cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17301275
title: COVID-ARE-Konsultationsinzidenz

description: Im Datensatz "COVID-ARE-Konsultationsinzidenz" des Robert Koch-Instituts werden wöchentliche Inzidenzen von ambulanten Konsultationen mit akuter respiratorischer Erkrankung (ARE) und zusätzlicher COVID-19-Diagnose in Deutschland bereitgestellt. Über das syndromische Surveillance-Modul SEED-ARE werden aus Sentinelpraxen Daten von gesetzlich versicherten Patientinnen und Patienten mit einer akuten Atemwegserkrankung inklusive der jeweiligen ICD-10-Diagnosecodes elektronisch übermittelt. Die COVID-ARE-Konsultationsinzidenz wird pro 100.000 Einwohner und nach Altersgruppen ausgewiesen. Der Datensatz ermöglicht eine zeitnahe Einschätzung der Krankheitslast und unterstützt evidenzbasierte Entscheidungen im Infektionsgeschehen mit COVID-19.
DOI: 10.15468/dl.wtm3dc
title: Occurrence Download

description: A dataset containing 1303 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Salmo marmoratus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1303 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064322-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.u6ppzb
title: Occurrence Download

description: A dataset containing 10894 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-90 -60,-60 -60,-60 -30,-90 -30,-90 -60))"
 ]
}

 The dataset includes 10894 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064323-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.efe5n4
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sidalcea malviflora",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 90 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064325-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7488/ds/8028
title: 2025 Into the Light Index on Global Child Sexual Exploitation and Abuse

description: This dataset is the collection of dataframes that, when taken together, comprise the Childlight 2025 Into the Light Index on Global Child Sexual Exploitation and Abuse. This includes dataframes across three indicator areas: 1. Victimisation (offline and technology facilitated CSEA), 2. Frontline data (policing), and 3. Child sexual abuse material. README files accompany the dataframes for additional context. The overall synthesis of data, including a Supplemental Thematic Analysis Report and Technical Note, can be found on Childlight’s website at https://www.childlight.org/intothelight/ . Permission to copy, disseminate or otherwise use information from the 2025 edition of the Into the Light Index on Global Child Sexual Exploitation and Abuse is granted, so long as appropriate acknowledgement and citation is given.
DOI: 10.5281/zenodo.13879662
title: BrainSTEM: A multi-resolution fetal brain atlas to assess the fidelity of human midbrain cultures

description: This upload contains data objects associated with our paper "BrainSTEM: A multi-resolution fetal brain atlas to assess the fidelity of human midbrain cultures".

In particular, this upload contains four single-cell atlases as R object files:

1) fetalWholeBrainAtlas.noRNA.rds: the fetal whole brain atlas (RNA assay removed to reduce the size)

2) fetalMidBrainAtlas.noRNA.rds: the fetal midbrain atlas (RNA assay removed to reduce the size)

3) fetalWholebrainAtlas.noRNA.mini.rds: the downsampled fetal whole brain atlas (10% cells from 1)

4) fetalMidbrainAtlas.noRNA.mini.rds: the downsampled fetal midbrain atlas (10% cells from 2)
DOI: 10.5281/zenodo.17291276
title: BrainSTEM: A multi-resolution fetal brain atlas to assess the fidelity of human midbrain cultures

description: This upload contains data objects associated with our paper "BrainSTEM: A multi-resolution fetal brain atlas to assess the fidelity of human midbrain cultures".

In particular, this upload contains four single-cell atlases as R object files:

1) fetalWholeBrainAtlas.noRNA.rds: the fetal whole brain atlas (RNA assay removed to reduce the size)

2) fetalMidBrainAtlas.noRNA.rds: the fetal midbrain atlas (RNA assay removed to reduce the size)

3) fetalWholebrainAtlas.noRNA.mini.rds: the downsampled fetal whole brain atlas (10% cells from 1)

4) fetalMidbrainAtlas.noRNA.mini.rds: the downsampled fetal midbrain atlas (10% cells from 2)
DOI: 10.15468/dl.r7p77j
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-120 -60,-90 -60,-90 -30,-120 -30,-120 -60))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064326-250920141307145/datasets/export for details.
DOI: 10.15468/dl.z82qub
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-150 -60,-120 -60,-120 -30,-150 -30,-150 -60))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064327-250920141307145/datasets/export for details.
DOI: 10.5281/zenodo.17300840
title: Indian Traffic VQA Dataset

description: 🧭 Overview

Indian Traffic VQA is a real-world Visual Question Answering (VQA) dataset focusing on Indian road traffic signboards.The dataset is designed for training and evaluating Vision-Language Models (VLMs) and VQA systems in the traffic and transportation domain.

This dataset bridges a gap between real-world Indian traffic conditions and machine understanding — ideal for research in autonomous driving, smart city AI, and traffic sign recognition under natural environments.

📦 Dataset Summary



Images: 1,085 real-world traffic signboard images

Questions: 4,341 unique questions

Answers: Short, ground-truth textual responses

Source: All images were collected using a mobile phone in real Indian road environments

Format: .csv file with the following columns:



image_name — name of the image file

question — text-based query




answer — corresponding ground-truth answer. The traffic512final.zip file contains all the 1085 images with 512x512 resolution. There are two .csv files attached. traffic_vqa_1085.csv contains one question and one answer, traffic_vqa_4341.csv contains multiple questions and answers per image. The first .csv file can be used for low resource computational environment. 

🧠 Task Definition

Given an image of a traffic signboard and a related question, the model must predict a short text answer.

Example:






image_name



question



answer







image_0001.jpg



What does this sign indicate?



Speed Limit





image_0002.jpg



What does this sign show?



Stop





image_0003.jpg



Is U-turn allowed here?



No





🧩 Applications



Visual Question Answering (VQA)

Vision-Language Model (VLM) Fine-tuning

Multimodal classification of traffic signs

Dataset for benchmarking model reasoning in domain-specific visual data


🧰 Data Collection Details



Captured in diverse Indian traffic conditions (urban, rural, highways)

Includes varying lighting, occlusions, and view angles

All images are real photographs, not synthetic
DOI: 10.5281/zenodo.17300841
title: Indian Traffic VQA Dataset

description: 🧭 Overview

Indian Traffic VQA is a real-world Visual Question Answering (VQA) dataset focusing on Indian road traffic signboards.The dataset is designed for training and evaluating Vision-Language Models (VLMs) and VQA systems in the traffic and transportation domain.

This dataset bridges a gap between real-world Indian traffic conditions and machine understanding — ideal for research in autonomous driving, smart city AI, and traffic sign recognition under natural environments.

📦 Dataset Summary



Images: 1,085 real-world traffic signboard images

Questions: 4,341 unique questions

Answers: Short, ground-truth textual responses

Source: All images were collected using a mobile phone in real Indian road environments

Format: .csv file with the following columns:



image_name — name of the image file

question — text-based query




answer — corresponding ground-truth answer. The traffic512final.zip file contains all the 1085 images with 512x512 resolution. There are two .csv files attached. traffic_vqa_1085.csv contains one question and one answer, traffic_vqa_4341.csv contains multiple questions and answers per image. The first .csv file can be used for low resource computational environment. 

🧠 Task Definition

Given an image of a traffic signboard and a related question, the model must predict a short text answer.

Example:






image_name



question



answer







image_0001.jpg



What does this sign indicate?



Speed Limit





image_0002.jpg



What does this sign show?



Stop





image_0003.jpg



Is U-turn allowed here?



No





🧩 Applications



Visual Question Answering (VQA)

Vision-Language Model (VLM) Fine-tuning

Multimodal classification of traffic signs

Dataset for benchmarking model reasoning in domain-specific visual data


🧰 Data Collection Details



Captured in diverse Indian traffic conditions (urban, rural, highways)

Includes varying lighting, occlusions, and view angles

All images are real photographs, not synthetic
DOI: 10.15468/dl.juprmw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((-180 -60,-150 -60,-150 -30,-180 -30,-180 -60))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064330-250920141307145/datasets/export for details.
DOI: 10.15468/dl.bpz376
title: Occurrence Download

description: A dataset containing 691 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Picea asperata)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 691 records from 36 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064331-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ser297
title: Occurrence Download

description: A dataset containing 569 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Philadelphus purpurascens"
 ]
}

 The dataset includes 569 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064334-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.37x2vv
title: Occurrence Download

description: A dataset containing 1303 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Astronotus ocellatus",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1303 records from 57 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064333-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p9zfbf
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eucalyptus gunnii",
 "Country is Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 5 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064335-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f2dt67
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eucalyptus gunnii",
 "Country is Portugal",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064336-250920141307145/datasets/export for details.
DOI: 10.15468/dl.uxzsgw
title: Occurrence Download

description: A dataset containing 177 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eucalyptus gunnii",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 177 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064337-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xecnfq
title: Occurrence Download

description: A dataset containing 10184 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((150 -30,180 -30,180 0,150 0,150 -30))"
 ]
}

 The dataset includes 10184 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064338-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17301338
title: SARI-Hospitalisierungsinzidenz

description: Im Datensatz "SARI-Hospitalisierungsinzidenz" des Robert Koch-Instituts werden die wöchentlichen Inzidenzen schwerer akuter respiratorischer Infektionen (SARI) auf Bundesebene in Deutschland bereitgestellt. Die Daten stammen aus der syndromischen Krankenhaussurveillance ICOSARI, die auf ICD-10-Diagnosecodes aus etwa 70 Sentinelkliniken basiert. Der Datensatz umfasst Hospitalisierungsinzidenzen pro 100.000 Einwohner, aufgeschlüsselt nach Altersgruppen, Saison und Kalenderwoche. Neben der Gesamtheit aller SARI-Fälle werden auch Fälle mit zusätzlicher COVID-19-, Influenza- oder RSV-Diagnose separat erfasst. Die Surveillance liefert entscheidende Informationen zur Krankheitslast akuter respiratorischer Erkrankungen und dient als Grundlage für epidemiologische Bewertungen und Empfehlungen für gesundheitspolitische Maßnahmen.
DOI: 10.5281/zenodo.17301337
title: GrippeWeb - Daten des Wochenberichts

description: Im Datensatz "GrippeWeb - Daten des Wochenberichts" des Robert Koch-Instituts werden wöchentliche, bevölkerungsbasierte Schätzungen zur Inzidenz akuter respiratorischer Erkrankungen (ARE) und grippeähnlicher Erkrankungen (ILI) in Deutschland bereitgestellt. GrippeWeb als Online-Portal zur partizipativen syndromischen Surveillance nutzt Selbstauskünfte freiwilliger, pseudonym registrierter Teilnehmender ab 16 Jahren zu Symptomen wie Husten, Fieber und Halsschmerzen. Daraus werden Inzidenzen nach Altersgruppen und Regionen errechnet. Die erhobenen Daten unterstützen die Überwachung saisonaler Infektionen und dienen der Risikobewertung in Pandemien wie COVID-19.
DOI: 10.15468/dl.2y7pnf
title: Occurrence Download

description: A dataset containing 39486 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((120 -30,150 -30,150 0,120 0,120 -30))"
 ]
}

 The dataset includes 39486 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064339-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cgqgn7
title: Occurrence Download

description: A dataset containing 3108 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Ciconiiformes)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((90 -30,120 -30,120 0,90 0,90 -30))"
 ]
}

 The dataset includes 3108 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064340-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.np8g3x
title: Occurrence Download

description: A dataset containing 497 species occurrences available in GBIF matching the query:
{
 "and" : [
 "MediaType is Image",
 "TaxonKey is one of (Rana ridibunda, Rana amurensis, Triturus vulgaris, Bufo danatensis, Bufotes oblongus)"
 ]
}

 The dataset includes 497 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064341-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ebv2p
title: Occurrence Download

description: A dataset containing 438018 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is South America",
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Country derived from coordinates, Continent derived from coordinates)",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 438018 records from 406 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064240-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mxq8c3
title: Occurrence Download

description: A dataset containing 1167 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Picea brachytyla)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1167 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064342-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.z5nzf7
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Thea assamica"
 ]
}

 The dataset includes 56 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064343-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17299791
title: Microbially-mediated halogenation and dehalogenation cycling of organohalides in the ocean

description: As the Earth's largest reservoir of dissolved organic carbon, sulfur, and halogen species, the ocean is a hotspot for biogeochemical element cycling, potentially influencing global food webs and climate. Nonetheless, in contrast to the extensively studied organic carbon and sulfur cycles, investigation on the biogeochemical cycling of organohalides in the ocean is still in its infancy. Metagenome sequencing has offered new opportunities to advance our understanding of microbially mediated organohalide cycling. However, there are problems in applying publicly available orthology databases to identify organohalide-cycling genes such as inefficient database searching, inaccurate functional annotation and low coverage of organohalide-cycling genes/pathways. Therefore, it is essential to develop a comprehensive and accurate database for characterizing organohalide-cycling genes. To solve those problems, we constructed a manually curated organohalide-cycling gene database (HaloCycDB) for metagenomic analysis of microbially mediated organohalide-cycling process in the environment. Here, protein sequences from HaloCycDB were recruited from multiple public databases including UniProt, NCBI nr, KEGG, COG, eggNOG, arCOG. HaloCycDB covers 7 dehalogenation processes (oxidative dehalogenase, hydrolytic dehalogenase, reductive dehalogenase, glutathione S-transferase, methyltransferase, dehydrochlorinase, and halohydrin dehalogenase) and 4 halogenation processes (flavin-dependent halogenase, vanadium-dependent halogenase, nonheme iron-dependent halogenase, and S-adenosyl-L-methionine-dependent halogenase), containing sequences of 221 functionally-characterized genes and 187,289 representative homologous genes. HaloCycDB and the associated Python scripts will greatly promote the study of microbially mediated organohalide cycling.
DOI: 10.5281/zenodo.17299792
title: Microbially-mediated halogenation and dehalogenation cycling of organohalides in the ocean

description: As the Earth's largest reservoir of dissolved organic carbon, sulfur, and halogen species, the ocean is a hotspot for biogeochemical element cycling, potentially influencing global food webs and climate. Nonetheless, in contrast to the extensively studied organic carbon and sulfur cycles, investigation on the biogeochemical cycling of organohalides in the ocean is still in its infancy. Metagenome sequencing has offered new opportunities to advance our understanding of microbially mediated organohalide cycling. However, there are problems in applying publicly available orthology databases to identify organohalide-cycling genes such as inefficient database searching, inaccurate functional annotation and low coverage of organohalide-cycling genes/pathways. Therefore, it is essential to develop a comprehensive and accurate database for characterizing organohalide-cycling genes. To solve those problems, we constructed a manually curated organohalide-cycling gene database (HaloCycDB) for metagenomic analysis of microbially mediated organohalide-cycling process in the environment. Here, protein sequences from HaloCycDB were recruited from multiple public databases including UniProt, NCBI nr, KEGG, COG, eggNOG, arCOG. HaloCycDB covers 7 dehalogenation processes (oxidative dehalogenase, hydrolytic dehalogenase, reductive dehalogenase, glutathione S-transferase, methyltransferase, dehydrochlorinase, and halohydrin dehalogenase) and 4 halogenation processes (flavin-dependent halogenase, vanadium-dependent halogenase, nonheme iron-dependent halogenase, and S-adenosyl-L-methionine-dependent halogenase), containing sequences of 221 functionally-characterized genes and 187,289 representative homologous genes. HaloCycDB and the associated Python scripts will greatly promote the study of microbially mediated organohalide cycling.