cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48544/84be1b59-fd98-4ad4-a223-f482514fe18b
title: Streven naar een robuuste sociale advocatuur? Zet blijvend in op autonome motivatie!
DOI: 10.15468/dl.vpypav
title: Occurrence Download

description: A dataset containing 8485294 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United States of America",
 "GadmGid is USA.2_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 8485294 records from 660 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002953-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.earbyj
title: Occurrence Download

description: A dataset containing 53751 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE",
 "Geometry POLYGON((-100.551 36.917,-71.79 36.917,-71.79 49.612,-100.551 49.612,-100.551 36.917))",
 "Year is greater than or equal to 1970",
 "RecordedBy is one of (barabaradiose, Barbara, Barbara Gawin, Barbara Katzenberg, barbarac99, barbspins, barbthomascall, baronbradley, bauman, Baxter Naday, baya2001, bbfalcon, bbfriedman, bbuzas, bclatt1, bcnorval, bcsmth, bcvilnrotter, bdagley, beccametzler, beckyandsebastian, BeeeH, beepboop, beepie, beetleinahaystack, belby, Beltzville State Park, belyykit, Ben, Ben Borgmann-Winter, Ben Hofmann, Ben Lee, Ben Luukkonen, Ben Nettleton, Ben Pelkey, Ben Redding, Ben Schlusser, Ben Schweinhart, Ben Stubbs, Ben Zerante, ben_gantz, benandkerstyn, benbl, benbreslow, bendingtree, benhall-7, Benigno Veraz, Benjamin Burgunder, Benjamin Hansknecht, Benji Beluga)",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 53751 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002952-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17026/ss/phodzv
title: Interview with Dr. Tatja Scholte, Amsterdam, 17 January 2025

description: Interview with Dr. Tatja Scholte covering her education, career and work in the Instituut Collectie Nederland (ICN), Rijksdienst voor het Cultureel Erfgoed (RCE), Stichting Behoud Moderne Kunst (SBMK) and on European Union (EU) projects. The aim of the interview was to discuss a pivotal time in the formation of Contemporary Art Conservation principles in the Netherlands/European Union. The interview covers Dr. Scholte’s time working at kM magazine that covers material-technical information on art and design, the inception and aspirations for the INCCA (International Network for the Conservation of Contemporary Art) network and the formation, coordination and outcomes of the EU funded project Inside Installations.
description: Interview conducted in the context of the course Oral History and Artwork Life Stories at the University of Amsterdam, an elective as part of the Conservation and Restoration of Cultural Heritage programme.
DOI: 10.5281/zenodo.18554478
title: Multi-omics dataset of individual variations in growth performance of large yellow croaker

description: Integrated metagenomic, transcriptomic, and metabolomic datasets exploring individual variations in growth performance of the large yellow croaker (Larimichthys crocea). Sequencing data and LC–MS/MS raw data are deposited in NCBI (BioProject PRJNA1110616, PRJNA1115810; SRA accession numbers: SRS21275888–SRS21275899; SRR29152265–SRR29152277) and metabolomics data in MetaboLights (MTBLS10000). These datasets enable analysis of gut microbiota composition, host gene expression, and metabolite profiles underlying growth differences.
DOI: 10.15468/dl.dadz47
title: Occurrence Download

description: A dataset containing 177184 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Pyrus calleryana"
 ]
}

 The dataset includes 177184 records from 265 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002955-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18554479
title: Multi-omics dataset of individual variations in growth performance of large yellow croaker

description: Integrated metagenomic, transcriptomic, and metabolomic datasets exploring individual variations in growth performance of the large yellow croaker (Larimichthys crocea). Sequencing data and LC–MS/MS raw data are deposited in NCBI (BioProject PRJNA1110616, PRJNA1115810; SRA accession numbers: SRS21275888–SRS21275899; SRR29152265–SRR29152277) and metabolomics data in MetaboLights (MTBLS10000). These datasets enable analysis of gut microbiota composition, host gene expression, and metabolite profiles underlying growth differences.
DOI: 10.15468/dl.v9bj35
title: Occurrence Download

description: A dataset containing 48 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Geometry POLYGON((-97.50884 19.27785,-97.47452 19.27785,-97.47452 19.29777,-97.50884 19.29777,-97.50884 19.27785))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 48 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002984-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26036/cnp0009007
title: Single-cell sequencing analysis of Echinococcus multilocularis-2

description: Alveolar echinococcosis, caused by Echinococcus multilocularis, leads to high morbidity and mortality rates in humans. This worldwide disease is difficult to diagnose, treat and control. Little is known about the role of tissues of Echinococcus multilocularis in successful parasitism, which limits the development of targeted drugs for alveolar echinococcosis. Using single-cell RNA sequencing, we characterized 15,541 and 32,575 cells from the protoscoleces and the larval vesicles, respectively, and identified 23 distinct cell clusters, including muscle cells , neuronal cells, stem cells, and cells of unknown clusters. The stem cells of Echinococcus multilocularis highly express the CDK1 gene, and we effectively inhibit the growth of the larval vesicles using targeted inhibitors. In summary, these data provide molecular insights into the cellular composition of this important pathogen and identify potential therapeutic targets. This study provides a platform for developing effective treatments and interventions to control alveolar echinococcosis.
DOI: 10.26036/cnp0008990
title: The Raw Data of Amphioctopus aegina

description: Including WGS data, HiFi data, Hi-C data, and transcriptomic data
DOI: 10.15468/dl.ggb8wg
title: Occurrence Download

description: A dataset containing 1498 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Astrebla lappacea"
 ]
}

 The dataset includes 1498 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002982-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17185/duepublico/82148
title: Iterations for active sampling in inelastic neutron scattering

description: We combine Linear Spin Wave Theory with active-learning sampling, resulting in a Kalman Filter enhanced Adversarial Bayesian Optimization (KFABO) algorithm. This algorithm approximates the magnon spectrum using a minimal number of sampling points and iterations. Despite the limited iterations, the algorithm effectively addresses noisy neutron scattering data, providing reliable magnetic interactions that replicate the experimental spectra for 2D CrSBr. It can also reveal hidden or weak interactions, such as those induced by spin-orbit coupling. The attached files illustrate the sampling process during different iteration scenarios. "Theoretical_SPINW_woDMI.gif" shows the iterations for the case including only Heisenberg exchange (J) interactions. "Theoretical_SPINW_wDMI.gif" displays iterations for the case including both Dzyaloshinskii-Moriya interactions (DMI) and Heisenberg exchange interactions. Finally, "Experimental_SPINW_wDMI.gif" represents the iterations during the fitting of the experimental spin wave data.
DOI: 10.15468/dl.wbva2c
title: Occurrence Download

description: A dataset containing 22168 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is TRUE",
 "HasGeospatialIssue is FALSE",
 "Geometry POLYGON((-100.551 36.917,-71.79 36.917,-71.79 49.612,-100.551 49.612,-100.551 36.917))",
 "Year is greater than or equal to 1970",
 "RecordedBy is one of (benmadlinger, bennet, bennett-s, bennyblaze420, Benoit Renaud, benwadejones, Bernard Brown, bernicez, bernsue, Bert Harris, Beth Ann, Beth Brownson BIODIVERSITY/HABITAT UNIT, Peterborough;OFAH - Staff, Beth Johnson, Beth_BIOL151, beth_tracks, bethbrownlee, bethh1902, bethnadal, Betsy McCully, betsytrotzke, Bev Horton, bev435, Beverley Meyers Belmont Lake Cottagers Association;OFAH Staff, bfrankenstei, bg-redoaks, bgnoble, bhai, bheinzen49, bianca0214, bicew, bickel, big_nature_finds, bighenry, bigjohn2468, bigyellowtaxon, Bill Cour, Bill Crins, Bill Hubick, Bill Keim, Bill LaBarre, Bill Lynch, Bill Michalek, Bill Moore, Bill Wolanske, billmacl, Billy Keiper, binc, BiodiversityBuff, biol_rebgiroux, Biologist Dan)",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 22168 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002985-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc1q0wl6
title: CCDC 1579778: Experimental Crystal Structure Determination

description: Related Article: Lianke Wang, Fabián G. Cantú Reinhard, Christian Philouze, Serhiy Demeshko, Sam P. de Visser, Franc Meyer, Marcello Gennari, Carole Duboc|2018|Chem. Sel.|24|11973|doi:10.1002/chem.201801377
description: Related Article:  Lianke Wang, Fabián G. Cantú Reinhard, Christian Philouze, Serhiy Demeshko, Sam P. de Visser, Franc Meyer, Marcello Gennari, Carole Duboc,|2018|Chem.-Eur.J.|24|11973|doi:doi.org/10.1002/chem.201801377
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.18459760
title: PAIR DATASET AND ANNOTATION

description: PAIR: Panofskian Art Interpretation and Retrieval Framework - Datasets and Annotations

This repository contains the datasets and pre-computed annotations for the paper "PAIR: A Panofsky-Inspired Multi-Agent Framework for Art Image Retrieval".

Repository Contents




File
Size
Description




annotation-data.zip
-
Pre-computed multi-agent annotations for all artworks


semart-images-1.zip
-
SemArt dataset images (Part 1)


semart-images-2.zip
-
SemArt dataset images (Part 2)


semart-files.zip
-
SemArt dataset metadata and query files




 

1. Annotation Data (annotation-data.zip)

Pre-computed multi-agent annotations for all artworks in the evaluation datasets.

Contents



Structured annotations following Panofsky's three-level iconographic framework

Global annotations (form, subject, symbolism, cultural context, technical analysis)

Regional annotations with spatial coordinates

Vector embeddings (BGE-large-en-v1.5, 1024 dimensions)


Dataset Scales

Annotations are provided for three evaluation scales:




Dataset
Images
Purpose




data-100
100
Rapid validation


data-1069
1,069
Primary benchmark (complete test set)


data-5000
5,000
Scalability testing




2. SemArt Dataset

The SemArt benchmark is split into three files due to size constraints.

Images



semart-images-1.zip: Artwork images (Part 1)

semart-images-2.zip: Artwork images (Part 2)


Metadata (semart-files.zip)



Image metadata (title, artist, date, type)

Official train/test splits

100 evaluation queries with ground-truth annotations


License

SemArt is released under CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial). See the original dataset page for details.

All experimental datasets are derived from the publicly available SemArt benchmark. The 100 evaluation queries are drawn from SemArt's official test partition, testing iconographic understanding, symbolic interpretation, and cultural context comprehension.

Image Sources: Artwork images in SemArt originate from museum digital collections including the Web Gallery of Art and Wikimedia Commons. Many source images are in the public domain due to artwork age (pre-1900).

3. Data Usage and Copyright

Annotation Outputs

PAIR generates original textual annotations through LLM-based analysis. These annotations constitute derivative scholarly analysis rather than reproduction of copyrighted content. Annotations describe visual elements, interpret symbolic meanings, and provide cultural context—all original analytical text generated by our system.

No Image Reproduction

Our system does not reproduce, modify, or redistribute copyrighted artwork images. During retrieval, the system returns references to original images (URLs) rather than copies. Users access images through their original sources.

Model Outputs

LLM-generated content (annotations and verification reasoning) represents original analytical work. These outputs do not reproduce protected expression from training data but synthesize domain knowledge into new scholarly descriptions.
DOI: 10.5281/zenodo.18210608
title: PAIR DATASET AND ANNOTATION

description: PAIR: Panofskian Art Interpretation and Retrieval Framework - Datasets and Annotations

This repository contains the datasets and pre-computed annotations for the paper "PAIR: A Panofsky-Inspired Multi-Agent Framework for Art Image Retrieval".

Repository Contents




File
Size
Description




annotation-data.zip
-
Pre-computed multi-agent annotations for all artworks


semart-images-1.zip
-
SemArt dataset images (Part 1)


semart-images-2.zip
-
SemArt dataset images (Part 2)


semart-files.zip
-
SemArt dataset metadata and query files




 

1. Annotation Data (annotation-data.zip)

Pre-computed multi-agent annotations for all artworks in the evaluation datasets.

Contents



Structured annotations following Panofsky's three-level iconographic framework

Global annotations (form, subject, symbolism, cultural context, technical analysis)

Regional annotations with spatial coordinates

Vector embeddings (BGE-large-en-v1.5, 1024 dimensions)


Dataset Scales

Annotations are provided for three evaluation scales:




Dataset
Images
Purpose




data-100
100
Rapid validation


data-1069
1,069
Primary benchmark (complete test set)


data-5000
5,000
Scalability testing




2. SemArt Dataset

The SemArt benchmark is split into three files due to size constraints.

Images



semart-images-1.zip: Artwork images (Part 1)

semart-images-2.zip: Artwork images (Part 2)


Metadata (semart-files.zip)



Image metadata (title, artist, date, type)

Official train/test splits

100 evaluation queries with ground-truth annotations


License

SemArt is released under CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial). See the original dataset page for details.

All experimental datasets are derived from the publicly available SemArt benchmark. The 100 evaluation queries are drawn from SemArt's official test partition, testing iconographic understanding, symbolic interpretation, and cultural context comprehension.

Image Sources: Artwork images in SemArt originate from museum digital collections including the Web Gallery of Art and Wikimedia Commons. Many source images are in the public domain due to artwork age (pre-1900).

3. Data Usage and Copyright

Annotation Outputs

PAIR generates original textual annotations through LLM-based analysis. These annotations constitute derivative scholarly analysis rather than reproduction of copyrighted content. Annotations describe visual elements, interpret symbolic meanings, and provide cultural context—all original analytical text generated by our system.

No Image Reproduction

Our system does not reproduce, modify, or redistribute copyrighted artwork images. During retrieval, the system returns references to original images (URLs) rather than copies. Users access images through their original sources.

Model Outputs

LLM-generated content (annotations and verification reasoning) represents original analytical work. These outputs do not reproduce protected expression from training data but synthesize domain knowledge into new scholarly descriptions.
DOI: 10.5522/04/31289227
title: Health expenditure in 14 LMIC megacities and their respective countries (fiscal year 2026)

description: This dataset was prepared to support a comparative descriptive analysis of municipal health expenditure across 14 megacities in low- and middle-income countries (LMICs). It compiles city-level population estimates and publicly reported fiscal figures for total annual expenditure and annual health expenditure, and derives two harmonised indicators: health expenditure as a share of total expenditure (%) and health expenditure per capita (USD per person). Financial data were extracted from official municipal, provincial/state, and national public finance documents and reports, with full traceable sources provided. Population estimates use UN DESA World Urbanization Prospects (urban agglomerations) and UN World Population Prospects. Currency conversions use IMF monthly average exchange rates for the relevant fiscal year.
DOI: 10.5522/04/31289227.v1
title: Health expenditure in 14 LMIC megacities and their respective countries (fiscal year 2026)

description: This dataset was prepared to support a comparative descriptive analysis of municipal health expenditure across 14 megacities in low- and middle-income countries (LMICs). It compiles city-level population estimates and publicly reported fiscal figures for total annual expenditure and annual health expenditure, and derives two harmonised indicators: health expenditure as a share of total expenditure (%) and health expenditure per capita (USD per person). Financial data were extracted from official municipal, provincial/state, and national public finance documents and reports, with full traceable sources provided. Population estimates use UN DESA World Urbanization Prospects (urban agglomerations) and UN World Population Prospects. Currency conversions use IMF monthly average exchange rates for the relevant fiscal year.
DOI: 10.15468/eq3tgm
title: A new species of Primula (Primulaceae) from Sikkim Himalaya, India

description: This dataset contains the digitized treatments in Plazi based on the original journal article Lepcha, Dharmit, Chettri, Arun, Singh, Harsh (2025): A new species of Primula (Primulaceae) from Sikkim Himalaya, India. Phytotaxa 732 (1): 83-90, DOI: 10.11646/phytotaxa.732.1.8, URL: https://doi.org/10.11646/phytotaxa.732.1.8AbstractPrimula lepcha, a new species from Naga valley, North-Sikkim is described and illustrated. The new species closely resembles with P. bhutanica, P. whitei, and P. bracteosa, but it differs markedly in several floral and vegetative characters, including its efarinose nature of plant, the presence of both homostylous and heterostylous floral conditions, shorter scape, distinct bract shape and length, irregular calyx margins, ex-annulate corolla, and smaller stamens in both pin and thrum flowers. A detailed description, information on distribution and phenology, a comparative table, and colour photographs of its natural habitat are also provided.
DOI: 10.11583/dtu.29488202
title: OCT images for the paper "Assessing changes in ultraviolet radiation-exposed mouse skin using optical coherence tomography"

description: This repository contains the raw structural OCT images associated with the manuscript "Assessing changes in ultraviolet radiation-exposed mouse skin using optical coherence tomography." The data is organized into folders by the measurement timepoints. Within each of these folders is a subfolder for each treatment group. Each mouse was imaged at 3 locations: on the back, the side, and the stomach.
DOI: 10.11583/dtu.29488202.v1
title: OCT images for the paper "Assessing changes in ultraviolet radiation-exposed mouse skin using optical coherence tomography"

description: This repository contains the raw structural OCT images associated with the manuscript "Assessing changes in ultraviolet radiation-exposed mouse skin using optical coherence tomography." The data is organized into folders by the measurement timepoints. Within each of these folders is a subfolder for each treatment group. Each mouse was imaged at 3 locations: on the back, the side, and the stomach.
DOI: 10.15468/dl.yqx3ax
title: Occurrence Download

description: A dataset containing 145128 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Halyomorpha halys",
 "Year 1000-2025"
 ]
}

 The dataset includes 145128 records from 327 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002930-260208012135463/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18541166
title: Novice-Friendly Guided Teleportation for Exploring Knowledge Spaces in Virtual Reality [Supplemental Material]

description: Unity project and user study data as reported in the paper "Novice-Friendly Guided Teleportation for Exploring Knowledge Spaces in Virtual Reality"
DOI: 10.5281/zenodo.18541165
title: Novice-Friendly Guided Teleportation for Exploring Knowledge Spaces in Virtual Reality [Supplemental Material]

description: Unity project and user study data as reported in the paper "Novice-Friendly Guided Teleportation for Exploring Knowledge Spaces in Virtual Reality"
DOI: 10.5281/zenodo.18098523
title: Analysis Scripts and Datasets for a Longitudinal Study on Yoga Nidra

description: This repository contains the Python scripts, Jupyter notebooks, and datasets for a longitudinal study comparing a Yoga Nidra intervention group (YN) with a waitlist control group (WC).

The repository includes:

• Raw and processed datasets used in the study  • Statistical analysis notebooks for demographic, parametric, and non-parametric testing  • Per-protocol sensitivity analyses  • Additional subgroup and robustness analyses  

Analyses cover clinical outcomes (PSQI, PSS, GAD-7, PHQ-9, POMS, SWLS) and cognitive measures (N-back tasks, Trail Making Test).

This Version 2 update includes:• Per-protocol (PP) analyses  • Additional statistical checks  • Updated notebooks and documentation  

To reproduce results:Keep CSV data files and notebooks in the same directory and run the notebooks sequentially.

Required libraries include:pandas, numpy, scipy, and tabulate.