cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14750804
title: Relative endorsements for development finance strategies in national statements of IMF-World Bank meetings 2015-2024

description: To systematically assess the extent to which WBG shareholders endorse portfolio derisking compared to the other two approaches identified by our trilemma, we conducted a content analysis of national shareholder statements at the bi-annual meeting of IMF-World Bank meeting (development committee) from 2015 to 2024. 

We first categorized statements according to whether they contained explicit endorsements of one of three dominant approaches: (1) private capital mobilization, subdivided into (i) project derisking, (ii) portfolio derisking, and (iii) unspecified; (2) leveraging or strenghtening MDBs, subdivided into (2i) CAF reforms, (2ii) WBG capital increase, and (2iii) IDA replenishment; and (3) domestic resource mobilization, subdivided into (3i) figting illicit capital flight, (3ii) sovereign debt restructuring, and (3iii) other.

Subsequently, we weigh every endorsement according to the shareholder voting share in the three main institutions of the World Bank Group (WBG) – the IBRD, the IDA, and the IFC. See tab Data analysis and Voting share.

As the data shows, only a minority of WBG shareholders – weighted by vote share – have endorsed portfolio derisking approach as a desirable approach to reach the ambitions of the MFD agenda.

The statements have been read systematically, with the use of Qualtrics, with exact mentions and text excerpts written down. These forms can be made available upon request.
DOI: 10.5281/zenodo.14750875
title: Relative endorsements of development finance instruments in GDG- and ODI-policy documents

description: To assess the relative approval of the three approaches identified by our trilemma, we conducted a content analysis of policy documents published by the two leading independent think tanks in global development finance: the US-based CDG and the UK-based ODI. We categorised the Type of financing: (1) external, (2) mixed, (3) domestic. Subdivided into: (1) private capital mobilization, subdivided into (i) project derisking, (ii) portfolio derisking, and (iii) unspecified; (2) leveraging or strenghtening MDBs, subdivided into (2i) CAF reforms, (2ii) WBG capital increase, and (2iii) IDA replenishment; and (3) domestic resource mobilization, subdivided into (3i) figting illicit capital flight, (3ii) sovereign debt restructuring, and (3iii) other.

The G20 independent expert groups commissioned to write key reports on MDB reforms over the last decade – Making the Global Financial System Work for All (G20 Eminent Persons Group on Global Financial Governance, 2018), Boosting MDBs’ Investing Capacity: An Independent Review of MDBs’ Capital Adequacy Frameworks (G20 CAF Review Expert Panel, 2022), Strengthening the MDBs: The Triple Agenda (G20 Independent Expert Panel, 2023 – included affiliates of the GCD and/or ODI. 

To gauge the relative focus of the two think tanks on different approaches in the MFD agenda, we categorized 207 policy documents published from 2015 to 2024 with a focus on the MFD agenda according to whether they contained explicit endorsement of private (project or portfolio) derisking and/or leveraging/strengthening of MDBs. There has been some rise in endorsements of portfolio derisking proposals since 2020. Nevertheless, endorsement of such proposals have been far fewer than endorsements of proposals related to leveraging and/or strengthening the traditional business model of the MDBs.

The thinktank publications have been read systematically, with the use of Qualtrics, with exact mentions and text excerpts written down. These forms can be made available upon request. Qualtrics survey: https://ugent.qualtrics.com/jfe/form/SV_6Vx84GPlZyQ2ciG
DOI: 10.5281/zenodo.14750876
title: Relative endorsements of development finance instruments in GDG- and ODI-policy documents

description: To assess the relative approval of the three approaches identified by our trilemma, we conducted a content analysis of policy documents published by the two leading independent think tanks in global development finance: the US-based CDG and the UK-based ODI. We categorised the Type of financing: (1) external, (2) mixed, (3) domestic. Subdivided into: (1) private capital mobilization, subdivided into (i) project derisking, (ii) portfolio derisking, and (iii) unspecified; (2) leveraging or strenghtening MDBs, subdivided into (2i) CAF reforms, (2ii) WBG capital increase, and (2iii) IDA replenishment; and (3) domestic resource mobilization, subdivided into (3i) figting illicit capital flight, (3ii) sovereign debt restructuring, and (3iii) other.

The G20 independent expert groups commissioned to write key reports on MDB reforms over the last decade – Making the Global Financial System Work for All (G20 Eminent Persons Group on Global Financial Governance, 2018), Boosting MDBs’ Investing Capacity: An Independent Review of MDBs’ Capital Adequacy Frameworks (G20 CAF Review Expert Panel, 2022), Strengthening the MDBs: The Triple Agenda (G20 Independent Expert Panel, 2023 – included affiliates of the GCD and/or ODI. 

To gauge the relative focus of the two think tanks on different approaches in the MFD agenda, we categorized 207 policy documents published from 2015 to 2024 with a focus on the MFD agenda according to whether they contained explicit endorsement of private (project or portfolio) derisking and/or leveraging/strengthening of MDBs. There has been some rise in endorsements of portfolio derisking proposals since 2020. Nevertheless, endorsement of such proposals have been far fewer than endorsements of proposals related to leveraging and/or strengthening the traditional business model of the MDBs.

The thinktank publications have been read systematically, with the use of Qualtrics, with exact mentions and text excerpts written down. These forms can be made available upon request. Qualtrics survey: https://ugent.qualtrics.com/jfe/form/SV_6Vx84GPlZyQ2ciG
DOI: 10.15468/dl.j6xd6b
title: Occurrence Download

description: A dataset containing 474054 species occurrences available in GBIF matching the query:
{
 "and" : [
 "CoordinateUncertaintyInMeters 0.0-1000000.0",
 "Country is United States of America",
 "GadmGid is USA.15_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 474054 records from 352 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000545-250127130748423/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.28290053
title: LC-MS analysis of oligogalacturonide production

description: LC-MS analysis of oligogalacturonide production from leaves of A. thaliana plants (cultivated at high (HN) or low N (LN)) incubated for 18 h in liquid medium supplemented with spores of the WT, BcPNL1 mutant (pnl15, pnl16 and pnl17) and complemented strains (pnlC1 and pnlC2) of B. cinerea.
DOI: 10.6084/m9.figshare.28290053.v1
title: LC-MS analysis of oligogalacturonide production

description: LC-MS analysis of oligogalacturonide production from leaves of A. thaliana plants (cultivated at high (HN) or low N (LN)) incubated for 18 h in liquid medium supplemented with spores of the WT, BcPNL1 mutant (pnl15, pnl16 and pnl17) and complemented strains (pnlC1 and pnlC2) of B. cinerea.
DOI: 10.5519/qd.frvepx71
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (158 records)
DOI: 10.5281/zenodo.14691473
title: METAR cloud cover over weather stations in Sentinel-2 satellite images

description: This dataset contains the processed Sentinel-2 satellite images of level L1C, used in the Machine Learning model of MSCC (also known as AIMLSSE) for the ordinal classification of cloud cover in the METAR format as commonly used by weather stations.

This dataset contains 12749 cut-outs of satellite images in the dimensions of 16 × 16 km with a weather station in the center. The images are reduced to a size of 300 × 300 px. The images are in the TIF format, with RGB color channels that have been pre-multiplied by the NDSI factor of each Sentinel-2 color band (Band 2, 3, and 4) and a SWIR band of a similar resolution (B11). The names and resolutions are also found here:

bands_metadata.csv




Band
Description
Resolution
Central Wavelength


B2
Blue
10 m
490 nm


B3
Green
10 m
560 nm


B4
Red
10 m
665 nm


B11
Short Wave Infrared (SWIR)
20 m
1610 nm




Be aware that data mismatches between weather station data and satellite images are unavoidable. The time differences between satellite and weather station observations have been capped at 30 minutes to ensure relatively stable weather conditions for the training model while also providing enough data to train, validate, and test the Machine Learning model. Additionally, some stations are no longer stationed at their original location, which is not reflected in the input data.

The data itself is organized into three subsets for training, validation, and testing of Machine Learning models. Each directory is structured as outlined here:

├── [station name 1]/
│   ├── [Sentinel-2 product ID 1].tif
│   ├── [Sentinel-2 product ID 2].tif
│   └── ...
├── [station name 2]/
│   ├── [Sentinel-2 product ID 1].tif
│   ├── [Sentinel-2 product ID 2].tif
│   └── ...
└── ...

The station name directly identifies the weather station with a unique ID, while the Sentinel-2 product ID allows to re-download the exact same image from which this section has been taken via the Copernicus Open Access Hub. The data is collected from January 2023 until June 2023.

Assuming that the locations are correct, the stations have been clustered for an approximate 80-10-10 distribution for training, validation, and test respectively, ensuring no overlapping regions exist between the three subsets.

The mapping of the images to the METAR reference values as well as the manual labels, and the time difference between satellite image and METAR observation are provided in the following files:

training_labels.csv
validation_labels.csv
test_labels.csv

Automatic cloud cover is found under “max cloud cover” while the manually adjusted labels are located in column “true cloud cover”. The label distributions apply to the dataset labels.

The weights for the dataset labels are provided in:

training_weights.csv

The weights correspond to the inverse frequency of label occurrence in the dataset and can be used for both loss functions and data samplers.
DOI: 10.5281/zenodo.14691474
title: METAR cloud cover over weather stations in Sentinel-2 satellite images

description: This dataset contains the processed Sentinel-2 satellite images of level L1C, used in the Machine Learning model of MSCC (also known as AIMLSSE) for the ordinal classification of cloud cover in the METAR format as commonly used by weather stations.

This dataset contains 12749 cut-outs of satellite images in the dimensions of 16 × 16 km with a weather station in the center. The images are reduced to a size of 300 × 300 px. The images are in the TIF format, with RGB color channels that have been pre-multiplied by the NDSI factor of each Sentinel-2 color band (Band 2, 3, and 4) and a SWIR band of a similar resolution (B11). The names and resolutions are also found here:

bands_metadata.csv




Band
Description
Resolution
Central Wavelength


B2
Blue
10 m
490 nm


B3
Green
10 m
560 nm


B4
Red
10 m
665 nm


B11
Short Wave Infrared (SWIR)
20 m
1610 nm




Be aware that data mismatches between weather station data and satellite images are unavoidable. The time differences between satellite and weather station observations have been capped at 30 minutes to ensure relatively stable weather conditions for the training model while also providing enough data to train, validate, and test the Machine Learning model. Additionally, some stations are no longer stationed at their original location, which is not reflected in the input data.

The data itself is organized into three subsets for training, validation, and testing of Machine Learning models. Each directory is structured as outlined here:

├── [station name 1]/
│   ├── [Sentinel-2 product ID 1].tif
│   ├── [Sentinel-2 product ID 2].tif
│   └── ...
├── [station name 2]/
│   ├── [Sentinel-2 product ID 1].tif
│   ├── [Sentinel-2 product ID 2].tif
│   └── ...
└── ...

The station name directly identifies the weather station with a unique ID, while the Sentinel-2 product ID allows to re-download the exact same image from which this section has been taken via the Copernicus Open Access Hub. The data is collected from January 2023 until June 2023.

Assuming that the locations are correct, the stations have been clustered for an approximate 80-10-10 distribution for training, validation, and test respectively, ensuring no overlapping regions exist between the three subsets.

The mapping of the images to the METAR reference values as well as the manual labels, and the time difference between satellite image and METAR observation are provided in the following files:

training_labels.csv
validation_labels.csv
test_labels.csv

Automatic cloud cover is found under “max cloud cover” while the manually adjusted labels are located in column “true cloud cover”. The label distributions apply to the dataset labels.

The weights for the dataset labels are provided in:

training_weights.csv

The weights correspond to the inverse frequency of label occurrence in the dataset and can be used for both loss functions and data samplers.
DOI: 10.15468/dl.r76q3p
title: Occurrence Download

description: A dataset containing 9150 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "TaxonKey is Ara macao (Linnaeus, 1758)"
 ]
}

 The dataset includes 9150 records from 78 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000565-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9d4gfv
title: Occurrence Download

description: A dataset containing 65030 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-106.32923 23.70872,-105.27541 17.89976,-100.21706 17.92483,-100.2434 23.75696,-106.32923 23.70872))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Cathartes aura (Linnaeus, 1758)"
 ]
}

 The dataset includes 65030 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000566-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uq85p7
title: Occurrence Download

description: A dataset containing 131081 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Hyla arborea (Linnaeus, 1758), Hyla molleri Bedriaga, 1889, Hyla meridionalis Boettger, 1874, Hyla intermedia Boulenger, 1882, Hyla sarda (De Betta, 1853))",
 "OccurrenceStatus is one of (Present)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil)"
 ]
 }
 },
 "Year is greater than or equal to 2010"
 ]
}

 The dataset includes 131081 records from 1643 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000556-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q64f7t
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eleocharis bahiensis D.A.Simpson"
 ]
}

 The dataset includes 19 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0155552-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gvprp3
title: Occurrence Download

description: A dataset containing 21 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Dioscorea spectabilis R.Knuth"
 ]
}

 The dataset includes 21 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0155553-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.srj55x
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cordyceps bicephala Berk."
 ]
}

 The dataset includes 12 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0241679-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rhfc4s
title: Occurrence Download

description: A dataset listing the 2757318 species recorded in GBIF matching the query:
{ }

 The dataset's 2757318 records were derived from 25050 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001856-190918142434337/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.424hge
title: Occurrence Download

description: A dataset containing 1975 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cochlospermum planchonii Hook.fil. ex Planch."
 ]
}

 The dataset includes 1975 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005025-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8yf5c7
title: Occurrence Download

description: A dataset containing 5615 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "TaxonKey is Erigeron karvinskianus DC.",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5615 records from 170 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010780-171219132708484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bgx42d
title: Occurrence Download

description: A dataset containing 30461 species occurrences available in GBIF matching the query:
{
 "Geometry" : [
 "POLYGON ((-126 58.78068, -120 58.78068, -120 60.0882, -126 60.0882, -126 58.78068))"
 ]
}

 The dataset includes 30461 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039043-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pgkuup
title: Occurrence Download

description: A dataset containing 1541 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cochlospermum tinctorium Perr. ex A.Rich."
 ]
}

 The dataset includes 1541 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005042-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dusntx
title: Occurrence Download

description: A dataset containing 1229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Blandfordiaceae"
 ]
}

 The dataset includes 1229 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059313-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.93bwtg
title: Occurrence Download

description: A dataset containing 2065 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "OccurrenceStatus is Present",
 "TaxonKey is Ardisia crispa (Thunb.) A.DC."
 ]
}

 The dataset includes 2065 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052007-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dng4xc
title: Occurrence Download

description: A dataset containing 6184 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 }
 ]
 },
 "TaxonKey is Nyctipolus nigrescens (Cabanis, 1849)"
 ]
}

 The dataset includes 6184 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005017-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xkioun
title: Occurrence Download

description: A dataset containing 611 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Pharomachrus mocinno La Llave, 1832",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 611 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010781-160118175350007/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.b24568
title: Occurrence Download

description: A dataset containing 694 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Fagraea gracilipes A.Gray"
 ]
}

 The dataset includes 694 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0051995-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a54z7z
title: Occurrence Download

description: A dataset containing 273 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cochlospermum religiosum (L.) Alston"
 ]
}

 The dataset includes 273 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005034-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wxvjfx
title: Occurrence Download

description: A dataset containing 2558 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Macrolobium Schreb."
 ]
}

 The dataset includes 2558 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010781-160623103540712/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tqp5wm
title: Occurrence Download

description: A dataset containing 46 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Festuca lahonderei Kerguélen & Plonka"
 ]
}

 The dataset includes 46 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0052005-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fpx9th
title: Occurrence Download

description: A dataset containing 575 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coddia rudis (E.Mey. ex Harv.) Verdc."
 ]
}

 The dataset includes 575 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005083-240314170635999/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.