cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15370405
title: Volatile-rich evolution of molten super-Earth L 98-59 d (simulations and code)

description: Includes simulation data and plots produced by PROTEUS for our paper on the evolution of super-Earth L 98-59 d.

Summary of content is given in the table below.




Archive file
Content


l98d_main
Distilled data from main grid of main 900 simulations. Including atmosphere/interior profiles results in too much data for upload (>250 GB) so this just includes the most important information. These are CSV files (created by Pandas) which tabulate scalar quanities over time (e.g. Tsurf, Psurf, OLR, Radius) for each simulation. Also log and config files.


l98d_updated1
Updated grid of simulations for comparison against new density estimate by Cadieux+25, distilled in same manner as `l98d_main`, but also including some plots. Generated for paper revisions.


l98d_chemstudy
Case study of atmospheric chemistry with VULCAN from one of the simulation grid points. Includes full data.


l98d_sens_bands
Grid of 3 simulations testing sensitivity to spectral bands. Includes full data.


l98d_sens_corefrac
Grid of 25 testing sensitivity to corefraction. Includes full data.


l98d_sens_eccentric
Grid of 25 testing sensitivity to eccentricity. Includes full data.


l98d_sens_escape
Grid of 25 testing sensitivity to escape efficiency. Includes full data.




Other zip files contain archives of the the simulation codes and analysis scripts used to produce our article.
DOI: 10.15468/dl.amb96p
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((100.49 2.217179, 100.419685 2.211611, 100.351103 2.195042, 100.285943 2.167883, 100.225812 2.130801, 100.17219 2.08471, 100.126398 2.030747, 100.089563 1.97024, 100.062592 1.904681, 100.046146 1.835683, 100.040631 1.764945, 100.04618 1.694211, 100.062655 1.62522, 100.089651 1.559672, 100.126502 1.499181, 100.172299 1.445234, 100.225915 1.39916, 100.286031 1.362093, 100.351167 1.334945, 100.419718 1.318384, 100.49 1.312819, 100.560282 1.318384, 100.628833 1.334945, 100.693969 1.362093, 100.754085 1.39916, 100.807701 1.445234, 100.853498 1.499181, 100.890349 1.559672, 100.917345 1.62522, 100.93382 1.694211, 100.939369 1.764945, 100.933854 1.835683, 100.917408 1.904681, 100.890437 1.97024, 100.853602 2.030747, 100.80781 2.08471, 100.754188 2.130801, 100.694057 2.167883, 100.628897 2.195042, 100.560315 2.211611, 100.49 2.217179))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003192-260120142942310/datasets/export for details.
DOI: 10.6084/m9.figshare.31118719
title: Risk Factors for Severe and Profound Sensorineural Hearing Loss and Auditory Performance in Children After Cochlear Implant Surgery at Instituto Nacional de Salud del Niño, San Borja, Lima, 2021–2024

description: Sensorineural hearing loss in children, when associated with specific risk factors, can negatively affect language development, which in turn impacts their quality of life as well as their family and social environment.
DOI: 10.6084/m9.figshare.31118719.v1
title: Risk Factors for Severe and Profound Sensorineural Hearing Loss and Auditory Performance in Children After Cochlear Implant Surgery at Instituto Nacional de Salud del Niño, San Borja, Lima, 2021–2024

description: Sensorineural hearing loss in children, when associated with specific risk factors, can negatively affect language development, which in turn impacts their quality of life as well as their family and social environment.
DOI: 10.5281/zenodo.18330494
title: "And here we go again" 😒...  Our Historical Pattern

description: This is the dominant historical pattern of human civilization.What you identified is not a failure of modern people, ideology, or technology. It is a recurring civilizational cycle observed across cultures, eras, and systems of governance. Is the roadmap described in this document—crisis, reform, improvement, rollback, relapse—a persistent pattern across human history, or a modern anomaly? 

 

Research Question:

Is the roadmap described in this document—crisis, reform, improvement, rollback, relapse—a persistent pattern across human history, or a modern anomaly?

Short Answer

Yes.

This is the dominant historical pattern of human civilization.What you identified is not a failure of modern people, ideology, or technology. It is a recurring civilizational cycle observed across cultures, eras, and systems of governance. Is the roadmap described in this document—crisis, reform, improvement, rollback, relapse—a persistent pattern across human history, or a modern anomaly?
DOI: 10.5281/zenodo.18330493
title: "And here we go again" 😒...  Our Historical Pattern

description: This is the dominant historical pattern of human civilization.What you identified is not a failure of modern people, ideology, or technology. It is a recurring civilizational cycle observed across cultures, eras, and systems of governance. Is the roadmap described in this document—crisis, reform, improvement, rollback, relapse—a persistent pattern across human history, or a modern anomaly? 

 

Research Question:

Is the roadmap described in this document—crisis, reform, improvement, rollback, relapse—a persistent pattern across human history, or a modern anomaly?

Short Answer

Yes.

This is the dominant historical pattern of human civilization.What you identified is not a failure of modern people, ideology, or technology. It is a recurring civilizational cycle observed across cultures, eras, and systems of governance. Is the roadmap described in this document—crisis, reform, improvement, rollback, relapse—a persistent pattern across human history, or a modern anomaly?
DOI: 10.5281/zenodo.18330369
title: Mesocarnivore diet in a human-dominated landscape with abundant livestock and low large carnivore presence

description: This dataset is associated with the manuscript entitled 'Mesocarnivore diet in a human-dominated landscape with abundant livestock and low large carnivore presence', which is currently in review with a scientific journal. In this research we assessed the diet of black-backed jackal from genetically confirmed jackal scat collected between 2019-2022 in four communal conservancies of central-eastern Namibia. To explore how jackal diet may be influenced by the presence of wild dogs, we compared jackal diet within vs. more than 10km from wild dog denning areas. The dataset includes two Microsoft Excel databases: 1) Jackal Sample Genetic ID and Locations: This database contains a list of scat samples included in study with genetic species identity and locations. 2) Jackal Diet Analysis Data: This database supports the diet study of black-backed jackal and consists of two worksheets (Proportion of items by volume, Cuticular imprint reading).
DOI: 10.5281/zenodo.18330370
title: Mesocarnivore diet in a human-dominated landscape with abundant livestock and low large carnivore presence

description: This dataset is associated with the manuscript entitled 'Mesocarnivore diet in a human-dominated landscape with abundant livestock and low large carnivore presence', which is currently in review with a scientific journal. In this research we assessed the diet of black-backed jackal from genetically confirmed jackal scat collected between 2019-2022 in four communal conservancies of central-eastern Namibia. To explore how jackal diet may be influenced by the presence of wild dogs, we compared jackal diet within vs. more than 10km from wild dog denning areas. The dataset includes two Microsoft Excel databases: 1) Jackal Sample Genetic ID and Locations: This database contains a list of scat samples included in study with genetic species identity and locations. 2) Jackal Diet Analysis Data: This database supports the diet study of black-backed jackal and consists of two worksheets (Proportion of items by volume, Cuticular imprint reading).
DOI: 10.5281/zenodo.18329207
title: SuperDARN data in netCDF format (2002-Jul)

description: 2002-Jul SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6787706
title: SuperDARN data in netCDF format (2002-Jul)

description: 2002-Jul SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.15468/dl.pk7x86
title: Occurrence Download

description: A dataset containing 147615 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Aegolius acadicus"
 ]
}

 The dataset includes 147615 records from 157 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003164-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.regjkr
title: Occurrence Download

description: A dataset containing 1002 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "PublishingCountry is Colombia",
 {
 "and" : [
 "Country is Colombia",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 }
 ]
 },
 {
 "and" : [
 "Geometry POLYGON((-73.22388 6.13654,-73.22792 6.06044,-73.16218 6.05709,-73.16252 6.13721,-73.22388 6.13654))",
 "TaxonKey is one of (Amphibia [GBIF Backbone Taxonomy])"
 ]
 }
 ]
}

 The dataset includes 1002 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003193-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a8krey
title: Occurrence Download

description: A dataset containing 6631 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is COL.2_2",
 "OccurrenceStatus is Present",
 "TaxonKey is Psittacara wagleri"
 ]
}

 The dataset includes 6631 records from 22 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003194-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60966/k96ok76z
title: Building Stronger Transport Policy: An Evidence Gap Map - Dataset

description: Efficient and reliable transport systems are central to economic growth, social inclusion, and environmental sustainability. In Latin America and the Caribbean (LAC), transport and logistics performance remains below that of advanced economies, constraining access to services, social inclusion (Scholl et al., 2021), competitiveness, and productivity (Calatayud & Montes, 2021).

The EGM, available at https://developmentevidence.3ieimpact.org/egm/transportation-evidence-gap-map, presents global effectiveness evidence on transportation interventions, including roads, regional transportation and logistics; urban mobility infrastructure; and laws, regulations, and policies governing public transit, mobility, traffic, and transportation.

Financed and co-produced by the Inter-American Development Bank (IDB), the EGM compiles, curates, and classifies studies that estimate causal effects, displaying where evidence is clustered and where gaps remain. It aims to help decision-makers identify the most promising approaches for improving transport systems, highlight priority areas for future research, and ultimately support evidence-informed policymaking, enhance the allocation of scarce resources, and contribute to safer, more inclusive, and more sustainable transport in LAC and beyond.

Know of any studies that could be included in this map? We invite you to share them with us using this form.
 
Note: This map includes studies published between 2005 and April 2025. Eligible studies from China—mainly focused on high-speed rail—are listed separately here.

This Evidence Gap Map was co-produced by the Inter-American Development Bank’s Transport and Knowledge and Learning Divisions, and the International Initiative for Impact Evaluation (3ie). It is part of the broader collaboration between the IDB and 3ie, formalized through a Memorandum of Understanding signed in October 2023. The authors are solely responsible for any errors or omissions.

IDB project collaborators: Camilo Acosta, Leonel Borja, Agustina Calatayud, Vileydy González, Minji Kang, Indira Porto, María Eugenia Rivas, Magdalena Rossetti, Santiago Sánchez, Gonzalo Santamaría, Valentina Sequi, and Alejandro Taddia.

3ie project collaborators: María Daniela Anda, Diana Belén Córdova-Aráuz, Mark Engelbert, Tomasz Kozakiewicz, and Shannon Shisler.
DOI: 10.15468/dl.6cde5n
title: Occurrence Download

description: A dataset containing 156 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((-73.56100000000001 7.644109, -73.631888 7.638537, -73.701025 7.62196, -73.766704 7.594786, -73.827305 7.557686, -73.881332 7.511577, -73.927454 7.457596, -73.964538 7.397075, -73.99167199999999 7.331507, -74.00819199999999 7.262507, -74.013696 7.191776, -74.008053 7.121056, -73.99140800000001 7.052088, -73.964175 6.986568, -73.92702800000001 6.926108, -73.88088399999999 6.872195, -73.82687900000001 6.826154, -73.76634199999999 6.789115, -73.700762 6.76199, -73.63175 6.745443, -73.56100000000001 6.739882, -73.49025 6.745443, -73.421238 6.76199, -73.35565800000001 6.789115, -73.29512099999999 6.826154, -73.24111600000001 6.872195, -73.19497200000001 6.926108, -73.157825 6.986568, -73.13059199999999 7.052088, -73.113947 7.121056, -73.108304 7.191776, -73.11380800000001 7.262507, -73.13032800000001 7.331507, -73.157462 7.397075, -73.194546 7.457596, -73.240668 7.511577, -73.294695 7.557686, -73.355296 7.594786, -73.420975 7.62196, -73.490112 7.638537, -73.56100000000001 7.644109))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 156 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003191-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.60966/sij240vu
title: Informing Citizen Security Policy: An Evidence Gap Map on Policing Interventions - Dataset

description: Citizen security remains one of the most pressing development challenges facing low- and middle-income countries around the globe. In Latin America and the Caribbean (LAC), for example—a region where homicide rates have consistently remained more than three times the global average (UNODC, 2023; InSight Crime, 2024)—crime and violence are estimated to cost approximately 3.4% of the region’s GDP (IDB, 2024), whereas research suggests that bringing the crime level in Latin America down to the world average would boost LAC’s average annual growth rate by 0.5 percentage points (IMF, 2023).

This Evidence Gap Map (EGM) focuses on citizen security interventions led or supported by police agencies, and maps existing impact evaluations and systematic reviews that examine the effectiveness of a wide range of policing interventions aimed at reducing crime, violence, disorder, overall insecurity, and their associated risk factors and underlying determinants. While some previous evidence maps have narrowly focused on specific strategies or contexts, this EGM takes a broader and more inclusive and comprehensive approach, covering a wide range of intervention types, settings, and outcome areas.

The EGM is available at: https://developmentevidence.3ieimpact.org/egm/IDB-policing-egm

By synthesizing rigorous evidence on what works, what doesn’t, and where gaps remain, the EGM aims to inform policymakers, practitioners, and researchers on the most effective uses of policing resources. It is intended to support evidence-informed decision-making, promote more effective allocation of public security investments, and ultimately contribute to safer communities and stronger economies across the LAC region and beyond.

This EGM was developed through a collaborative effort across multiple teams within the Inter-American Development Bank (IDB), and peer-reviewed, and visualized by the International Initiative for Impact Evaluation (3ie) in 2025 to ensure methodological rigor and transparency.

Project collaborators include Camilo Acosta, Sergio Britto Lima, Minji Kang, Indira Porto, Rodrigo Serrano Berthet, and Harold Villalba (listed alphabetically).
DOI: 10.60966/6x55ayx4
title: Sample Code for: Creating Public Payroll Indicators: A Methodological Guide

description: The R code is used to calculate and standardize payroll indicators from common-format personnel records.
Specifically, it provides working examples for deriving each key indicator (wage bill growth, employment growth, average pay trajectories, pay equity, gender pay gap, turnover, promotions/career progression, and retirement projections), so governments can compute these measures for the whole administration, for specific agencies, or for employee subgroups (e.g., by job, gender, contract). The code also illustrates recommended calculations and helps address common data errors, enabling comparable, reproducible salary indicators across countries.
DOI: 10.15468/dl.jftzyh
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((100.393 2.235179, 100.322684 2.229611, 100.254101 2.213042, 100.188941 2.185882, 100.128809 2.1488, 100.075187 2.10271, 100.029394 2.048747, 99.992559 1.98824, 99.965587 1.92268, 99.94914199999999 1.853682, 99.94362599999999 1.782945, 99.94917599999999 1.71221, 99.96565200000001 1.64322, 99.992648 1.577672, 100.029499 1.51718, 100.075296 1.463234, 100.128913 1.41716, 100.18903 1.380093, 100.254166 1.352945, 100.322718 1.336385, 100.393 1.330819, 100.463282 1.336385, 100.531834 1.352945, 100.59697 1.380093, 100.657087 1.41716, 100.710704 1.463234, 100.756501 1.51718, 100.793352 1.577672, 100.820348 1.64322, 100.836824 1.71221, 100.842374 1.782945, 100.836858 1.853682, 100.820413 1.92268, 100.793441 1.98824, 100.756606 2.048747, 100.710813 2.10271, 100.657191 2.1488, 100.597059 2.185882, 100.531899 2.213042, 100.463316 2.229611, 100.393 2.235179))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003196-260120142942310/datasets/export for details.
DOI: 10.60966/hs6a70d6
title: IDB Group Impact Framework Performance Targets: Dataset

description: This dataset provides detailed data on the Performance Targets indicators of the IDB Group Impact Framework.

The Impact Framework is the highest-level tool of the IDB, IDB Invest, and IDB Lab for monitoring performance and achieving strategic objectives under IDBStrategy. It serves important functions in both accountability and performance management, with indicators that capture our Mission Goals, Portfolio Results, and Performance Targets. 

This dataset contains the 2024-2030 indicators and targets that guide the work of the IDB, IDB Invest, and IDB Lab to deliver tangible results for Latin America and the Caribbean.
DOI: 10.15468/dl.mda894
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Taxonomy of the Micrurus spixii species complex (Serpentes, Elapidae)"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003195-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/14573822
title: Balochi Language to English Translation Dataset