cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7910/dvn/vrodrj
title: Replication Data for: Esoteric beliefs and CAM impact SARS-CoV-2 immunization drivers, uptake and pediatric immunization views in Germany

description: Recent studies demonstrate that socio-political attitudes partially explain variance in (SARS-CoV-2) vaccine hesitancy and uptake. Other attitudes, such as those towards esoteric beliefs, complementary and alternative medicine (CAM), and religion, have also been proposed. However, pertinent studies provide limited direction for public health efforts, as the impact of such attitudes has been tested in isolation or on different outcomes. Moreover, related associations between SARS-CoV-2 immunization drivers as well as views towards other modes of immunization (e.g. routine pediatric immunization), remain unclear. Based on a sample of ~7,400 survey participants (Germany), where esoteric belief systems and CAM (Waldorf, homeopathy) are rather prevalent, and controlling for other sociological factors, we found that (i) individuals with positive attitudes towards Waldorf education and homeopathy are significantly less likely to have received a (further) dose of SARS-CoV-2 vaccine compared to those with positive views of mainstream medicine; (ii) for the former, immunization decisions are primarily driven by external pressures, and for the latter overwhelmingly by voluntary considerations; (iii) attitudes influencing adult SARS-CoV-2 vaccine uptake similarly influence views towards routine pediatric immunization. Our findings provide significant evidence informing a more nuanced design of public health and communication campaigns, and pertinent policies.
DOI: 10.7910/dvn/llgpox
title: Replication Data for: Short Term Memory abilities in Children

description: Data on Short Term Memory assessment in children
DOI: 10.15468/dl.zcsvqj
title: Occurrence Download

description: A dataset containing 516695 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 (Passer montanus (Linnaeus, 1758))",
 "Country is one of (Afghanistan, Armenia, Azerbaijan, Bahrain, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, Cyprus, Georgia, Hong Kong, India, Indonesia, Iran (Islamic Republic of), Iraq, Israel, Japan, Jordan, Kazakhstan, Korea (Democratic People’s Republic of), Korea, Republic of, Kuwait, Kyrgyzstan, Lao People’s Democratic Republic, Lebanon, Macao, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Oman, Pakistan, Palestine, State of, Philippines, Qatar, Saudi Arabia, Singapore, Sri Lanka, Syrian Arab Republic, Tajikistan, Thailand, Timor-Leste, Türkiye, Turkmenistan, United Arab Emirates, Uzbekistan, Viet Nam, Yemen)"
 ]
}

 The dataset includes 516695 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015195-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/v9b289v6ct
title: Structure and mechanism of anti-phage retron Eco2, Jasnauskaite et al.

description: This a repository for the DNA sequencing data and analysis scripts, HMM profiles, and phylogenetic analysis data and scripts used in the study "Retron Eco2 breaks tRNA for antiphage defense" by Jasnauskaite et al.
DOI: 10.17632/v9b289v6ct.1
title: Structure and mechanism of anti-phage retron Eco2, Jasnauskaite et al.

description: This a repository for the DNA sequencing data and analysis scripts, HMM profiles, and phylogenetic analysis data and scripts used in the study "Retron Eco2 breaks tRNA for antiphage defense" by Jasnauskaite et al.
DOI: 10.15468/dl.srqsha
title: Occurrence Download

description: A dataset containing 87316 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "Geometry POLYGON((-6.48541 36.71881,-6.2305 36.34514,-6.07697 36.17713,-5.8771 36.05836,-5.66274 36.00912,-5.55846 35.96567,-5.41362 35.98305,-5.29196 36.08153,-5.26299 36.18582,-5.20796 36.33065,-5.10078 36.39148,-4.91539 36.44073,-4.73579 36.42624,-4.60833 36.4639,-4.41715 36.6435,-4.50209 36.93777,-4.59865 37.3884,-4.70901 37.77006,-5.12285 37.908,-5.69763 37.86662,-6.13907 37.51255,-6.41496 36.97456,-6.48541 36.71881))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Plantae"
 ]
}

 The dataset includes 87316 records from 156 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020699-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/2hdmd2vd8j
title: Fenomena Oversharing sebagai Bentuk Pencarian Identitas Diri pada Generasi Z di Media Sosial

description: This dataset contains qualitative primary data collected from in-depth interviews with five Generation Z participants aged 19–23. It explores patterns of social media use, types of content shared, motivations for sharing personal information (oversharing), and perceptions of digital identity formation. The data includes respondents’ narratives on platform preferences, self-presentation strategies, and the use of selective sharing practices such as second accounts. It is intended to support research on social media behavior, oversharing, and digital identity among young adults.
DOI: 10.17632/2hdmd2vd8j.1
title: Fenomena Oversharing sebagai Bentuk Pencarian Identitas Diri pada Generasi Z di Media Sosial

description: This dataset contains qualitative primary data collected from in-depth interviews with five Generation Z participants aged 19–23. It explores patterns of social media use, types of content shared, motivations for sharing personal information (oversharing), and perceptions of digital identity formation. The data includes respondents’ narratives on platform preferences, self-presentation strategies, and the use of selective sharing practices such as second accounts. It is intended to support research on social media behavior, oversharing, and digital identity among young adults.
DOI: 10.17632/z6794ft3fs
title: Reddit discussions on generative AI in education dataset

description: This dataset contains Reddit posts and comments discussing generative AI (GenAI) in education, collected from 320 education-related subreddits between September 2022 and October 2025. It includes two versions: an unfiltered dataset of all GenAI-related posts and a cleaned, manually validated subset focused specifically on GenAI in educational contexts. Each entry includes metadata such as timestamp, score, subreddit, and text content, with stakeholder labels (students, educators, parents) added in the filtered version. All data are anonymized and compliant with Reddit’s Terms of Service. The dataset supports research on public discourse, stakeholder perspectives, sentiment, and topic trends around GenAI in education.
DOI: 10.17632/z6794ft3fs.2
title: Reddit discussions on generative AI in education dataset

description: This dataset contains Reddit posts and comments discussing generative AI (GenAI) in education, collected from 320 education-related subreddits between September 2022 and October 2025. It includes two versions: an unfiltered dataset of all GenAI-related posts and a cleaned, manually validated subset focused specifically on GenAI in educational contexts. Each entry includes metadata such as timestamp, score, subreddit, and text content, with stakeholder labels (students, educators, parents) added in the filtered version. All data are anonymized and compliant with Reddit’s Terms of Service. The dataset supports research on public discourse, stakeholder perspectives, sentiment, and topic trends around GenAI in education.
DOI: 10.6084/m9.figshare.30278374.v1
title: Supporting Computational Data for C-H Activation Initiated Skeletal Recasting of Cyclopropane Carboxylic Acid

description: Supporting Information for C-H Activation Initiated Skeletal Recasting of Cyclopropane Carboxylic Acid: This repository contains XYZ coordinate files, optimized structures, and associated Excel data used in our computational study. All files are organized for easy reuse and reproducibility, enabling further analysis and validation of reaction mechanisms and structural properties
DOI: 10.15468/dl.teqmtk
title: Occurrence Download

description: A dataset containing 42 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.97 8.770084000000001, 99.898912 8.764512, 99.829581 8.747933, 99.76371899999999 8.720756, 99.702952 8.683654000000001, 99.64878 8.637542, 99.602536 8.583558, 99.565359 8.523035999999999, 99.538161 8.457466999999999, 99.521607 8.388469000000001, 99.516099 8.317741, 99.52176799999999 8.247025000000001, 99.538467 8.178063, 99.56578 8.112551, 99.603031 8.052099, 99.6493 7.998194, 99.703447 7.95216, 99.76414 7.915129, 99.829887 7.888008, 99.899073 7.871465, 99.97 7.865905, 100.040927 7.871465, 100.110113 7.888008, 100.17586 7.915129, 100.236553 7.95216, 100.2907 7.998194, 100.336969 8.052099, 100.37422 8.112551, 100.401533 8.178063, 100.418232 8.247025000000001, 100.423901 8.317741, 100.418393 8.388469000000001, 100.401839 8.457466999999999, 100.374641 8.523035999999999, 100.337464 8.583558, 100.29122 8.637542, 100.237048 8.683654000000001, 100.176281 8.720756, 100.110419 8.747933, 100.041088 8.764512, 99.97 8.770084000000001))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 42 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020730-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zk4dau
title: Occurrence Download

description: A dataset listing the 213 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Swiss National Breeding Bird Databank"
 ]
}

 The dataset's 213 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020705-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r3awk4
title: Occurrence Download

description: A dataset containing 2487 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Macrobrachium nipponense",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2487 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020732-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57806/4d2fpj1y
title: Görlitz Rail Test Center CV Dataset 2024 (RailGoerl24)

description: RailGoerl24 is an on-board visual light Full-HD camera dataset consisting of 12,205 frames and 383,922,305 off-board LiDAR colored cloud points recorded in a railway test center of TÜV SÜD Rail, in Görlitz, Germany, on April 24th, 2024. In addition to the raw data, the dataset contains 33,556 bounding-box annotations in total for the object class ‘person’. The faces of recorded people are not blurred or altered in any other way.

It was created as a part the DZSF-funded project XRAISE. PECS-WORK GmbH, EYYES Deutschland GmbH, Chair of Engineering Psychology and Applied Cognitive Research (TU Dresden), and Chair of Fundamentals of Electrical Engineering (TU Dresden) constituted the project consortium. TU Dresden was co-supported by SECAI. TÜV SÜD Rail GmbH provided the space in Görlitz and facilitated the data collection. For more information and relevant links, please refer to the alternate description on FID-move.
description: ![Source: own illustration based on images by EYYES GmbH](https://www.dzsf.bund.de/DZSF/DE/DZSF_Intern/Bilder_RailGoerl24_FID_Move/07_RailGoerl.jpg?__blob=normal)
*Source: own animation based on images by EYYES GmbH*

## Project Info
![Logos](https://www.dzsf.bund.de/DZSF/DE/DZSF_Intern/Bilder_RailGoerl24_FID_Move/08_Logos.png?__blob=normal)

RailGoerl24 is an on-board visual light Full HD camera dataset of 12,205 frames and 383,922,305 off-board LiDAR colored cloud points recorded in a railway test center of TÜV SÜD Rail, in Görlitz, Germany, on April 24th, 2024. In addition to the raw data, the dataset contains 33,556 boxwise annotations in total for the object class ‘person’. The faces of recorded people are not blurred or altered in any other way.

It was created as a part of DZSF project  [XRAISE](https://www.dzsf.bund.de/SharedDocs/Standardartikel/DZSF/Projekte/Projekt_151_Sicherheitsargumentation_KI_ATO.html). [PECS-WORK GmbH](https://pecs-work.com/), [EYYES Deutschland GmbH](https://www.eyyes.com/), [Chair of Engineering Psychology and Applied Cognitive Research](https://tu-dresden.de/mn/psychologie/iaosp/applied-cognition?set_language=en) and [Chair of Fundamentals of Electrical Engineering](https://tu-dresden.de/ing/elektrotechnik/iee/ge) constituted the project consortium. TU Dresden was co-supported by [SECAI](https://secai.org/de). [TÜV SÜD Rail GmbH](https://www.tuvsud.com/de-de/ueber-uns/unsere-gesellschaften/rail) provided the area for recording. 

## Supplementing paper

Rustam Tagiew, Ilkay Wunderlich, Mark Sastuba, Steffen Seitz. 2025. [RailGoerl24: Görlitz Rail Test Center CV Dataset 2024](https://arxiv.org/abs/2504.00204)

## License Info
RailGoerl24 is published under [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/legalcode).
DOI: 10.15468/dl.hdx2pd
title: Occurrence Download

description: A dataset containing 115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Coronilla vaginalis, Coronilla vaginalis)",
 "Geometry POLYGON ((8.643 46.99, 14.1 46.92, 14.43 50.75, 8.534 50.83, 8.643 46.99))",
 "Year is greater than or equal to 2010",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "CoordinateUncertaintyInMeters is less than or equal to 50",
 "BasisOfRecord is one of (Observation, Human Observation, Machine Observation, Material sample)"
 ]
}

 The dataset includes 115 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020734-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gmsxtcrfgt.1
title: From Oil to Carbon: Structural Breaks and Risk Transmission in Carbon and Energy Futures

description: Overview
This dataset contains daily price and return series for three key markets over December 1, 2008 to December 31, 2020: Brent crude oil futures (fossil energy benchmark), European Renewable Energy Index (ERIX) (clean energy performance proxy), and EU Allowance (EUA) carbon futures (European carbon market benchmark). The data are used to examine time-varying dependence, tail dependence, and volatility spillovers across the carbon–oil–clean energy system.
Data sources
Brent crude oil futures: collected from the U.S. Energy Information Administration (EIA) petroleum price database.
Clean energy market (ERIX): retrieved from Bloomberg. ERIX tracks renewable energy firms with substantial exposure to at least one of the following clusters: marine, geothermal, wind, water, biofuels, and solar. Constituents are selected among the largest and most liquid eligible firms, and weights combine fixed component weights with market-value-based weights.
Carbon market (EUA): the EUA futures contract is used (rather than spot) and collected from Wind (sourced from ECX/ICE listings).
Contract and sample construction
Why EUA futures instead of spot: spot prices can be more volatile and reflect short-term supply-demand conditions, while futures incorporate forward-looking price discovery and can better represent the market’s valuation of carbon scarcity.
Sample window choice: the sample starts on December 1, 2008 to avoid the EU ETS Phase I, whose EUA return dynamics differ materially from later phases due to regulatory and trading mechanism changes, and to maintain data availability consistency across series. The sample covers EU ETS Phases II and III.
Continuous EUA series: a continuous carbon futures price series is constructed using daily settlement prices from December-expiry EUA contracts (Dec08 through Dec20). For each calendar year, the settlement prices of the corresponding December delivery contract are used to form a continuous daily series.
Data processing and variables
Frequency: daily observations.
How to interpret and use the dataset
Brent represents the global fossil-energy benchmark widely used in pricing and risk management.
ERIX captures market valuation of listed renewable energy firms and can be used as a clean-energy proxy.
EUA futures represent the forward price of carbon allowances in the European emissions trading system and are suitable for analyses that require forward-looking carbon pricing information.
Researchers can use these series to replicate dependence and spillover analyses, test alternative models (e.g., different copulas, regime definitions, or volatility specifications), or extend the system with additional assets and macro factors.
DOI: 10.17632/twyrywn22j
title: Research data supporting the manuscript “A machine learning framework for reliable prediction of open channel flow depth and velocity for hydraulic engineering applications”

description: This dataset contains the input and output variables, processed data, and model-ready datasets used to develop and validate machine learning models for reliable prediction of open channel flow depth and velocity in hydraulic engineering applications. The data supports the manuscript entitled “A machine learning framework for reliable prediction of open channel flow depth and velocity for hydraulic engineering applications” submitted to Catena. All files are organized and described in the accompanying Machine learning optimized data and results file.
DOI: 10.17632/twyrywn22j.1
title: Research data supporting the manuscript “A machine learning framework for reliable prediction of open channel flow depth and velocity for hydraulic engineering applications”

description: This dataset contains the input and output variables, processed data, and model-ready datasets used to develop and validate machine learning models for reliable prediction of open channel flow depth and velocity in hydraulic engineering applications. The data supports the manuscript entitled “A machine learning framework for reliable prediction of open channel flow depth and velocity for hydraulic engineering applications” submitted to Catena. All files are organized and described in the accompanying Machine learning optimized data and results file.
DOI: 10.17632/6mzk48brxt
title: Raw images

description: Raw images for all Western blots from "Functional characterization of CASP, a splice variant of CUX1, reveals its tumor-promoting role in colorectal cancer via TRIM21-mediated signaling".
DOI: 10.17632/6mzk48brxt.1
title: Raw images

description: Raw images for all Western blots from "Functional characterization of CASP, a splice variant of CUX1, reveals its tumor-promoting role in colorectal cancer via TRIM21-mediated signaling".
DOI: 10.17632/y4gk5m7y5f
title: Fifteen years of agriwilding substantially restores butterfly and moth diversity in a European rural landscape

description: This dataset contains a summary of Lepidoptera monitoring data obtained in the framework of the present study titled "Fifteen years of agriwilding substantially restores butterfly and moth diversity in a European rural landscape". 

Per land-management type (agriculture, agriwilding, rural nature), the total abundance of each species throughout the monitoring period is given. This means the sum of all different timepoints at which was monitored, is given. For moths, it also shows the sum of the led-light trapping monitoring method and the bait monitoring method.

Additionally, it contains trait data for the observed species. Included traits are body size and national prevalence. Body size is proxied as forewing length (in milimetres, mm) and is hence closely linked to the mobility of species (Ovaskainen et al., 2019; Sekar, 2012; Slade et al., 2013). Forewing length data was based on Cook et al., 2021, Eskildsen et al., 2015, and Sterling & Parsons, 2023. For species that were not determined to species level, the mean forewinglength of the genus or family was calculated based on species described in Sterling & Parsons, 2023 and Waring & Townsend 2020.
National prevalence reflects the total abundance of the species observed across Belgium from 2010 to 2025 (Observations.org). For species that were not determined to species level, this was considered as "NA".
DOI: 10.17632/y4gk5m7y5f.1
title: Fifteen years of agriwilding substantially restores butterfly and moth diversity in a European rural landscape

description: This dataset contains a summary of Lepidoptera monitoring data obtained in the framework of the present study titled "Fifteen years of agriwilding substantially restores butterfly and moth diversity in a European rural landscape". 

Per land-management type (agriculture, agriwilding, rural nature), the total abundance of each species throughout the monitoring period is given. This means the sum of all different timepoints at which was monitored, is given. For moths, it also shows the sum of the led-light trapping monitoring method and the bait monitoring method.

Additionally, it contains trait data for the observed species. Included traits are body size and national prevalence. Body size is proxied as forewing length (in milimetres, mm) and is hence closely linked to the mobility of species (Ovaskainen et al., 2019; Sekar, 2012; Slade et al., 2013). Forewing length data was based on Cook et al., 2021, Eskildsen et al., 2015, and Sterling & Parsons, 2023. For species that were not determined to species level, the mean forewinglength of the genus or family was calculated based on species described in Sterling & Parsons, 2023 and Waring & Townsend 2020.
National prevalence reflects the total abundance of the species observed across Belgium from 2010 to 2025 (Observations.org). For species that were not determined to species level, this was considered as "NA".
DOI: 10.17632/hhz9cprk3f
title: Data for: Comparative study on the applicability of two numerical models for predicting flow noise and acoustic sources in submarines

description: These data are verification data for the flow field and acoustic field of the SUBOFF submarine.
DOI: 10.17632/hhz9cprk3f.1
title: Data for: Comparative study on the applicability of two numerical models for predicting flow noise and acoustic sources in submarines

description: These data are verification data for the flow field and acoustic field of the SUBOFF submarine.
DOI: 10.5517/ccdc.csd.cc2q3231
title: CCDC 2505392: Experimental Crystal Structure Determination

description: Related Article: Toshiro Takao|2025|CSD Communication|||
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.