylian FD amongst extant Crocodylia. Under current extinction scenarios, 32-38% of crocodylian FD might be lost within 100 years. Losses increase to 48% if all threatened species go extinct, with Asia identified as a hotspot of threatened FD in crocodylians. Highly-threatened distinctive species lead this extinction scenario, exacerbated by clusters of species sharing traits linked to high extinction risk. These traits include habitat specialism and lower reproductive investment; in contrast, species that tolerate climate extremes are more resilient. Prioritising at-risk species based on functional distinctiveness and threat status appears to be an effective way to conserve present-day crocodylian diversity. Conservation prioritisation based on the EcoDGE metric performed well to minimize projected losses in FD. Among extant crocodylians, FD losses are projected when high diversity overlaps with high extrinsic threats. We then examined the utility of PD-based measures as surrogates for FD conservation, to better understand the advantages and drawbacks of such substitutions. A PD-based measure such as the EDGE metric, provided an effective tool to capture functional diversity in our tests.
description: This is the functional trait database to accompany 'Using functional traits to identify conservation priorities for the world's crocodylians'.
DOI: 10.5281/zenodo.6643915
title: Dataset_2 for "An integrated imaging sensor for aberration-corrected 3D photography"

description: ...
DOI: 10.5281/zenodo.6643914
title: Dataset_2 for "An integrated imaging sensor for aberration-corrected 3D photography"

description: ...
DOI: 10.5281/zenodo.6641847
title: Dataset_1 for "An integrated imaging sensor for aberration-corrected 3D photography"

description: ...
DOI: 10.5281/zenodo.6641846
title: Dataset_1 for "An integrated imaging sensor for aberration-corrected 3D photography"

description: ...
DOI: 10.5281/zenodo.6644095
title: Dataset_3 for "An integrated imaging sensor for aberration-corrected 3D photography"

description: ...
DOI: 10.5281/zenodo.6644094
title: Dataset_3 for "An integrated imaging sensor for aberration-corrected 3D photography"

description: ...
DOI: 10.21227/5tq1-xj36
title: KUMono Bangla Corpus

description: A very large Bangla monolingual corpus consisting of more than 350 million tokens
DOI: 10.6084/m9.figshare.19745104
title: 1111111111111

description: 111111111
DOI: 10.6084/m9.figshare.19745104.v2
title: 1111111111111

description: 111111111
DOI: 10.6084/m9.figshare.19745104.v1
title: CPR N95

description: CPR with N95 mask
DOI: 10.5517/ccdc.csd.cc22jp6j
title: CCDC 1922657: Experimental Crystal Structure Determination

description: Related Article: Troy Luster, Hannah J. Van de Roovaart, Kyle J. Korman, Georgia G. Sands, Kylie M. Dunn, Anthony Spyker, Richard J. Staples, Shannon M. Biros, John E. Bender|2022|Dalton Trans.|51|9103|doi:10.1039/D2DT01570F
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.cc2bf9nr
title: CCDC 2157744: Experimental Crystal Structure Determination

description: Related Article: Ofelia Hernández-Negrete, Rogerio R. Sotelo-Mundo, Hilda E. Esparza-Ponce, Martín A.Encinas-Romero, Javier Hernández-Paredes|2022|J.Solid State Chem.|313|123282|doi:10.1016/j.jssc.2022.123282
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.cc2brdcw
title: CCDC 2167438: Experimental Crystal Structure Determination

description: Related Article: Yang Lin, Ao Yu, Jinjing Wang, Derui Kong, Hongtao Liu, Jianwei Li, Chunman Jia|2022|RSC Advances|12|16772|doi:10.1039/D2RA02595G
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: 10.6084/m9.figshare.20072309
title: CPR

description: cpr的原始数据
DOI: 10.6084/m9.figshare.20072309.v1
title: CPR

description: cpr的原始数据
DOI: 10.6084/m9.figshare.20072252.v1
title: Calb20_2021-01-22_13-08-20

description: Electrophysiology recording
DOI: 10.24376/rd.sgul.20067605
title: COPD_&_CAD_data

description: The dataset comprises demographics and a range of biomedical variables from a cohort of 100 patients (53 patients with a primary diagnosis of Chronic Obstructive Pulmonary Disease (COPD), 24 with a primary diagnosis of coronary artery disease (CAD) and 23 with both COPD and CAD. Patients were recruited from respiratory and cardiology departments at St George's Hospital NHS Foundation Trust between December 2015 and October 2017. Variables include a range of markers of respiratory function, systemic inflammation, cognitive function and structural white matter damage (from brain magnetic resonance imaging). Ethical approval was granted by the national research ethics committee London - Dulwich (16/LO/0547) and East Midlands - Leicester South Research Ethics Committee (15/EM/0425). All patients provided informed written consent.<br> Raw data is provided on Sheet 1 of the Excel file. A number of variables had a non-Guassian distribution. These variables were transformed using log10 or square root transformations.
DOI: 10.6084/m9.figshare.17182985.v3
title: A bankfull geometry dataset for major exorheic rivers on the Qinghai-Tibet Plateau

description: Based on the Sentinel-2 and Landsat 5/7/8 multispectral instrument imageries combined with in-situ measured hydrological data, bankfull river geometry of six major exorheic river basins of the Qinghai-Tibet Plateau (the upper Yellow River, upper Jinsha River, Yalong River, Lantsang River, Nu River and Yalung Zangbo River) are presented. River surface of six mainstreams and major tributaries are included. For each river basin, two types of rivers are included: connected and disconnected rivers. Format of the dataset is .shp exported from the ArcGIS 10.5.
DOI: 10.6084/m9.figshare.12130980.v145
title: MOOD Maps of Google community mobility change during the COVID-19 outbreak

description: The MOOD project (MOnitoring Outbreak events for Disease surveillance in a data science context. H2020) has geo-referenced the data Google has published as a series of PDF files presenting reports on national and subnational human mobility levels relative to a baseline data of late January 2020. The details and the PDF files can be found at https://www.google.com/covid19/mobility/.<br>More detail on these files can be found at https://www.moodspatialdata.com/humanmobilityforcovid19 <br>The first set of data were released on April 2 2020 and have been revised weekly since then. The maps now utilise the CSV data released by Google. Please note that the maps figures use a mean of the previous three days, while the Google PDFs use a single days data so there will be differences between values in our maps when compare to the Google PDFs.<br>The authors have extracted the majority of these data into a series of excel spreadsheets. Each worksheet provides the data for % change in numbers of records at various types of location categories illustrated by: retail and recreation, grocery and pharmacy, parks and beaches, transit stations, workplaces and residential (columns f to K). A second set of columns calculates the difference of each value from the mean values for each category (columns L to P) Columns A to E contain geographical details. Column Q contains the names used to link to a mapping file.There are separate worksheets for the date of the data from each dated release (e.g. 2903, 0504 etc.) and separate worksheets calculating the changes between specific dates.<br>A second spreadsheet has been added calculating the 3 day moving mean of each day from the 15th of February. Each day is referenced by the Gregorian calendar day count. So day 48 = Feb 17th.<br>The maps (for EU & Global) display these data. We provide 600 dpi jpegs of the Global (“WD”) and European (“EU”) mapped values at the latest date available, for each of the mobility categories: retail and recreation (“retrec”) , grocery and pharmacy (“grocphar”) , parks (“parks”) , transit stations (“transit”), residential (“resid”) and workplaces (“work”). We also provide maps of the changes from the previous week (“ch”).<br>All data extracting and subsequent processing have been carried out by ERGO (Environmental Research Group Oxford, c/o Dept Zoology, University of Oxford) on behalf of the MOOD H2020 project. Data will be periodically updated. Additional maps can be obtained on request to the authors.
DOI: 10.18112/openneuro.ds004158.v1.0.0
title: rest_eye
DOI: 10.18112/openneuro.ds004158.v1.0.1
title: rest_eye
DOI: 10.6084/m9.figshare.11973693.v15
title: Solar wind in situ data for creating catalogs and statistics of interplanetary coronal mass ejections and high speed streams (Solar Orbiter, Parker Solar Probe, STEREO-A/B, MAVEN, Wind, MESSENGER, VEX, Ulysses) 1995-2021

description: These are solar wind in situ data arrays in python pickle format suitable for creating catalogs, plots and movies of interplanetary coronal mass ejections.<br><br>See AAREADME_insitu.txt for more explanation.<br>If you use these data for peer reviewed scientific publications, please get in touch by christian.moestl@oeaw.ac.at or twitter @chrisoutofspace concerning usage and possible co-authorship.<br>Made with https://github.com/cmoestl/heliocats
DOI: 10.15156/bio/sh0924500.10fu
title: SH0924500.10FU

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/sh0924501.10fu
title: SH0924501.10FU

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/sh0924502.10fu
title: SH0924502.10FU

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.