cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.jmptde
title: Occurrence Download

description: A dataset containing 180731 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Lamium amplexicaule"
 ]
}

 The dataset includes 180731 records from 1322 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048285-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22002/m948q-jv525
title: Myxococcus xanthus delta-pilA

description: grid box YWC059
description: <strong>Tilt Series Date:</strong> 2013-12-28</p>
<strong>Data Taken By:</strong> Yi-Wei Chang</p>
<strong>Species / Specimen:</strong> Myxococcus xanthus</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-65.0°, 65.0°), step: 1.0°, constant angular increment, dosage: 180.0 eV/Å²,  defocus: -8.0 μm,  magnification: 26000x. </p>
<strong>Microscope:</strong> Janelia Titan</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain form Lotte Sogaard-Andersen</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Cells grown 48 hr in shaking CTT medium at 30 degrees without antibiotics. OD600=0.7</p>
<strong>Sample Preparation:</strong> Vitrobot settings: 100% humidity, 3µl sample, 10 mg/ml BSA treated gold. -4 offset, 4 sec blot time, 1s drain. Ethane/propane mix. Grid: Quantifoil Cu 2/2 Finder. 20 nm gold beads.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2013-12-28-32/rawdata/</p>20131228_Janelia_YWC059_10048.mrc,  Tilt Series (Pixel Size 0.42 nm), 3.6 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2013-12-28-32/rawdata/20131228_Janelia_YWC059_10048.mrc"
        > <i class="download icon"></i> Download </a></p>

        20131228_Janelia_YWC059_10048_full.rec,  Reconstruction (Pixel Size 1.68 nm), 688.9 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2013-12-28-32/3dimage_37217/20131228_Janelia_YWC059_10048_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.6084/m9.figshare.29986924
title: Subsampled ab1 Sanger sequencing reads prior to SSV clustering.

description: Subsampled ab1 Sanger sequencing reads prior to SSV clustering.
DOI: 10.6084/m9.figshare.29986924.v2
title: Subsampled ab1 Sanger sequencing reads prior to SSV clustering.

description: Subsampled ab1 Sanger sequencing reads prior to SSV clustering.
DOI: 10.6084/m9.figshare.29986924.v1
title: Subsampled ab1 Sanger sequencing reads Q30 &gt;300bp prior to SSV clustering.

description: Subsampled ab1 Sanger sequencing reads Q30 &gt;300bp prior to SSV clustering.
DOI: 10.22002/eeea4-kys51
title: Chromogranin A-GFP

description: CLEM of chromogranin A-GFP expressing INS-1E cells
description: <strong>Tilt Series Date:</strong> 2014-08-26</p>
<strong>Data Taken By:</strong> Stephen Carter</p>
<strong>Species / Specimen:</strong> INS-1E Pancreatic Cells expressing Chromogranin A GFP</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1°, constant angular increment, dosage: 90.0 eV/Å²,  defocus: -10.0 μm,  magnification: 18000x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> Undefined</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Zach Friedberg</p>
<strong>Purification / Growth Conditions / Treatment:</strong> INS-1E cells grown on gold finder grids and plunge frozen using the vitrobot III blotted both side pressure setting 1. Grids coated with fibronectin and 200 nm red fluorescent beads added to grids before freezing.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/scd2014-08-26-3/rawdata/</p>tomogram3-1.mrc,  Tilt Series (Pixel Size 1.2 nm), 861.6 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/scd2014-08-26-3/rawdata/tomogram3-1.mrc"
        > <i class="download icon"></i> Download </a></p>

        tomogram3-1_part121_5.rec,  Reconstruction (Pixel Size 4.8 nm), 223.7 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/scd2014-08-26-3/3dimage_45804/tomogram3-1_part121_5.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/e4skj-azz38
title: Myxococcus xanthus delta-tsaP

description: grid box YWC065
description: <strong>Tilt Series Date:</strong> 2014-01-24</p>
<strong>Data Taken By:</strong> Yi-Wei Chang</p>
<strong>Species / Specimen:</strong> Myxococcus xanthus</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-60.0°, 60.0°), step: 1.0°, constant angular increment, dosage: 200.0 eV/Å²,  defocus: -8.0 μm,  magnification: 22500x. </p>
<strong>Microscope:</strong> Caltech Polara</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain form Lotte Sogaard-Andersen</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Cells grown 48 hr in shaking CTT medium at 30 degrees without antibiotics. OD600=0.7</p>
<strong>Sample Preparation:</strong> Vitrobot settings: 100% humidity, 3µl sample, 10 mg/ml BSA treated gold. -4 offset, 4 sec blot time, 1s drain. Ethane/propane mix. Grid: Quantifoil Cu 2/2 Finder. 10 nm gold beads.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2014-01-24-16/rawdata/</p>20140124_YWC065_10013.mrc,  Tilt Series (Pixel Size 0.48 nm), 3.4 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2014-01-24-16/rawdata/20140124_YWC065_10013.mrc"
        > <i class="download icon"></i> Download </a></p>

        20140124_YWC065_10013_full.rec,  Reconstruction (Pixel Size 1.92 nm), 712.7 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2014-01-24-16/3dimage_38000/20140124_YWC065_10013_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.22002/73966-t8948
title: Myxococcus xanthus delta-pilQ

description: grid box YWC061
description: <strong>Tilt Series Date:</strong> 2013-12-30</p>
<strong>Data Taken By:</strong> Yi-Wei Chang</p>
<strong>Species / Specimen:</strong> Myxococcus xanthus</p>
<strong>Strain:</strong> </p>
<strong>Tilt Series Settings:</strong>  Single Axis, tilt range: (-65.0°, 65.0°), step: 1.0°, constant angular increment, dosage: 180.0 eV/Å²,  defocus: -8.0 μm,  magnification: 26000x. </p>
<strong>Microscope:</strong> Janelia Titan</p>
<strong>Acquisition Software:</strong> UCSFTomo</p>
<strong>Upload Method:</strong> pipeline</p>
<strong>Processing Software Used:</strong> Raptor</p>
<strong>Collaborators and Roles:</strong> Strain form Lotte Sogaard-Andersen</p>
<strong>Purification / Growth Conditions / Treatment:</strong> Cells grown 48 hr in shaking CTT medium at 30 degrees without antibiotics. OD600=0.7</p>
<strong>Sample Preparation:</strong> Vitrobot settings: 100% humidity, 3µl sample, 10 mg/ml BSA treated gold. -4 offset, 4 sec blot time, 1s drain. Ethane/propane mix. Grid: Quantifoil Cu 2/2 Finder. 20 nm gold beads.</p>
description: Files available via S3 at https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2013-12-30-52/rawdata/</p>20131230_Janelia_YWC061_10007.mrc,  Tilt Series (Pixel Size 0.42 nm), 3.6 GB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2013-12-30-52/rawdata/20131230_Janelia_YWC061_10007.mrc"
        > <i class="download icon"></i> Download </a></p>

        20131230_Janelia_YWC061_10007_full.rec,  Reconstruction (Pixel Size 1.68 nm), 688.9 MB  
        
<a role="button" class="ui compact mini button" href="https://sdsc.osn.xsede.org/ini210004tommorrell/tomography_archive/ycw2013-12-30-52/3dimage_37303/20131230_Janelia_YWC061_10007_full.rec"
        > <i class="download icon"></i> Download </a></p>
DOI: 10.15468/dl.4azuhx
title: Occurrence Download

description: A dataset containing 76266 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cornus sericea"
 ]
}

 The dataset includes 76266 records from 567 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048286-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14541426
title: Becoming an Economist: A Database of French Economics PhDs

description: This database compiles information on Ph.D. dissertations in economics defended in France since 1900. See our companion website for news and full documentation.

The French database is implemented as a relational database that integrates multiple interconnected data frames. It is organized around four main components:



Thesis Metadata: This table contains the core information for each dissertation. Each entry corresponds to a single thesis and includes details such as the title, defense date, abstract, and other relevant metadata.

Edges Data: This table captures the connections between the other three tables, linking individuals, institutions, and theses. It associates each thesis with the individuals and institutions involved in its production, thereby enabling a synthetized view of these relationships. The edges data are provided in two formats: (1) a ready-to-use format with cleaned and standardized information; and (2) a more   extensive format that allows for comparison between the original  collected data and the results of the cleaning process.

Institutions Data: This table includes information on universities, laboratories, doctoral schools, and other institutions associated with the dissertations. Each entry corresponds to a single institution.

Individual Data: This table contains information on the individuals involved in the dissertations, including authors, supervisors, and jury members. Each entry corresponds to a single individual.


The data used in this project comes from three mains sources: 



Theses.fr: https://theses.fr/

Sudoc:  https://www.sudoc.fr/

IdRef:  https://www.idref.fr/]


If you use our data or scripts, please cite the following reference: “Delcey Thomas, and Aurélien Goutsmedt. (2024). Becoming an Economist: A Database of French Economics PhDs. Zenodo. https://doi.org/10.5281/zenodo.14541427”
DOI: 10.5281/zenodo.14541427
title: Becoming an Economist: A Database of French Economics PhDs

description: This database compiles information on Ph.D. dissertations in economics defended in France since 1900. See our companion website for news and full documentation.

The French database is implemented as a relational database that integrates multiple interconnected data frames. It is organized around four main components:



Thesis Metadata: This table contains the core information for each dissertation. Each entry corresponds to a single thesis and includes details such as the title, defense date, abstract, and other relevant metadata.

Edges Data: This table captures the connections between the other three tables, linking individuals, institutions, and theses. It associates each thesis with the individuals and institutions involved in its production, thereby enabling a synthetized view of these relationships. The edges data are provided in two formats: (1) a ready-to-use format with cleaned and standardized information; and (2) a more   extensive format that allows for comparison between the original  collected data and the results of the cleaning process.

Institutions Data: This table includes information on universities, laboratories, doctoral schools, and other institutions associated with the dissertations. Each entry corresponds to a single institution.

Individual Data: This table contains information on the individuals involved in the dissertations, including authors, supervisors, and jury members. Each entry corresponds to a single individual.


The data used in this project comes from three mains sources: 



Theses.fr: https://theses.fr/

Sudoc:  https://www.sudoc.fr/

IdRef:  https://www.idref.fr/


If you use our data or scripts, please cite the following reference: “Delcey Thomas, and Aurélien Goutsmedt. (2024). Becoming an Economist: A Database of French Economics PhDs. Zenodo. https://doi.org/10.5281/zenodo.14541427”
DOI: 10.5281/zenodo.14713202
title: Becoming an Economist: A Database of French Economics PhDs

description: This database compiles information on Ph.D. dissertations in economics defended in France since 1900. See our companion website for news and full documentation.

The French database is implemented as a relational database that integrates multiple interconnected data frames. It is organized around four main components:



Thesis Metadata: This table contains the core information for each dissertation. Each entry corresponds to a single thesis and includes details such as the title, defense date, abstract, and other relevant metadata.

Edges Data: This table captures the connections between the other three tables, linking individuals, institutions, and theses. It associates each thesis with the individuals and institutions involved in its production, thereby enabling a synthetized view of these relationships. The edges data are provided in two formats: (1) a ready-to-use format with cleaned and standardized information; and (2) a more   extensive format that allows for comparison between the original  collected data and the results of the cleaning process.

Institutions Data: This table includes information on universities, laboratories, doctoral schools, and other institutions associated with the dissertations. Each entry corresponds to a single institution.

Individual Data: This table contains information on the individuals involved in the dissertations, including authors, supervisors, and jury members. Each entry corresponds to a single individual.


The data used in this project comes from three mains sources: 



Theses.fr: https://theses.fr/

Sudoc:  https://www.sudoc.fr/

IdRef:  https://www.idref.fr/]


If you use our data or scripts, please cite the following reference: “Delcey Thomas, and Aurélien Goutsmedt. (2024). Becoming an Economist: A Database of French Economics PhDs. Zenodo. https://doi.org/10.5281/zenodo.14541427”
DOI: 10.5281/zenodo.14718814
title: Becoming an Economist: A Database of French Economics PhDs

description: This database compiles information on Ph.D. dissertations in economics defended in France since 1900. See our companion website for news and full documentation.

The French database is implemented as a relational database that integrates multiple interconnected data frames. It is organized around four main components:



Thesis Metadata: This table contains the core information for each dissertation. Each entry corresponds to a single thesis and includes details such as the title, defense date, abstract, and other relevant metadata.

Edges Data: This table captures the connections between the other three tables, linking individuals, institutions, and theses. It associates each thesis with the individuals and institutions involved in its production, thereby enabling a synthetized view of these relationships. The edges data are provided in two formats: (1) a ready-to-use format with cleaned and standardized information; and (2) a more   extensive format that allows for comparison between the original  collected data and the results of the cleaning process.

Institutions Data: This table includes information on universities, laboratories, doctoral schools, and other institutions associated with the dissertations. Each entry corresponds to a single institution.

Individual Data: This table contains information on the individuals involved in the dissertations, including authors, supervisors, and jury members. Each entry corresponds to a single individual.


The data used in this project comes from three mains sources: 



Theses.fr: https://theses.fr/

Sudoc:  https://www.sudoc.fr/

IdRef:  https://www.idref.fr/]


If you use our data or scripts, please cite the following reference: “Delcey Thomas, and Aurélien Goutsmedt. (2024). Becoming an Economist: A Database of French Economics PhDs. Zenodo. https://doi.org/10.5281/zenodo.14541427”
DOI: 10.5281/zenodo.15270248
title: Becoming an Economist: A Database of French Economics PhDs

description: This database compiles information on Ph.D. dissertations in economics defended in France since 1900. See our companion website for news and full documentation.

The French database is implemented as a relational database that integrates multiple interconnected data frames. It is organized around four main components:



Thesis Metadata: This table contains the core information for each dissertation. Each entry corresponds to a single thesis and includes details such as the title, defense date, abstract, and other relevant metadata.

Edges Data: This table captures the connections between the other three tables, linking individuals, institutions, and theses. It associates each thesis with the individuals and institutions involved in its production, thereby enabling a synthetized view of these relationships. The edges data are provided in two formats: (1) a ready-to-use format with cleaned and standardized information; and (2) a more   extensive format that allows for comparison between the original  collected data and the results of the cleaning process.

Institutions Data: This table includes information on universities, laboratories, doctoral schools, and other institutions associated with the dissertations. Each entry corresponds to a single institution.

Individual Data: This table contains information on the individuals involved in the dissertations, including authors, supervisors, and jury members. Each entry corresponds to a single individual.


The data used in this project comes from three mains sources: 



Theses.fr: https://theses.fr/

Sudoc:  https://www.sudoc.fr/

IdRef:  https://www.idref.fr/]


If you use our data or scripts, please cite the following reference: “Delcey Thomas, and Aurélien Goutsmedt. (2024). Becoming an Economist: A Database of French Economics PhDs. Zenodo. https://doi.org/10.5281/zenodo.14541427”
DOI: 10.15468/dl.fabne2
title: Occurrence Download

description: A dataset containing 165 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((26.50399 45.73304,67.96299 45.73304,67.96299 62.29782,26.50399 62.29782,26.50399 45.73304))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Cicerbita macrophylla (Willd.) Wallr."
 ]
}

 The dataset includes 165 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006418-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.22033/esgf/cmip6.885
title: MIROC MIROC6 model output prepared for CMIP6 CFMIP

description: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets: These data include all datasets published for 'CMIP6.CFMIP.MIROC.MIROC6' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'.
 
 The MIROC6 climate model, released in 2017, includes the following components:
 aerosol: SPRINTARS6.0, atmos: CCSR AGCM (T85; 256 x 128 longitude/latitude; 81 levels; top level 0.004 hPa), land: MATSIRO6.0, ocean: COCO4.9 (tripolar primarily 1deg; 360 x 256 longitude/latitude; 63 levels; top grid cell 0-2 m), seaIce: COCO4.9. 
The model was run by the JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Kanagawa 236-0001, Japan), AORI (Atmosphere and Ocean Research Institute, The University of Tokyo, Chiba 277-8564, Japan), NIES (National Institute for Environmental Studies, Ibaraki 305-8506, Japan), and R-CCS (RIKEN Center for Computational Science, Hyogo 650-0047, Japan) (MIROC) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, land: 250 km, ocean: 100 km, seaIce: 100 km. 

Project: These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6).

CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ).

The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. - Project website: https://pcmdi.llnl.gov/CMIP6.
DOI: 10.15468/dl.bz5u2q
title: Occurrence Download

description: A dataset containing 491 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Armillaria (Fr.) Staude"
 ]
}

 The dataset includes 491 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006412-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29189966
title: Figure4_WAy.txt

description: Climate change attribution study.
DOI: 10.6084/m9.figshare.29189966.v1
title: Figure4_WAy.txt

description: Climate change attribution study.
DOI: 10.15468/dl.5y3mjm
title: Occurrence Download

description: A dataset containing 8253 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-56.96174 -37.14169,-35.59874 -37.14169,-35.59874 -18.61889,-56.96174 -18.61889,-56.96174 -37.14169))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Procellariiformes",
 "Year 2010-2025"
 ]
}

 The dataset includes 8253 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009065-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.