cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18742/28718606
title: Mothers on the Margins: metadata and study documents

description: This project includes qualitative and quantitative data.All qualitative data produced during the study is owned by King's College London. We recognise the importance of balancing open access to research data with the need to protect the confidentiality and privacy of individuals. Due to the very high sensitivity of the data that will be produced in this study (e.g. in-depth qualitative interviews about the experiences of families undergoing children's social care proceedings or who have had their infants removed from their custody), it will not be possible to deposit the underlying data or make this publicly available in its raw form. However, we share copies of the interview schedules/topic guides.For the electronic health record analysis, data are owned by a third party, Maudsley Biomedical Research Centre (BRC) Clinical Records Interactive Search (CRIS) tool, which provides access to anonymised data derived from SLaM electronic medical records. These data can only be accessed by permitted individuals from within a secure firewall (i.e. the data cannot be sent elsewhere). The data has to remain within the SLAM firewall at all times.
DOI: 10.18742/28718606.v1
title: Mothers on the Margins: metadata and study documents

description: This project includes qualitative and quantitative data.All qualitative data produced during the study is owned by King's College London. We recognise the importance of balancing open access to research data with the need to protect the confidentiality and privacy of individuals. Due to the very high sensitivity of the data that will be produced in this study (e.g. in-depth qualitative interviews about the experiences of families undergoing children's social care proceedings or who have had their infants removed from their custody), it will not be possible to deposit the underlying data or make this publicly available in its raw form. However, we share copies of the interview schedules/topic guides.For the electronic health record analysis, data are owned by a third party, Maudsley Biomedical Research Centre (BRC) Clinical Records Interactive Search (CRIS) tool, which provides access to anonymised data derived from SLaM electronic medical records. These data can only be accessed by permitted individuals from within a secure firewall (i.e. the data cannot be sent elsewhere). The data has to remain within the SLAM firewall at all times.
DOI: 10.15468/dl.v79nnj
title: Occurrence Download

description: A dataset listing the 5 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Psittacus erithacus"
 ]
}

 The dataset's 5 records were derived from 161 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038523-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mk2uke
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((111.632 0.630184, 111.561733 0.624617, 111.493196 0.608052, 111.428078 0.580897, 111.367982 0.543822, 111.314387 0.497738, 111.268614 0.443782, 111.23179 0.383281, 111.20482 0.317726, 111.188368 0.248731, 111.18284 0.177994, 111.188372 0.107258, 111.204826 0.038264, 111.231798 -0.02729, 111.268625 -0.08778900000000001, 111.314398 -0.141744, 111.367992 -0.187826, 111.428087 -0.2249, 111.493203 -0.252053, 111.561736 -0.268618, 111.632 -0.274185, 111.702264 -0.268618, 111.770797 -0.252053, 111.835913 -0.2249, 111.896008 -0.187826, 111.949602 -0.141744, 111.995375 -0.08778900000000001, 112.032202 -0.02729, 112.059174 0.038264, 112.075628 0.107258, 112.08116 0.177994, 112.075632 0.248731, 112.05918 0.317726, 112.03221 0.383281, 111.995386 0.443782, 111.949613 0.497738, 111.896018 0.543822, 111.835922 0.580897, 111.770804 0.608052, 111.702267 0.624617, 111.632 0.630184))"},{"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/0038550-251120083545085/datasets/export for details.
DOI: 10.15468/dl.8zu6a7
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Rubus ulmifolius"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038553-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eybevv
title: Occurrence Download

description: A dataset containing 60972 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Fishes of Texas Project (FoTX) Database - Darwin Core",
 "Geometry POLYGON((-98.26417 26.09353,-99.08801 27.27812,-100.02015 28.51886,-100.55718 29.63821,-101.91025 31.05639,-103.41845 32.07232,-103.82054 32.90185,-103.93103 33.27999,-103.9591 34.38714,-103.9591 34.38714,-104.58821 35.20577,-105.41289 36.00372,-105.2205 37.54462,-107.52531 38.25738,-107.67808 37.45366,-107.0087 36.62357,-107.8963 33.11488,-107.10404 31.81022,-105.28672 30.28374,-104.11592 28.93734,-102.93312 28.71919,-102.4351 29.4265,-101.3768 29.48071,-100.89334 28.72577,-100.26232 28.06453,-99.98237 27.7152,-99.75182 27.3355,-99.58713 26.8223,-99.22484 26.33629,-98.80792 26.30214,-98.66951 26.20339,-98.57829 26.20339,-98.46221 26.17338,-98.36757 26.13091,-98.27512 26.08527,-98.26417 26.09353))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 60972 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038526-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k823yt
title: Occurrence Download

description: A dataset listing the 5 species recorded in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-137.94458 2.02944,-53.05542 2.02944,-53.05542 35.97056,-137.94458 35.97056,-137.94458 2.02944))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pleopeltis muenchii"
 ]
}

 The dataset's 5 records were derived from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038521-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5s9p7h
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Filogranula annulata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038554-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ar/mhakow
title: PAN-00181485 - composite Rollenkappe-brooch

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00181485&lt;/p&gt;
description: Modified: 2025-10-24T15:42:50+02:00
DOI: 10.15468/dl.fd2qd7
title: Occurrence Download

description: A dataset containing 1219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ruellia blechum"
 ]
}

 The dataset includes 1219 records from 66 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038555-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.48472/datapb/ydw3im
title: Research Data Management: An investigation from the perspective of Biodiversity, in the context of Open Science

description: It addresses research data management in the field of biodiversity within the Open Science movement. The research is conducted in the Doctoral Program in Information Science at the Federal University of Paraíba and aims to analyze the perceptions of faculty/researchers regarding Research Data Management in Postgraduate Biodiversity Programs at public universities in Brazil. The specific objectives include identifying the understanding of faculty/researchers about the stages of the Data Lifecycle, evaluating the understanding of faculty/researchers about the stages of the Data Lifecycle, and mapping the understanding of faculty/researchers about the stages of the Data Lifecycle. This study is justified by the need to understand the aspects of data management in the context of biodiversity, given the increasing demand for open science that promotes transparency, accessibility, and reproducibility of data. The research is applied and exploratory, aiming to investigate the practices of biodiversity faculty/researchers in Brazil. Questionnaires were administered to collect data on the perceptions and practices of these faculty/researchers regarding the sharing and reuse of research data. Research data management for Open Science promotes transparency, reuse, and interdisciplinary collaboration. In the context of biodiversity, the work explores the challenges and strategies to effectively organize, analyze, and share data. Therefore, it involves practices for organizing, storing, and reusing data. It also discusses the intersection between data management, biodiversity, and open science. The research intends to contribute to the understanding and improvement of data management practices in the field of biodiversity in Brazil, promoting discussions on more effective and collaborative strategies for the advancement of science.
DOI: 10.15468/dl.7bcwm7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((101.793 0.644184, 101.722733 0.638617, 101.654196 0.622052, 101.589077 0.594897, 101.528981 0.557822, 101.475387 0.511738, 101.429614 0.457782, 101.392789 0.397281, 101.365819 0.331726, 101.349368 0.262731, 101.34384 0.191994, 101.349371 0.121258, 101.365826 0.052263, 101.392798 -0.013291, 101.429625 -0.07378999999999999, 101.475398 -0.127744, 101.528992 -0.173826, 101.589087 -0.2109, 101.654203 -0.238053, 101.722736 -0.254618, 101.793 -0.260185, 101.863264 -0.254618, 101.931797 -0.238053, 101.996913 -0.2109, 102.057008 -0.173826, 102.110602 -0.127744, 102.156375 -0.07378999999999999, 102.193202 -0.013291, 102.220174 0.052263, 102.236629 0.121258, 102.24216 0.191994, 102.236632 0.262731, 102.220181 0.331726, 102.193211 0.397281, 102.156386 0.457782, 102.110613 0.511738, 102.057019 0.557822, 101.996923 0.594897, 101.931804 0.622052, 101.863267 0.638617, 101.793 0.644184))"},{"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/0038556-251120083545085/datasets/export for details.
DOI: 10.7910/dvn/3cwqhi
title: Replication Data for: EPA Biennial Hazardous Waste Report 2023

description: Federal regulations require large quantity generators to submit a report every two years regarding the nature, quantities and disposition of hazardous waste generated at their facility. EPA refers to this as the National Biennial RCRA Hazardous Waste Report or Biennial Report. Some of these tables offer summary information about hazardous waste sites in an easy-to-use format and are best for obtaining counts and basic information. Other files include all data tables organized by topic area and are available for analysts who require access to comprehensive and/or historical data. Tables with more than one million records comprise multiple files. General info available here: https://www.epa.gov/hwgenerators/biennial-hazardous-waste-report
DOI: 10.34740/kaggle/dsv/14064642
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.qtpxs3
title: Occurrence Download

description: A dataset listing the 2 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Gabon",
 "TaxonKey is Panthera pardus",
 "Year 2010-2025"
 ]
}

 The dataset's 2 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038535-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3m5amm
title: Occurrence Download

description: A dataset containing 1297 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ruellia ciliatiflora"
 ]
}

 The dataset includes 1297 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038557-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.23086.16965
title: Supp2.pdf
DOI: 10.15468/dl.3msk5z
title: Occurrence Download

description: A dataset containing 966 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Country is Mexico",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Ruellia inundata"
 ]
}

 The dataset includes 966 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038559-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/jyhgtf
title: Replication Data for: Timing Matters: Analyzing Climate Policies and Adaptive Resilience

description: As the world grapples with the escalating impacts of climate change, a vital question that remains for both scholars and policymakers is not just whether climate policies work, but: when do they make a difference? This paper seeks to answer this question while shifting the primary focus to when climate adaptation policies succeed. Leveraging data on adaptation laws and adaptive capacity, we employ change point analysis and segmented regression techniques to identify (and estimate the impact of) distinct time periods where policy effectiveness shifts, investigating the temporal dynamics of climate policies. While adaptation laws show modest positive effects in aggregate analyses, their impact varies dramatically across historical periods shaped by global conditions. During the Pre-2006 period, adaptation laws demonstrated significant positive long-term effects. However, during 2007-2015, laws were only effective when coupled with external financial support. Most strikingly, post-2016, populist governance has systematically undermined adaptation law effectiveness through significant negative interactions with legal frameworks. These patterns highlight how time- variant exogenous factors (e.g., economic crises, financial support, and political shifts) significantly impact policy effectiveness. By identifying conditions under which policies succeed, our study underscores the necessity for temporally and contextually aligned climate strategies.
DOI: 10.17026/ar/npyuhn
title: PAN-00181677 - early medieval enamelled disc brooch variant A1

description: &lt;p&gt;This find is registered at Portable Antiquities of the Netherlands with number PAN-00181677&lt;/p&gt;
description: Modified: 2025-10-27T13:33:15+01:00
DOI: 10.15468/dl.m5ugm2
title: Occurrence Download

description: A dataset containing 81 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'BR'
 AND (CAST(occurrence.taxonkey AS INTEGER) = 2906341 OR CAST(occurrence.acceptedtaxonkey AS INTEGER) = 2906341 OR CAST(occurrence.kingdomkey AS INTEGER) = 2906341 OR CAST(occurrence.phylumkey AS INTEGER) = 2906341 OR CAST(occurrence.classkey AS INTEGER) = 2906341 OR CAST(occurrence.orderkey AS INTEGER) = 2906341 OR CAST(occurrence.familykey AS INTEGER) = 2906341 OR CAST(occurrence.genuskey AS INTEGER) = 2906341 OR CAST(occurrence.specieskey AS INTEGER) = 2906341)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 81 records were derived from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038522-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.36507.94246
title: Supp3.pdf
DOI: 10.15468/dl.8sawyg
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Margaretamys christinae",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038560-251120083545085/datasets/export for details.
DOI: 10.13140/rg.2.2.10293.54246
title: Supp1.pdf
DOI: 10.15468/dl.ukn5p9
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Filogranula calyculata",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 52 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038558-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17859443
title: Biomedical Images Dataset

description: This repository contains the data from the manuscript "MaZda versus PyRadiomics – Comparison of the Effectiveness of Texture Feature Estimation in the Context of Classifying Selected Biomedical Images". During data collection, repositories available on the Kaggle and ISIC platforms were used, as well as the authors’ own resources prepared for earlier research. Five datasets containing images recorded using various imaging techniques were prepared. The characteristics of these datasets, including their division into observation classes, were as follows:• chest X-ray images – 2000 images divided into 4 classes (Normal, Covid-19, Viral Pneumonia, Lung Opacity);• lung CT images – 1000 images divided into 2 classes (Non-Covid, Covid-19);• brain MRI images – 2000 images divided into 4 classes (Normal, Glioma Tumor, Meningioma Tumor, Pituitary Tumor);• thyroid ultrasound images – 800 images divided into 2 classes (Normal, Hashimoto’s Disease);• dermoscopic images of skin lesions – 1600 images divided into 4 classes (Nevus, Seborrheic Keratosis, Malignant Melanoma, Basal Cell Carcinoma).

As part of the image pre-processing, cropping and conversion to an 8-bit grayscale format were performed. The image-cropping method, along with the size of the individual crops, is presented in this Figure:

https://drive.google.com/file/d/1d67O_qvC-GMoeJehpp--S6eORA7PQSO2/view?usp=drive_link.

All datasets were randomly divided into training and testing parts (70% and 30% of the full set respectively). In all datasets, the observation classes are balanced (each class contains the same number of samples). The collection of images contained in this repository can be used for testing and comparing methods of texture feature estimation, such as measures based on the gray-level co-occurrence matrix (GLCM), LBP descriptors, or wavelet transform parameters. In addition, they provide a suitable environment for validating image classification algorithms, both traditional ones (K-NN, SVM, decision trees) and those based on deep neural networks. Thanks to the controlled experimental conditions and known class labels, it is possible to objectively compare the effectiveness of individual approaches and optimize model architectures.