cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/pbj-kj8-djd
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/p8m-8xa-nb7
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/z5z-tyj-c31
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.us8hc3
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphanus sativus",
 "Country is Bosnia and Herzegovina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024267-250811113504898/datasets/export for details.
DOI: 10.3535/8cp-79j-khb
title: Cytheridea (Cytheridea) Bosquet, 1852

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/961-96k-y50
title: Amphibia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/99t-gzs-k98
title: Procerolagena distoma (Parker & Jones, 1864)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/fya-sae-hch
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/mrk-x05-vpm
title: Heterostegina depressa d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/rxc-39h-g06
title: Triloculina laevigata d'Orbigny in Terquem, 1878

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.5281/zenodo.16904140
title: Sources of Uncertainty in Quantum and Classical Measurement Dataset

description: This dataset consists of participants' natural language responses to a series of questions on the Measurement Survey, a Physics Education Research assessment survey that studies physics students’ thinking about sources of measurement uncertainty across experimental contexts, including classical and quantum mechanics contexts. We consider this dataset to be especially useful for evaluating and comparing different multiclass classification machine learning techniques for two reasons: i) the text responses are well segmented into distinct ideas due to the structure of the survey question, and ii) the coding scheme applied to the data is mutually exclusive, presenting a true multiclass problem for machine learning. 

The format of the survey is as follows: first, the survey presents an experimental context, then, the survey prompts participants to answer questions in the context of that experimental context. The responses in this dataset come from the first version of the Measurement Survey which consisted of four experimental contexts: Projectile Motion (PM), Brownian Motion (BM), Stern Gerlach (SG), and Single Slit (SS). Each experimental context included a text description, a diagram of the experiment, and a histogram of fictitious experimental results. 

For each experiment, participants were asked to generate a list of sources of uncertainty in response to the prompt: “What is causing the shape of the distribution? List as many causes as you can think of.” The data are presented in long format, where each row represents an item in the lists of sources of uncertainty generated by participants. The Response Id corresponds to each unique participant who responded to the survey, therefore, rows with the same Response Id represent multiple sources of uncertainty listed by the same participant. 

Responses were coded by the research team based on an emergent coding scheme with four categories defined as follows: 

Limitations (L): Reasoning that uncertainty arises from an inability to perfectly measure and model all aspects of a real-world experiment.

Physical Principles (P): Reasoning that uncertainty is inherent in the theoretical abstraction of an experiment. 

Statistics (S): Reasoning that uncertainty is inherent to the nature of experiments and repeating trials. 

Other (O): Non-empty responses that are vague or do not fall into one of the other three codes. 

The dataset is multi-institutional and was collected over multiple semesters. For more details about data collection and the demographics of participants, see the journal articles listed under related works or contact the creators.
DOI: 10.3535/tr4-2v1-qzp
title: Lobatula wuellerstorfi (Schwager, 1866)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.2xhk7a
title: Occurrence Download

description: A dataset containing 104 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Raphanus sativus",
 "Country is Brazil",
 "HasCoordinate is true"
 ]
}

 The dataset includes 104 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024268-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/hpa-b0s-k5g
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/td5-kcx-243
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/9qy-e26-91q
title: Amphistegina radiata (Fichtel & Moll, 1798)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.25549/inscriptifact-ouc110820419
title: Persepolis Fortification Elamite Tablet 2267.101, Fort 2267.101

description: [Text Description:] Administrative text with seal ❧ [Text or Publication Number Note:] Fort 2267.101 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. Seal impression on right edge. ❧ [Physical Object Note:] Left side of tablet missing.
DOI: 10.25549/inscriptifact-ouc110820381
title: Persepolis Fortification Elamite Tablet 2272.101, Fort 2272.101

description: [Text Description:] Administrative text ❧ [Text or Publication Number Note:] Fort 2272.101 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. ❧ [Physical Object Note:] Upper left, upper right and lower right corners broken off. Damage on obverse, reverse.
DOI: 10.25549/inscriptifact-ouc110820693
title: Persepolis Fortification Elamite Tablet 2272.102, Fort 2272.102

description: [Text Description:] Administrative text ❧ [Text or Publication Number Note:] Fort 2272.102 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. ❧ [Physical Object Note:] Borken right edge, upper edge, most of left edge.
DOI: 10.3886/e240204
title: Drainage Basins Used for Assessing Trends in Concentration of Pesticides in Streams of the United States, 1992-2010

description: This dataset consists of drainage basin boundaries for 212 U.S. Geological Survey (USGS) stream sites sampled in the National Water-Quality Assessment (NAWQA) Program, the National Stream Quality Accounting Network (NASQAN), and the National Monitoring Network (NMN). Of the 212 sites, 206 have either a contributing or total drainage basin boundary, and the remaining 6 have both a total drainage basin boundary and a smaller contributing basin boundary. Collectively, these 218 basin boundaries have been used in a geographic information system (GIS) to generate basin characteristics for the assessment of trends in concentrations of pesticides streams of the United States.<br><br>Related report: https://pubs.usgs.gov/ds/655/
description: drainage basin boundaries for 212 U.S. Geological Survey (USGS) stream sites.
description: Date downloaded: 2025-11-12
DOI: 10.3886/e240204v1
title: Drainage Basins Used for Assessing Trends in Concentration of Pesticides in Streams of the United States, 1992-2010

description: This dataset consists of drainage basin boundaries for 212 U.S. Geological Survey (USGS) stream sites sampled in the National Water-Quality Assessment (NAWQA) Program, the National Stream Quality Accounting Network (NASQAN), and the National Monitoring Network (NMN). Of the 212 sites, 206 have either a contributing or total drainage basin boundary, and the remaining 6 have both a total drainage basin boundary and a smaller contributing basin boundary. Collectively, these 218 basin boundaries have been used in a geographic information system (GIS) to generate basin characteristics for the assessment of trends in concentrations of pesticides streams of the United States.<br><br>Related report: https://pubs.usgs.gov/ds/655/
description: drainage basin boundaries for 212 U.S. Geological Survey (USGS) stream sites.
description: Date downloaded: 2025-11-12
DOI: 10.25549/inscriptifact-ouc110820602
title: Persepolis Fortification Elamite Tablet 2267.101, Fort 2267.101

description: [Text Description:] Administrative text with seal ❧ [Text or Publication Number Note:] Fort 2267.101 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. Seal impression on right edge. ❧ [Physical Object Note:] Left side of tablet missing.
DOI: 10.25549/inscriptifact-ouc110820648
title: Persepolis Fortification Elamite Tablet 2272.102, Fort 2272.102

description: [Text Description:] Administrative text ❧ [Text or Publication Number Note:] Fort 2272.102 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. ❧ [Physical Object Note:] Borken right edge, upper edge, most of left edge.
DOI: 10.15468/dl.v22p6j
title: Occurrence Download

description: A dataset containing 207 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is one of (USA.41_1, USA.34_1, USA.11_1, USA.1_1, USA.47_1, USA.49_1, USA.43_1)",
 "TaxonKey is Spilogale putorius"
 ]
}

 The dataset includes 207 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029356-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25549/inscriptifact-ouc110820591
title: Persepolis Fortification Elamite Tablet 2267.101, Fort 2267.101

description: [Text Description:] Administrative text with seal ❧ [Text or Publication Number Note:] Fort 2267.101 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. Seal impression on right edge. ❧ [Physical Object Note:] Left side of tablet missing.
DOI: 10.25549/inscriptifact-ouc110820598
title: Persepolis Fortification Elamite Tablet 2267.101, Fort 2267.101

description: [Text Description:] Administrative text with seal ❧ [Text or Publication Number Note:] Fort 2267.101 ❧ [Excavation Description:] Found during Oriental Institute's excavations in Spring, 1933, near the northeastern corner of the stone platform of Persepolis, in two small rooms of a bastion in the fortification wall ❧ [Medium:] Clay ❧ [Script Note:] Non-Alphabetic Cuneiform ❧ [Physical Object Description:] Clay tablet with cuneiform text. Seal impression on right edge. ❧ [Physical Object Note:] Left side of tablet missing.
DOI: 10.15468/dl.vtw5b5
title: Occurrence Download

description: A dataset containing 169 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Hipposideros pratti Thomas, 1891"
 ]
}

 The dataset includes 169 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009225-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.29107511
title: Supplementary information files for "Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset"

description: Supplementary files for article "Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset"<br><br>Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries. The data were collected between November 2022 and August 2023 as part of the global Many Labs study “Trust in Science and Science-Related Populism” (TISP). The questionnaire contained comprehensive measures for individuals’ trust in scientists, science-related populist attitudes, perceptions of the role of science in society, science media use and communication behaviour, attitudes to climate change and support for environmental policies, personality traits, political and religious views and demographic characteristics. Here, we describe the dataset, survey materials and psychometric properties of key variables. We encourage researchers to use this unique dataset for global comparative analyses on public perceptions of science and its role in society and policy-making.<br><br>©The Author(s), CC BY 4.0
DOI: 10.17028/rd.lboro.29107511.v1
title: Supplementary information files for "Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset"

description: Supplementary files for article "Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset"<br><br>Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries. The data were collected between November 2022 and August 2023 as part of the global Many Labs study “Trust in Science and Science-Related Populism” (TISP). The questionnaire contained comprehensive measures for individuals’ trust in scientists, science-related populist attitudes, perceptions of the role of science in society, science media use and communication behaviour, attitudes to climate change and support for environmental policies, personality traits, political and religious views and demographic characteristics. Here, we describe the dataset, survey materials and psychometric properties of key variables. We encourage researchers to use this unique dataset for global comparative analyses on public perceptions of science and its role in society and policy-making.<br><br>©The Author(s), CC BY 4.0
DOI: 10.15468/dl.mm4p5f
title: Occurrence Download

description: A dataset containing 2219 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is FRA.3.3_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Capreolus capreolus (Linnaeus, 1758)"
 ]
}

 The dataset includes 2219 records from 38 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009226-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sjum6w
title: Occurrence Download

description: A dataset containing 2395 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is 成龍溼地魚類生態紀錄"
 ]
}

 The dataset includes 2395 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048665-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57967/hf/5270
title: dmp-qa-with-context
DOI: 10.5281/zenodo.15298992
title: Detecting Parkinson's Disease Using Vocal Features

description: The report explores using machine learning to predict Parkinson’s Disease based on vocal features, aiming for non-invasive early diagnosis.It details preprocessing steps like handling class imbalance with SMOTE and standardizing features, followed by EDA revealing key vocal differences in patients.Multiple models (Random Forest, SVC, Gradient Boosting) were evaluated, with Random Forest achieving the highest accuracy (94%) and performance metrics.Findings highlight vocal frequency and amplitude variations as critical predictors, supported by visualizations like boxplots and correlation heatmaps. https://github.com/alihassan098799/datastewardship_1
DOI: 10.5281/zenodo.15298993
title: Detecting Parkinson's Disease Using Vocal Features

description: The report explores using machine learning to predict Parkinson’s Disease based on vocal features, aiming for non-invasive early diagnosis.It details preprocessing steps like handling class imbalance with SMOTE and standardizing features, followed by EDA revealing key vocal differences in patients.Multiple models (Random Forest, SVC, Gradient Boosting) were evaluated, with Random Forest achieving the highest accuracy (94%) and performance metrics.Findings highlight vocal frequency and amplitude variations as critical predictors, supported by visualizations like boxplots and correlation heatmaps. https://github.com/alihassan098799/datastewardship_1
DOI: 10.25550/7x-hzda
title: MicroCT analysis of Ambn-IRESCre mouse models

description: The enamel of 8-week-old _Ambn-IREScre^+/-^, Ambn-IREScre^+/+^_ mouse incisor enamel was examined by microCT
DOI: 10.25550/7x-hzec
title: Determination of Cre-recombinase activity in Ambn-IRESCre mouse model

description: Using β-galactosidase (LacZ) staining, we analyzed the spatiotemporal expre_emphasized text_ssion of Cre-recombinase in newly established _Ambn-IRESCre_ mouse driver lines.
DOI: 10.15468/dl.qbv852
title: Occurrence Download

description: A dataset containing 48868774 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "DatasetKey is iNaturalist Research-grade Observations",
 "Year 2005-2025"
 ]
}

 The dataset includes 48868774 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009223-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jg3avr
title: Occurrence Download

description: A dataset containing 120 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Gortyna borelii lunata",
 "HasCoordinate is true"
 ]
}

 The dataset includes 120 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0046130-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17654339
title: Flickr: USGS Bee Inventory and Monitoring Lab

description: https://www.flickr.com/photos/usgsbiml/ The USGS Native Bee Inventory and Monitoring Program designs and develops large and small scale surveys for native bees. As part of that program we also develop identification tools and keys for native bee species. One aspect of creating those tools is creating accurate and detailed pictures of native bees and the plants and insects they interact with. This site is designed to provide easy access to our photographs so that they may be freely used. There is no need to ask for our permission for any use of these photographs. You can download the original version directly from Flickr at your convenience. 
Please contact Sam Droege for further information at sdroege@usgs.gov or or 301-497-5840 or visit our website at: www.pwrc.usgs.gov/nativebees/ Photos were taken with a system developed by Dr. Anthony G Gutierrez (Tony.Gutierrez@us.army.mil) and taken by Brooke Alexander, Sue Boo, Heagan Ahmed and Sierra Williams. A how to manual for taking similar pictures is available a (note the url is very long and you have to use the shift and arrow key to highlight the whole thing): ftp://ftpext.usgs.gov/pub/er/md/laurel/Droege/How to Take MacroPhotographs of Insects BIML Lab2.pdf Posts do not = endorsement: on.doi.gov/pgwu0Y 
Follow us on instagram: @usgsbiml 
https://eol-jira.bibalex.org/browse/DATA-1855
DOI: 10.5281/zenodo.17654348
title: Flickr: USGS Bee Inventory and Monitoring Lab

description: https://www.flickr.com/photos/usgsbiml/ The USGS Native Bee Inventory and Monitoring Program designs and develops large and small scale surveys for native bees. As part of that program we also develop identification tools and keys for native bee species. One aspect of creating those tools is creating accurate and detailed pictures of native bees and the plants and insects they interact with. This site is designed to provide easy access to our photographs so that they may be freely used. There is no need to ask for our permission for any use of these photographs. You can download the original version directly from Flickr at your convenience. 
Please contact Sam Droege for further information at sdroege@usgs.gov or or 301-497-5840 or visit our website at: www.pwrc.usgs.gov/nativebees/ Photos were taken with a system developed by Dr. Anthony G Gutierrez (Tony.Gutierrez@us.army.mil) and taken by Brooke Alexander, Sue Boo, Heagan Ahmed and Sierra Williams. A how to manual for taking similar pictures is available a (note the url is very long and you have to use the shift and arrow key to highlight the whole thing): ftp://ftpext.usgs.gov/pub/er/md/laurel/Droege/How to Take MacroPhotographs of Insects BIML Lab2.pdf Posts do not = endorsement: on.doi.gov/pgwu0Y 
Follow us on instagram: @usgsbiml 
https://eol-jira.bibalex.org/browse/DATA-1855
DOI: 10.15468/cmazb4
title: Carl L. Hubbs collection at LACM

description: <b>Carl L. </b><b>Hubbs </b>(1894-1979) was an Arizona-born, Stanford-educated ichthyologist, who became professor of biology at Scripps Institution of Oceanography (SIO) and was instrumental in building the SIO fish collections. He collected these marine invertebrates off of California and Baja California between 1945–1950.