cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3535/maq-ge7-k82
title: †Lepidorbitoides Silvestri, 1907

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/2bg-kva-nnx
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/smf-zsa-243
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/321-fqt-d8j
title: Sahulia kerimbaensis (Said, 1949)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/t2v-khm-34j
title: Mollusca

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/1zf-mjx-98w
title: †Lepidocyclina Gümbel, 1870

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/8l2-t53-bc2
title: Planorbulinella Cushman, 1927

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/xtt-xgm-24n
title: Echinodermata

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/63j-s84-a1g
title: Pullenia Parker & Jones in Carpenter et al., 1862

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/wng-qhy-nac
title: Pullenia Parker & Jones in Carpenter et al., 1862

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/85m-af8-jct
title: Cytherura Sars, 1866

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/92z-68n-9rz
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/659-rm3-x7l
title: Peneroplis Montfort, 1808

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/z5s-41l-ezx
title: Obelus W. Hartmann, 1842

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/ax8-1fa-gf5
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/wd6-n6h-0kd
title: †Cibicides excavatus Brotzen, 1936

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/cq4-gwq-r6g
title: Mammalia Linnaeus, 1758

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/17c-jzr-nas
title: Cytherura Sars, 1866

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/37c-pcj-wb4
title: Foraminifera d'Orbigny, 1826

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.vymm4h
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erigeron bonariensis",
 "Country is Romania",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020865-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/8zj-ffe-6pd
title: †Lepidorbitoides Silvestri, 1907

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/t22-3js-j8t
title: Ostracoda Latreille, 1802

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/h06-826-fsq
title: †Gyroidinoides nitida (Reuss, 1844)

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.3535/qjs-n2e-n85
title: Animalia

description: Digital Specimen for the physical specimen hosted at Naturalis Biodiversity Center.
DOI: 10.15468/dl.x5wg3e
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061211-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pngfwj
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001991-180920211646547/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fusevw
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001962-180920211646547/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hvl2cc
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0092416-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vlai0v
title: Occurrence Download

description: A dataset containing 1450263389 species occurrences available in GBIF matching the query:
{ }

 The dataset includes 1450263389 records from 17385 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000848-170826194755519/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15530926
title: A cell type in the visual system that receives feedback about limb movement

description: Imaging and behavioral data used in "A cell type in the visual system that receives feedback about limb movement" by Hartman et al. (Current Biology, 2025)
DOI: 10.5281/zenodo.15530927
title: A cell type in the visual system that receives feedback about limb movement

description: Imaging and behavioral data used in "A cell type in the visual system that receives feedback about limb movement" by Hartman et al. (Current Biology, 2025)
DOI: 10.15468/dl.4yaa29
title: Occurrence Download

description: A dataset containing 1038438 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Museums Victoria provider for OZCAM"
 ]
}

 The dataset includes 1038438 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004105-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.puxhm6
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dolichandra unguis-cati",
 "Country is Guatemala",
 "HasCoordinate is true"
 ]
}

 The dataset includes 20 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079299-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14528302
title: YouTube Earnings Data (YED) 2023

description: The dataset and R-scripts to replicate the results of the following paper: Verwiebe, Krauter, Fritsch, Weißmann, Philipp, Buder (2025): Working on an algorithm-controlled platform as a content creator: What explains unequal earnings on YouTube?
DOI: 10.5281/zenodo.14528303
title: YouTube Earnings Data (YED) 2023

description: The dataset and R-scripts to replicate the results of the following paper: Verwiebe, Krauter, Fritsch, Weißmann, Philipp, Buder (2025): Working on an algorithm-controlled platform as a content creator: What explains unequal earnings on YouTube?
DOI: 10.15468/dl.93mcgb
title: Occurrence Download

description: A dataset containing 316023 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "BasisOfRecord is one of (Human Observation, Machine Observation, Occurrence evidence, Observation)",
 "TaxonKey is one of (Rupicapra rupicapra)",
 "Country is one of (Åland Islands, Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See, Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Republic of, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, Russian Federation, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom of Great Britain and Northern Ireland)"
 ]
}

 The dataset includes 316023 records from 248 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079281-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.55kw38
title: Occurrence Download

description: A dataset containing 19 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dolichandra unguis-cati",
 "Country is France",
 "HasCoordinate is true"
 ]
}

 The dataset includes 19 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0079298-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17044/scilifelab.27368322
title: Frequent longitudinal blood microsampling and proteome monitoring identify disease markers and enable timely intervention in a mouse model of type 1 diabetes

description: <b>The work has been published as </b><b>Parajuli et al. (2025) Diabetologia</b><b> </b>Frequent self-sampling of blood has the potential to identify early, disease-predictive markers, including proteins. In a study to test this hypothesis, we conducted regular microsampling of a mouse model over 14 days and monitored their molecular response to a type 1 diabetes (T1D)-associated virus.This longitudinal approach involved the collection of dried blood samples, which were subsequently analysed for 92 circulating proteins. The data revealed <b>transient molecular changes</b> in the virus-infected mice. Utilising machine learning techniques, we achieved a <b>prediction accuracy of over 90%</b> for infection status after day 2 post-infection. This high level of accuracy enabled timely treatment interventions with immune serum, which could potentially prevent the onset of diabetes in the infected animals.The data of this study underscores the utility of <b>frequent blood microsampling</b><b> </b>as a method for monitoring disease progression during the pre-symptomatic phase, allowing for prompt medical interventions of immune-mediated inflammatory diseases, including T1D.Description of data files:<b>Mouse DBS_Batch 1_ProtPQN data_rmd1021.csv</b>: <i>ProtPQN normalised NPX values for Study batch 1. The signals are in log2-scale. All columns not described below contain protein </i>measurements.<b>Mouse DBS_Batch 2_ProtPQN data.csv</b>: <i>ProtPQN normalised NPX values for Study batch 2. The signals are in log2-scale. All columns not described below contain protein measurements.</i><b>zscore_data_combined.csv</b>:<i> Z</i>-<i>score transformed measurements for both studies. All columns not described below contain protein measurements.</i><b>sample information study batch 1 and 2.csv</b>: <i>Sample information for all of the mice.</i><b>Mouse DBS_NPX_below LOD.xlsx</b><i>; Raw data from Olink Signature NPX software for Study batch 1. Values are reported as NPX values and are in log2-scale. This file contains values for limit of detection (LOD) per protein.</i><b>Mouse DBS Plate 2_NPX_belowLOD.xlsx</b>: <i>Raw data from Olink Signature NPX software for Study batch 2. Values are reported as NPX values and are in log2-scale. This file contains values for limit of detection (LOD) per protein</i>
DOI: 10.17044/scilifelab.27368322.v1
title: Frequent longitudinal blood microsampling and proteome monitoring identify disease markers and enable timely intervention in a mouse model of type 1 diabetes

description: <b>The work has been published as </b><b>Parajuli et al. (2025) Diabetologia</b><b> </b>Frequent self-sampling of blood has the potential to identify early, disease-predictive markers, including proteins. In a study to test this hypothesis, we conducted regular microsampling of a mouse model over 14 days and monitored their molecular response to a type 1 diabetes (T1D)-associated virus.This longitudinal approach involved the collection of dried blood samples, which were subsequently analysed for 92 circulating proteins. The data revealed <b>transient molecular changes</b> in the virus-infected mice. Utilising machine learning techniques, we achieved a <b>prediction accuracy of over 90%</b> for infection status after day 2 post-infection. This high level of accuracy enabled timely treatment interventions with immune serum, which could potentially prevent the onset of diabetes in the infected animals.The data of this study underscores the utility of <b>frequent blood microsampling</b><b> </b>as a method for monitoring disease progression during the pre-symptomatic phase, allowing for prompt medical interventions of immune-mediated inflammatory diseases, including T1D.Description of data files:<b>Mouse DBS_Batch 1_ProtPQN data_rmd1021.csv</b>: <i>ProtPQN normalised NPX values for Study batch 1. The signals are in log2-scale. All columns not described below contain protein </i>measurements.<b>Mouse DBS_Batch 2_ProtPQN data.csv</b>: <i>ProtPQN normalised NPX values for Study batch 2. The signals are in log2-scale. All columns not described below contain protein measurements.</i><b>zscore_data_combined.csv</b>:<i> Z</i>-<i>score transformed measurements for both studies. All columns not described below contain protein measurements.</i><b>sample information study batch 1 and 2.csv</b>: <i>Sample information for all of the mice.</i><b>Mouse DBS_NPX_below LOD.xlsx</b><i>; Raw data from Olink Signature NPX software for Study batch 1. Values are reported as NPX values and are in log2-scale. This file contains values for limit of detection (LOD) per protein.</i><b>Mouse DBS Plate 2_NPX_belowLOD.xlsx</b>: <i>Raw data from Olink Signature NPX software for Study batch 2. Values are reported as NPX values and are in log2-scale. This file contains values for limit of detection (LOD) per protein</i>
DOI: 10.25549/inscriptifact-ouc1sto1611999
title: InscriptiFact -- an image database of inscriptions and artifacts

description: The InscriptiFact Collection is designed to allow access via the Internet to high-resolution images of ancient inscriptions and artifacts, primarily from the Near Eastern and Mediterranean Worlds. The targeted inscriptions constitute some of the world’s earliest written records, which are mostly housed in a number of international museums and libraries, as well as field projects where inscriptions still remain in situ. Included, for example, are, selected Dead Sea Scrolls; cuneiform tablets from Mesopotamia, Persia, Canaan and Egypt; early Jewish papyri from Egypt; lapidary inscriptions, primarily from Jordan, Lebanon and Cyprus; inscriptions on a variety of hard media (e.g., ostraca, copper, semi-precious stones, jar handles) mostly written in early Canaanite, Phoenician, Hebrew, Aramaic, Ammonite and Edomite; and much more. These ancient texts are foundational documents that serve as a point of reference for Judaism, Christianity, Islam and the cultures out of which they emerged. The name "InscriptiFact" is intended to convey the concept of a scholarly archive based on "facts" about "inscriptions" and "artifacts." West Semitic Research Project (WSRP) under the auspices of the University of Southern California (USC) is broadly acknowledged as a leader in the application of photographic and digital technologies to capture and analyze data of ancient texts. The West Semitic Research image archive now contains approximately 1,500,000 images. Important! Search terms with more than one word or number need to be enclosed in quotation marks.Guide to Searching InscriptiFact
DOI: 10.25549/inscriptifact-ouc110623496
title: Persepolis Fortification Anepigraphic Tablet 0878.201, PFAnep 0878.201

description: [Text Description:] Administrative text with seals ❧ [Text or Publication Number Note:] PFAnep 0878.201, PFUT 0878-201 ❧ [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-Text ❧ [Physical Object Description:] Clay tablet with seal impressions on bottom edge, obverse, reverse, upper edge. ❧ [Physical Object Note:] Some abrasion on left edge, small crack on upper edge, right edge. Chips on right side of obverse.
DOI: 10.15156/bio/sh1838617.10fu
title: SH1838617.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1838629.10fu
title: SH1838629.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1838747.10fu
title: SH1838747.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.3hrub4
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Desmodium tortuosum",
 "Country is Fiji",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0087374-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ymcfna
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Desmodium tortuosum",
 "Country is Micronesia (Federated States of)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 2 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0087373-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e210045
title: Data and Code for: Quantifying Threshold Manipulation in the Presence of Rounding: The Case of Lead Monitoring in US Drinking Water

description: Replication code and data for "Quantifying Threshold Manipulation in the Presence of Rounding: The Case of Lead Monitoring in US Drinking Water" by Tihitina Andarge, Dalia Ghanem, David A. Keiser, and Gabriel E. Lade.<br><br>Below is the abstract of the paper:<br><br>Many laws and economic actions depend on thresholds. As a consequence, threshold manipulation is a common concern in a variety of settings. Existing methods for detecting and quantifying threshold manipulation assume a continuous counterfactual distribution absent manipulation. This assumption is violated in the presence of rounding, which is prevalent in many applications and distinct from manipulation. This paper develops methods for testing and quantifying threshold manipulation when rounding is a prominent feature of the data. We demonstrate the usefulness of our approach in an empirical application examining threshold manipulation in lead monitoring under the US Safe Drinking Water Act.<br>