cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.18301495
title: Dataset from a drought treatment on Viburnum opulus in a common garden set-up

description: Abstract from the associated manuscript: "Climate change impacts the functioning of our biosphere. The effects of extreme weather events, such as drought periods, will likely aggravate. We studied the impact of a summer drought on the shrub species Guelder rose (Viburnum opulus L.). Groups of saplings of a Belgian and a Swedish provenance, in a common garden setting, were subjected to different durations of drought. Impacts on phenology, morphology, physiology and growth were monitored. In the year of the treatment, severe drought extended the lifespan of surviving leaves through a slower decrease of the chlorophyll content, allowing leaves to remain green for a longer time. In the following year a delayed bud burst in the severely affected plants was surprisingly counteracted by a quicker build-up of leaf chlorophyll content. Together with a subsequent slower autumnal decrease these plants remained again longer green. Their leaves were in this year after the drought characterised by a higher specific leaf area and a more intense margin serration. These traits pointed to a proper recovery of leaf physiology and photosynthesis in the year following the drought while, as expected, both radial and height growth were reduced. Visual drought symptoms developed less quickly in the Swedish plants, possibly indicating the correspondence between cold adaptation and drought tolerance. Our results give new insights in the responses of plants upon severe drought stress."
DOI: 10.5281/zenodo.18459390
title: Genome completeness assessment of Meloidogyne hispanica
DOI: 10.5281/zenodo.18459391
title: Genome completeness assessment of Meloidogyne hispanica
DOI: 10.5878/002908
title: The Regional Western Sweden SOM Survey 2015
title: Den västsvenska SOM-undersökningen 2015
title: Väst-SOM 2015

description: Western SOM has been conducted yearly since 1992, but was initially limited to residents of Gothenburg and its surrounding municipalities. In 1998, the survey was extended to include the entire Västra Götaland County plus the municipality of Kungsbacka. 

The purpose of the regional surveys is to enable SOM researchers to study attitudes and behaviour linked to local and regional issues. They emphasise public services and media, although many of the questions are identical with those used in National SOM in order to make the answers comparable both between the regions and with Sweden at large.

Purpose:

Study attitudes and behaviours that are linked to local and regional issues and phenomena.
description: Väst-SOM har genomförts varje höst sedan 1992. Fram till 1997 omfattade studien Göteborg med kranskommuner, Undersökningen utökades sedan till att omfatta hela Västra Götalands län samt Kungsbacka kommun. Flertalet frågor har ställts i många år och svaren bidrar till att bibehålla tidsserier som sträcker sig från undersökningens början 1992. Frågorna fokuserar speciellt på områden som är aktuella på regional nivå så som offentlig service och trafikvanor. I 2015 års undersökning ingick ett antal frågor om konsumtion och miljö. Många av frågorna är identiska med frågor i Riks-SOM och Syd-SOM. Dessa studier är därmed jämförbara med varandra, både mellan de bägge regionerna och med Sverige som helhet.

Syfte:

Studera attityder och beteenden som är knutna till lokala och regionala frågor och företeelser.
DOI: 10.5878/002906
title: The Regional Western Sweden SOM Survey 2015
title: Den västsvenska SOM-undersökningen 2015
title: Väst-SOM 2015

description: Western SOM has been conducted yearly since 1992, but was initially limited to residents of Gothenburg and its surrounding municipalities. In 1998, the survey was extended to include the entire Västra Götaland County plus the municipality of Kungsbacka. 

The purpose of the regional surveys is to enable SOM researchers to study attitudes and behaviour linked to local and regional issues. They emphasise public services and media, although many of the questions are identical with those used in National SOM in order to make the answers comparable both between the regions and with Sweden at large.

Purpose:

Study attitudes and behaviours that are linked to local and regional issues and phenomena.
description: Väst-SOM har genomförts varje höst sedan 1992. Fram till 1997 omfattade studien Göteborg med kranskommuner, Undersökningen utökades sedan till att omfatta hela Västra Götalands län samt Kungsbacka kommun. Flertalet frågor har ställts i många år och svaren bidrar till att bibehålla tidsserier som sträcker sig från undersökningens början 1992. Frågorna fokuserar speciellt på områden som är aktuella på regional nivå så som offentlig service och trafikvanor. I 2015 års undersökning ingick ett antal frågor om konsumtion och miljö. Många av frågorna är identiska med frågor i Riks-SOM och Syd-SOM. Dessa studier är därmed jämförbara med varandra, både mellan de bägge regionerna och med Sverige som helhet.

Syfte:

Studera attityder och beteenden som är knutna till lokala och regionala frågor och företeelser.
DOI: 10.15468/dl.35sc2w
title: Occurrence Download

description: A dataset containing 3780 species occurrences available in GBIF matching the query:
{
 "and" : [
 "License is one of (CC0 1.0, CC-BY 4.0)",
 "MediaType is Image",
 "OccurrenceStatus is Present",
 "TaxonKey is Lutra lutra"
 ]
}

 The dataset includes 3780 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007211-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yktyyx
title: Occurrence Download

description: A dataset containing 671 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ungnadia speciosa",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 671 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007207-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qszvbb
title: Occurrence Download

description: A dataset containing 7739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA.34_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Dryobates borealis",
 "Year 1000-2026"
 ]
}

 The dataset includes 7739 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007208-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18212315
title: COFFAIL: A Dataset of Successful and Anomalous Robot Skill Executions in the Context of Coffee Preparation

description: Dataset description

This dataset includes both successful and anomalous execution episodes of the Jessie robot (https://www.h-brs.de/en/a2s/robots) performing seven different skills in the context of preparing coffee. All episodes were collected by demonstration (either by executing hand-coded scripts that produce the desired behaviour or using kinesthetic teaching).

The included skills are:



Picking up a cup from a countertop

Moving a cup by pushing

Pouring from one cup into another (note that, for safety reasons, liquid was not used in these trials)

Placing a cup on a countertop

Picking up a teaspoon

Stirring

Placing a spoon in a sink


The dataset includes robot observations and actions from the execution episodes:



Observations:



RGB images (of size 266x200 pixels) from a head camera and wrist cameras attached to each arm (for skills performed by a single arm, wrist images of the stationary arm are not collected)

Joint states (measured positions, velocities, and efforts)

End effector poses (with respect to the arm's base)



Actions in the form of end-effector delta motions (x, y, z position changes and roll, pitch, yaw orientation changes)


Data format

The data is saved in a RLDS-like format, but in the form of MongoDB databases. In particular, the dataset includes 15 separate database dumps:



Seven dumps corresponding to successful execution episodes (in total, 79 successful episodes over all skills)

Seven dumps corresponding to episodes with execution anomalies (in total, 48 anomalous episodes over all skills)

One dump of a database with anomaly annotations (anomalies are annotated using intervals, namely the annotations include entries for when each anomaly starts and when it ends, together with a comment on what the anomaly was)


In the databases corresponding to execution episodes:



each collection corresponds to a separate episode

each document corresponds to an execution step


Note that the recordings include idle states before and after each skill execution; these should be filtered out if the data is used for policy learning.

Usage examples

A Python package for working with the COFFAIL dataset is provided in the following repository: https://github.com/KEROL-project/coffail-utils/
DOI: 10.5281/zenodo.18212316
title: COFFAIL: A Dataset of Successful and Anomalous Robot Skill Executions in the Context of Coffee Preparation

description: Dataset description

This dataset includes both successful and anomalous execution episodes of the Jessie robot (https://www.h-brs.de/en/a2s/robots) performing seven different skills in the context of preparing coffee. All episodes were collected by demonstration (either by executing hand-coded scripts that produce the desired behaviour or using kinesthetic teaching).

The included skills are:



Picking up a cup from a countertop

Moving a cup by pushing

Pouring from one cup into another (note that, for safety reasons, liquid was not used in these trials)

Placing a cup on a countertop

Picking up a teaspoon

Stirring

Placing a spoon in a sink


The dataset includes robot observations and actions from the execution episodes:



Observations:



RGB images (of size 266x200 pixels) from a head camera and wrist cameras attached to each arm (for skills performed by a single arm, wrist images of the stationary arm are not collected)

Joint states (measured positions, velocities, and efforts)

End effector poses (with respect to the arm's base)



Actions in the form of end-effector delta motions (x, y, z position changes and roll, pitch, yaw orientation changes)


Data format

The data is saved in a RLDS-like format, but in the form of MongoDB databases. In particular, the dataset includes 15 separate database dumps:



Seven dumps corresponding to successful execution episodes (in total, 79 successful episodes over all skills)

Seven dumps corresponding to episodes with execution anomalies (in total, 48 anomalous episodes over all skills)

One dump of a database with anomaly annotations (anomalies are annotated using intervals, namely the annotations include entries for when each anomaly starts and when it ends, together with a comment on what the anomaly was)


In the databases corresponding to execution episodes:



each collection corresponds to a separate episode

each document corresponds to an execution step


Note that the recordings include idle states before and after each skill execution; these should be filtered out if the data is used for policy learning.

Usage examples

A Python package for working with the COFFAIL dataset is provided in the following repository: https://github.com/KEROL-project/coffail-utils/
DOI: 10.5281/zenodo.18459394
title: "Reading Between the Code Lines" Dataset and Survey Data

description: Replication package of the paper "Reading Between the Code Lines: On the Use of Self-Admitted Technical Debt for Security Analysis" by Díaz Ferreyra et al.
DOI: 10.15468/dl.bphu2u
title: Occurrence Download

description: A dataset containing 495 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Briófitos epífitos en el páramo de Rabanal, municipio de Ventaquemada"
 ]
}

 The dataset includes 495 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007213-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pz3y8c
title: Occurrence Download

description: A dataset containing 2509 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Urvillea ulmacea",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 2509 records from 169 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007214-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/a61a5173d040cf5559aaffa01f34d6e7
title: Harvard Forest Snow Pillow since 2009

description: Water storage in snowpack is a key factor in the hydrological cycle of central New England. The Harvard Forest Snow Pillow provides continuous long-term measurements of the water content of snowpack (snow water equivalent) during the winter months. The snow pillow is located in a mature mixed hardwood stand with scattered conifers about 50 m north of the Nelson Brook Big Weir. For current data, please see: https://harvardforest.fas.harvard.edu/met-hydro-stations.
DOI: 10.6084/m9.figshare.29391863
title: LabQAR (<b>Lab</b>oratory<b>Q</b>uestion<b>A</b>nswering with<b>R</b>eference Ranges) Data Set

description: LabQAR (<b>Lab</b>oratory <b>Q</b>uestion <b>A</b>nswering with <b>R</b>eference Ranges), a manually curated dataset containing multiple-choice questions about 550 lab tests with comprehensive reference ranges sourced from trusted medical resources with annotations on reference ranges, specimen types, and other factors impacting interpretation. We also assess the performance of several large language models (LLMs), including LLaMA 3.1, GatorTronGPT, GPT-3.5 turbo, GPT-4 turbo, and GPT-4o, in predicting reference ranges and classifying results as normal, low, or high.
DOI: 10.6084/m9.figshare.29391863.v1
title: LabQAR (<b>Lab</b>oratory<b>Q</b>uestion<b>A</b>nswering with<b>R</b>eference Ranges) Data Set

description: LabQAR (<b>Lab</b>oratory <b>Q</b>uestion <b>A</b>nswering with <b>R</b>eference Ranges), a manually curated dataset containing multiple-choice questions about 550 lab tests with comprehensive reference ranges sourced from trusted medical resources with annotations on reference ranges, specimen types, and other factors impacting interpretation. We also assess the performance of several large language models (LLMs), including LLaMA 3.1, GatorTronGPT, GPT-3.5 turbo, GPT-4 turbo, and GPT-4o, in predicting reference ranges and classifying results as normal, low, or high.
DOI: 10.5281/zenodo.17524155
title: Evaluation of a Timepix3 telescope for applications as a Compton scatter polarimeter for hard X- and soft γ-rays

description: This upload contains simulations of linearly polarized and unpolarized X-ray beams hitting a Timepix3 telescope consisting of 4 silicon 1-mm thick detectors and 5 cadmium telluride 1-mm thick detectors. 



Contents of this upload:





CPP_Codes.zip: C++ codes for the Geant4 simulation of the Timepix3 telescope and the polarized beams.

Polarimetry_SiCdTe_Telescope.zip: Simulated data sets in MM format (explained in the ZIP file) and Python codes to analyze them.

Polarimeter_Characteristics_0deg.txt, Polarimeter_Characteristics_45deg.txt, and Polarimeter_Characteristics_90deg.txt: Results of the data analysis - characterization of the telescope as an X-ray polarimeter at energies 35-100 keV. The seven columns in the file are:



Energy of the primary photons (in keV)

Quality factor (in %)

Uncertainty of the quality factor (in %)

Modulation factor (in %)

Uncertainty of the modulation factor (in %)

Efficiency of detection

Uncertainty of the efficiency of detection
DOI: 10.5281/zenodo.17524156
title: Evaluation of a Timepix3 telescope for applications as a Compton scatter polarimeter for hard X- and soft γ-rays

description: This upload contains simulations of linearly polarized and unpolarized X-ray beams hitting a Timepix3 telescope consisting of 4 silicon 1-mm thick detectors and 5 cadmium telluride 1-mm thick detectors. 



Contents of this upload:





CPP_Codes.zip: C++ codes for the Geant4 simulation of the Timepix3 telescope and the polarized beams.

Polarimetry_SiCdTe_Telescope.zip: Simulated data sets in MM format (explained in the ZIP file) and Python codes to analyze them.

Polarimeter_Characteristics_0deg.txt, Polarimeter_Characteristics_45deg.txt, and Polarimeter_Characteristics_90deg.txt: Results of the data analysis - characterization of the telescope as an X-ray polarimeter at energies 35-100 keV. The seven columns in the file are:



Energy of the primary photons (in keV)

Quality factor (in %)

Uncertainty of the quality factor (in %)

Modulation factor (in %)

Uncertainty of the modulation factor (in %)

Efficiency of detection

Uncertainty of the efficiency of detection
DOI: 10.4211/hs.43734306345c41358617d90800d12819
title: FLOOD-XML v.1.0 (Flood LOss and Observed Damage using eXplainable Machine Learning)

description: We introduce FLOOD-XML (Flood LOss and Observed Damage using eXplainable Machine Learning), a multi-model ensemble dataset that addresses this gap by developing data-driven flood damage functions and estimating event-level damages globally using a suite of machine learning (ML) models. Long-term flood event records from the Emergency Events Database (EM-DAT) since the 1980s have harmonized with event attributes (location, duration, fatalities, and affected area) to train ML models spanning tree-based methods, support vector regression, deep learning, and non-parametric approaches. Damage functions are calibrated using economic losses reported in U.S. dollars in EM-DAT and validated through leave-one-out and group K-fold cross-validation before being used to estimate flood damage for the Dartmouth Flood Observatory (DFO) dataset. Multiple evaluation metrics are used to assess model performance, and feature contributions are determined through explainable ML techniques.
The FLOOD-XML dataset provides globally consistent, explainable flood damage estimates, offering risk analysts, insurers, and policymakers a reproducible tool for impact-based flood hazard assessment and adaptation planning.

FLOOD-XML: https://github.com/nassernajibi/FLOOD-XML
FLOOD-XML Mapper: https://nassernajibi.github.io/FLOOD-XML-Mapper
DOI: 10.5281/zenodo.18459386
title: Supplementary Materials for "Artificial Intelligence as Ethical Mediation in Religious Education: A Transformative Eco-Social Framework from Islamic Educational"

description: This dataset contains the complete supplementary materials for the systematic literature review presented in the article "Artificial Intelligence as Ethical Mediation in Religious Education: A Transformative Eco-Social Framework from Islamic Educational Contexts." These materials provide the empirical foundation and methodological transparency for the development of the Ethical-Algorithmic Mediation Framework for Religious Education (EAM-RE).

The repository includes five comprehensive analytical matrices derived from the qualitative synthesis of 137 studies (2014–2025) on Artificial Intelligence, Religious Education, and values formation, with particular attention to Islamic educational contexts:

Contents:





SM-01: Study Characteristics Mapping TableDetailed coding of all 137 included studies with variables: Study ID, Authors/Year, Country/Context, Education Level, Methodology, and Technology-Inclusion Orientation.




SM-02: Inter-Coder Agreement MatrixComplete coding consistency data showing theme/sub-theme assignments with Krippendorff's alpha coefficients for three independent coders (average κ = 0.87).




SM-03: JBI Critical Appraisal ScoresQuality assessment of each study using Joanna Briggs Institute criteria for qualitative research, with strength/limitation annotations.




SM-04: PICo & Thematic-Content Analysis MatrixFull Population-Interest-Context framework application with thematic coding, operational definitions, and observable indicators for each study.




SM-05: Theme-SWOT-CIMO Analysis MatrixIntegrated explanatory mapping using SWOT (Strengths-Weaknesses-Opportunities-Threats) and CIMO (Context-Intervention-Mechanism-Outcome) logic for mechanism-based analysis.
DOI: 10.5281/zenodo.18459387
title: Supplementary Materials for "Artificial Intelligence as Ethical Mediation in Religious Education: A Transformative Eco-Social Framework from Islamic Educational"

description: This dataset contains the complete supplementary materials for the systematic literature review presented in the article "Artificial Intelligence as Ethical Mediation in Religious Education: A Transformative Eco-Social Framework from Islamic Educational Contexts." These materials provide the empirical foundation and methodological transparency for the development of the Ethical-Algorithmic Mediation Framework for Religious Education (EAM-RE).

The repository includes five comprehensive analytical matrices derived from the qualitative synthesis of 137 studies (2014–2025) on Artificial Intelligence, Religious Education, and values formation, with particular attention to Islamic educational contexts:

Contents:





SM-01: Study Characteristics Mapping TableDetailed coding of all 137 included studies with variables: Study ID, Authors/Year, Country/Context, Education Level, Methodology, and Technology-Inclusion Orientation.




SM-02: Inter-Coder Agreement MatrixComplete coding consistency data showing theme/sub-theme assignments with Krippendorff's alpha coefficients for three independent coders (average κ = 0.87).




SM-03: JBI Critical Appraisal ScoresQuality assessment of each study using Joanna Briggs Institute criteria for qualitative research, with strength/limitation annotations.




SM-04: PICo & Thematic-Content Analysis MatrixFull Population-Interest-Context framework application with thematic coding, operational definitions, and observable indicators for each study.




SM-05: Theme-SWOT-CIMO Analysis MatrixIntegrated explanatory mapping using SWOT (Strengths-Weaknesses-Opportunities-Threats) and CIMO (Context-Intervention-Mechanism-Outcome) logic for mechanism-based analysis.
DOI: 10.15468/dl.vgupxb
title: Occurrence Download

description: A dataset containing 217351 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Carcinus maenas"
 ]
}

 The dataset includes 217351 records from 488 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007157-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.q5khrn
title: Occurrence Download

description: A dataset containing 538199 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Human Observation, Specimen)",
 "CoordinateUncertaintyInMeters 0.0-10000.0",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Proteaceae",
 "Year 1996-2026"
 ]
}

 The dataset includes 538199 records from 164 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007188-260129131611470/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.