cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.15306421
title: PhenoVision machine annotations of phenology for iNaturalist plant photos

description: Global phenology data on flower and fruit presence generated from machine labeling iNaturalist images through March 2024.  This dataset contains key record level information from the iNaturalist observation needed for phenology analyses, along with data and metadata about fruit and flower detection, the model used to generate machine labeling of phenology presence, and record level classification quality metrics.
DOI: 10.15468/dl.bfkebf
title: Occurrence Download

description: A dataset containing 732722 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (United States of America, Canada)",
 "DatasetKey is iNaturalist Research-grade Observations",
 "License is CC0 1.0",
 "Month is one of (October, November, December, January, February)"
 ]
}

 The dataset includes 732722 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004363-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ff8hk2
title: Occurrence Download

description: A dataset containing 24356 records in GBIF matching the query:
SELECT
 '514' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= 51.21395264452012
 AND decimalLatitude &lt;= 56.135291543055025
 AND decimalLongitude &gt;= 46.77006611473658
 AND decimalLongitude &lt;= 57.564081506819555
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 24356 records were derived from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004361-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5061/dryad.0cfxpnwdd
title: Fecal DNA metabarcoding-derived diets of deer in Sweden

description: The dataset comprises 2,568 diet samples from four deer species: 1,080
 moose (Alces alces), 329 roe deer (Capreolus capreolus), 666 red deer
 (Cervus elaphus), and 493 fallow deer (Dama dama). These diets were
 analyzed using fecal DNA metabarcoding with the primer pair Sper01_F and
 Sper01_R, which amplify the P6-loop of the chloroplast trnL intron. Diet
 composition is represented by relative read abundances (RRA) across 210
 molecular operational taxonomic units (MOTUs). Samples were collected from
 two landscapes in Sweden—BN (boreo-nemoral) and CB
 (coastal-boreal)—between 2015 and 2017.
description: # Fecal DNA metabarcoding-derived diets of deer in Sweden Dataset DOI:
 [10.5061/dryad.0cfxpnwdd](10.5061/dryad.0cfxpnwdd) ## Description of the
 data and file structure This dataset contains 2,568 fecal DNA
 metabarcoding-derived diet profiles from four Swedish deer species—moose,
 roe deer, red deer, and fallow deer—collected between 2015 and 2017. Using
 primers Sper01_F/R, targeting the chloroplast trnL P6-loop, diets are
 represented as relative read abundances (RRA) across 210 MOTUs. Samples
 were collected from two landscapes: BN (boreo-nemoral) and CB
 (coastal-boreal). ### Files and variables #### File:
 CervidDiets_Sweden_fecDNAmb.xlsx **Description:** Diet data from four deer
 species in Sweden ##### Variables * Sample_No. (1 - 2,586) * Tract_ID
 (tract number where fecal samples were collected) * Area (BN:
 boreo-nemoral, CB: coastal-boreal) * Season * Month (collection month) *
 Year (collection year) * Deer_species (*Alces alces, Capreolus capreolus,
 Cervus elaphus, Dama dama*) * 210 columns denoting the MOTUs in the diets
DOI: 10.15468/dl.vyxyjm
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhadinorhynchus pristis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004379-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.16904/envidat.193
title: Ice nucleating particle concentrations active at -15 °C at Weissfluhjoch

description: This dataset contains number concentrations of ice-nucleating particles active at -15 °C observed at Weissfluhjoch during February and March 2019, as well as complementary data (measured aerosol number concentrations and modelled total precipitation along air mass trajectories). This data formed the basis of our paper with the title “Towards parameterising atmospheric concentrations of ice-nucleating particles active at moderate supercooling”.
description: Resource Title: INP15_WFJ_version1
 Size: 11030 bytes
 Format: text/csv
 URL: https://www.envidat.ch/dataset/abf0b918-c606-4d3b-99cb-e503e99435f6/resource/28c08311-01f4-4245-a139-f867cfe69677/download/inp15_wfj.csv
 Description:
description: Resource Title: INP15_WFJ_version2.csv
 Size: 12704 bytes
 Format: application/vnd.ms-excel
 URL: https://www.envidat.ch/dataset/abf0b918-c606-4d3b-99cb-e503e99435f6/resource/3fd9cf7f-1b00-4e70-be8d-eb3b70c4ad03/download/inp15_wfj_version2.csv
 Description: This dataset version includes revised formatting for the start and end time fields.
DOI: 10.16904/envidat.724
title: Data for the publication Optical determination of snow density via sub-surface scattering

description: This repository contains the data necessary to reproduce Fig. 5 of the publication: L. Mewes, H. Löwe, M. Schneebeli & B. Walter, *Optical determination of snow density via sub-surface scattering*, Commun Phys, doi: [10.1038/s42005-026-02490-1](https://doi.org/10.1038/s42005-026-02490-1).
The source code generating Fig. 5 for the above mentioned publication is available at [10.16904/envidat.726](https://doi.org/10.16904/envidat.726).
 Files
`SI01_Reflectance_Coldlab.h5`: Reflectance and partial reflectance data of a snow profile using the [SnowImager](https://www.snowimager.ch/).
`uCT_reference_data.csv`: Reference data extracted from a micro-computed tomography measurement.
Please refer to the `README` of the analysis code at [10.16904/envidat.726](https://doi.org/10.16904/envidat.726) for further information.
description: Resource Title: Data for the publication Mewes et al., Commun Phys, 2026.
 Size: 1625293 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/a243cb72-d674-4648-a741-aa52fa852f4f/resource/92c82462-e059-4ac9-8d0e-c113408eb99f/download/data.zip
 Description: SnowImager and reference micro-CT data.
DOI: 10.16904/envidat.726
title: Source code for the publication Optical determination of snow density via sub-surface scattering

description: The repository contains the source code necessary to reproduce Figs. 2-5 of the publication: L. Mewes, H. Löwe, M. Schneebeli & B. Walter, *Optical determination of snow density via sub-surface scattering*, Commun Phys, doi: [10.1038/s42005-026-02490-1](https://doi.org/10.1038/s42005-026-02490-1).
The data for Fig. 5 of the above mentioned publication is available at [10.16904/envidat.724](https://doi.org/10.16904/envidat.724).
Please refer to the `README` in this repository for additional information.
- **License:** The scripts in this repository are licensed under the MIT License; see LICENSE.txt for the full text.
 Files
`generate_figures.py`: Main script to generate the figures of the publication.
`snow_optics.py`: Core radiative-transfer functions.
`snow_image.py`: Utilities for loading and processing SnowImager ([www.snowimager.ch](https://www.snowimager.ch)) HDF5 data.
`helper.py`: Miscellaneous helper functions.
`lambertw.py`: Lambert W function implementation (John Burkardt, 2023, MIT license, -https://people.sc.fsu.edu/~jburkardt/py_src/lambert_w/lambert_w.py-).
 Third party resources
- Refractive indices of ice are taken from 'Warren, S. G., and R. E. Brandt (2008), Optical constants of ice from the ultraviolet to the microwave: A revised compilation, J. Geophys. Res., 113, D14220, doi:[10.1029/2007JD009744](https://doi.org/10.1029/2007JD009744).' available at: https://refractiveindex.info/database/data/main/H2O/nk/Warren-2008.yml
- The Lambert *W* function is implemented using the code of John Burkardt, modified 20 June 2023 and distributed under the MIT license (-https://people.sc.fsu.edu/~jburkardt/py_src/lambert_w/lambert_w.py-). 
- The source code in this repository is part of a larger project for post-processing [SnowImager](https://www.snowimager.ch) data hosted at [https://code.wsl.ch/snow-physics/snowimagerpro](https://code.wsl.ch/snow-physics/snowimagerpro).
description: Resource Title: README.md
 Size: 5181 bytes
 Format: text/markdown
 URL: https://www.envidat.ch/dataset/5ef9984d-7fd8-4b95-87c4-f479b2e5ac13/resource/97d46f1d-9321-4b1a-9a72-d79978da633f/download/readme.md
 Description: Instructions to generate figures for Mewes et al., Commun Phys, 2026.
description: Resource Title: Source code
 Size: 22825 bytes
 Format: application/zip
 URL: https://www.envidat.ch/dataset/5ef9984d-7fd8-4b95-87c4-f479b2e5ac13/resource/9af1ca7b-8780-46ec-abbc-e4b6890eead6/download/src.zip
 Description: Source code to generate the figures for Mewes et al., Commun Phys, 2026.

The scripts in this repository are licensed under the MIT License; see LICENSE.txt for the full text.
DOI: 10.5281/zenodo.18379216
title: A new bee species of the genus Dasypoda from North Africa uncovered by morphology and ultraconserved element phylogenomics (Hymenoptera: Melittidae)

description: This dataset supports the study “Ultraconserved element phylogenomics of Dasypoda bees uncovers a new species from North Africa (Hymenoptera: Melittidae)” (DOI: https://doi.org/10.1071/IS24073).

It includes genome/contig assemblies, a concatenated ultraconserved element (UCE) supermatrix, phylogenetic inference outputs from IQ-TREE and ASTRAL, extracted DNA barcode sequences, and metadata mapping legacy sample identifiers to updated names.

Assemblies were used for UCE extraction and alignment. Maximum-likelihood phylogenies were inferred using IQ-TREE, and coalescent-based species trees were estimated using ASTRAL. DNA barcode sequences support specimen identification and taxonomic validation, including the recognition of a newly described North African Dasypoda species.

These files enable reproducibility of phylogenomic results and reuse in comparative systematics, bee evolution research, and biodiversity genomics.

Related publication: https://doi.org/10.1071/IS24073License: CC-BY 4.0 (recommended)
DOI: 10.5281/zenodo.18379217
title: A new bee species of the genus Dasypoda from North Africa uncovered by morphology and ultraconserved element phylogenomics (Hymenoptera: Melittidae)

description: This dataset supports the study “Ultraconserved element phylogenomics of Dasypoda bees uncovers a new species from North Africa (Hymenoptera: Melittidae)” (DOI: https://doi.org/10.1071/IS24073).

It includes genome/contig assemblies, a concatenated ultraconserved element (UCE) supermatrix, phylogenetic inference outputs from IQ-TREE and ASTRAL, extracted DNA barcode sequences, and metadata mapping legacy sample identifiers to updated names.

Assemblies were used for UCE extraction and alignment. Maximum-likelihood phylogenies were inferred using IQ-TREE, and coalescent-based species trees were estimated using ASTRAL. DNA barcode sequences support specimen identification and taxonomic validation, including the recognition of a newly described North African Dasypoda species.

These files enable reproducibility of phylogenomic results and reuse in comparative systematics, bee evolution research, and biodiversity genomics.

Related publication: https://doi.org/10.1071/IS24073License: CC-BY 4.0 (recommended)
DOI: 10.15468/dl.5fvnjv
title: Occurrence Download

description: A dataset containing 3220 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Icaricia lupini"
 ]
}

 The dataset includes 3220 records from 37 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004380-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rv4ydd
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rhadinorhynchus saltatrix",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004381-260126135527185/datasets/export for details.
DOI: 10.5061/dryad.z8w9ghxrk
title: Transcriptome dataset for: The ESCRT protein CHMP5 restricts bone formation by controlling endolysosome-mitochondrion-mediated cell senescence

description: This original dataset was generated from transcriptome analysis of
 Chmp5-deficient versus control skeletal progenitor cells in the paper. The
 purpose of the experiment was to identify differentially expressed genes
 in Chmp5-deficient versus control periskeletal progenitor cells, which
 were obtained from Chmp5Ctsk and Chmp5Ctsk/+ mice, respectively. It
 includes data for 3 replicates (cells from 3 different animals) in each
 group.
description: # Transcriptome dataset for "The ESCRT protein CHMP5 restricts bone
 formation by controlling endolysosome-mitochondrion-mediated cell
 senescence" Dataset DOI:
 [10.5061/dryad.z8w9ghxrk](10.5061/dryad.z8w9ghxrk) ## Description of the
 data and file structure Transcriptome analysis of *Chmp5*-KO and Control
 periskeletal progenitor cells (mouse) ### Files and variables #### File:
 CO1_5m_C13_LIB_1.fq.gz **Description:**  Control periskeletal progenitor
 cells sample 1-1 #### File: CO1_5m_C13_LIB_2.fq.gz **Description:** 
 Control periskeletal progenitor cells sample 1-2 #### File:
 CO2_5m_C13_LIB_1.fq.gz **Description:**  Control periskeletal progenitor
 cells sample 2-1 #### File: CO2_5m_C13_LIB_2.fq.gz **Description:** 
 Control periskeletal progenitor cells sample 2-2 #### File:
 CO3_5m_C13_LIB_1.fq.gz **Description:**  Control periskeletal progenitor
 cells sample 3-1 #### File: CO3_5m_C13_LIB_2.fq.gz **Description:** 
 Control periskeletal progenitor cells sample 3-2 #### File:
 KO1_5m_C13_LIB_1.fq.gz **Description:** *Chmp5*-KO periskeletal progenitor
 cells sample 1-1 #### File: KO1_5m_C13_LIB_2.fq.gz
 **Description:** *Chmp5*-KO periskeletal progenitor cells sample 1-2 ####
 File: KO2_5m_C13_LIB_1.fq.gz **Description:** *Chmp5*-KO periskeletal
 progenitor cells sample 2-1 #### File: KO2_5m_C13_LIB_2.fq.gz
 **Description:** *Chmp5*-KO periskeletal progenitor cells sample 2-2 ####
 File: KO3_5m_C13_LIB_1.fq.gz **Description:** *Chmp5*-KO periskeletal
 progenitor cells sample 3-1 #### File: KO3_5m_C13_LIB_2.fq.gz
 **Description:** K*Chmp5*-KO periskeletal progenitor cells sample 3-2 ##
 Code/software The raw Illumina pair-end reads were first aligned with
 ribosomal RNA (GenBank ID BK000964.1) with Bowtie2 v2.2.6. Reads that
 failed to map to ribosomal RNA were aligned with the mouse reference
 genome mm10 with STAR v2.5.3 editor. Files can be opened and viewed in a
 text editor. ## Access information Other publicly accessible locations of
 the data: * N/A Data was derived from the following sources: * N/A
DOI: 10.15468/dl.a8g7h5
title: Occurrence Download

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Southwellina hispida",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 84 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004383-260126135527185/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.17429307
title: Appendix C - Dataset - Cognitive Capability and Personality Influence Problem-Solving

description: This is the anonymised dataset shared as a supplimentary materials for the paper accepted at CHASE 2026. . It does not include any identifiable information of the participants.
DOI: 10.5281/zenodo.17429306
title: Appendix C - Dataset - Cognitive Capability and Personality Influence Problem-Solving

description: This is the anonymised dataset shared as a supplimentary materials for the paper accepted at CHASE 2026. . It does not include any identifiable information of the participants.
DOI: 10.5061/dryad.0rxwdbscp
title: Secretome dataset for: The ESCRT protein CHMP5 restricts bone formation by controlling endolysosome-mitochondrion-mediated cell senescence

description: This is the original secretome dataset for Chmp5-KO versus
 control periskeletal progenitor cells, as presented in the paper (Figure
 4H). The purpose of the experiment was to characterize the secretory
 profile and identify differentially secreted proteins in the supernatant
 of Chmp5-KO versus control periskeletal progenitor cells, which were
 obtained from Chmp5Ctsk and wild-type mice, respectively. It includes data
 for 3 replicates (cells from 3 different animals) in each group.
description: # Secretome dataset for: The ESCRT protein CHMP5 restricts bone formation
 by controlling endolysosome-mitochondrion-mediated cell senescence Dataset
 DOI: [10.5061/dryad.0rxwdbscp](10.5061/dryad.0rxwdbscp) ## Description of
 the data and file structure This is the secretome dataset for *Chmp5*-KO
 and control periskeletal progenitor cells.  ### Files and variables ####
 File: BTP-20230615-05-01.raw **Description:** Control periskeletal
 progenitor cells, sample 1 #### File: BTP-20230615-05-02.raw
 **Description:** Control periskeletal progenitor cells, sample 2 ####
 File: BTP-20230615-05-03.raw **Description:** Control periskeletal
 progenitor cells, sample 3 #### File: BTP-20230615-05-04.raw
 **Description:** *Chmp5*-KO periskeletal progenitor cells, sample 1 ####
 File: BTP-20230615-05-05.raw **Description:** *Chmp5*-KO periskeletal
 progenitor cells, sample 2 #### File: BTP-20230615-05-06.raw
 **Description:** *Chmp5*-KO periskeletal progenitor cells, sample 3 ##
 Code/software These files can be opened and viewed using the Thermo RAW
 File Reader software or a third-party tool that can handle .raw files,
 such as MaxQuant. ## Access information Other publicly accessible
 locations of the data: * N/A Data was derived from the following sources:
 * N/A
DOI: 10.5281/zenodo.18408048
title: Wind and Nordpool Electricity Data
DOI: 10.5281/zenodo.18408047
title: Wind and Nordpool Electricity Data
DOI: 10.5061/dryad.cfxpnvxk2
title: Proteomic dataset for: The ESCRT protein CHMP5 restricts bone formation by controlling endolysosome-mitochondrion-mediated cell senescence

description: This is the proteomic dataset of Chmp5-KO versus control
 periskeletal progenitor cells, as presented in the paper (Figure 6I). The
 purpose of the experiment was to identify intracellular proteins that are
 differentially expressed in Chmp5-KO versus control periskeletal
 progenitor cells, which were obtained from Chmp5Ctsk and wild-type mice,
 respectively. The dataset includes data for 3 replicates (cells from 3
 different animals) in each group.
description: # Proteomic dataset for "The ESCRT protein CHMP5 restricts bone
 formation by controlling endolysosome-mitochondrion-mediated cell
 senescence" Dataset DOI:
 [10.5061/dryad.cfxpnvxk2](10.5061/dryad.cfxpnvxk2) ## Description of the
 data and file structure This is the proteomic dataset for *Chmp5*-KO and
 control periskeletal progenitor cells.  ### Files and variables #### File:
 BTP-20230615-05-07.raw **Description:** Control periskeletal progenitor
 cells, sample 1 #### File: BTP-20230615-05-08.raw **Description:** Control
 periskeletal progenitor cells, sample 2 #### File: BTP-20230615-05-09.raw
 **Description:** Control periskeletal progenitor cells, sample 3 ####
 File: BTP-20230615-05-10.raw **Description:** *Chmp5*-KO periskeletal
 progenitor cells, sample 1 #### File: BTP-20230615-05-11.raw
 **Description:** *Chmp5*-KO periskeletal progenitor cells, sample 2 ####
 File: BTP-20230615-05-12.raw **Description:** *Chmp5*-KO periskeletal
 progenitor cells, sample 3 ## Code/software These files can be opened and
 viewed using the Thermo RAW File Reader software or a third-party tool
 that can handle .raw files, such as MaxQuant. ## Access information Other
 publicly accessible locations of the data: * N/A Data was derived from the
 following sources: * N/A
DOI: 10.5281/zenodo.18392898
title: Rural distribution power line vegetation management dataset (vegetation, power line, power pole/structure, and background)

description: This dataset comprises 2,404 images of rural distribution power lines (and some abutting areas in urban zones), categorized into four classes: vegetation, power line, power pole/structure, and background. It is one of the results of Jean Cassio Peres Barbosa's master's thesis, advised by Prof. Dr. Rafael Rieder. This study was also supported by Charles Leonardo Israel, Ademilson Setti, Mateus Goetz, Diego Darci Langaro, Juliano Wagner Daronch, Cristiane de Fatima Ribeiro, and Fabrício Páris.

From this dataset, we labeled:- 3093 polygons as vegetation (class 0);- 6807 polygons as power line (class 1);- 2224 polygons as power pole/structure (class 2);- 386 polygon masks (holes) as background (class 3).

The authors acknowledge the financial support from Companhia Paulista de Força e Luz (CPFL – Distribuição) through the Research, Development, and Innovation Program of the Brazilian Electricity Regulatory Agency (ANEEL), under contract PD-00063-3099/2024, and the institutional support from Fundação Universidade de Passo Fundo (FUPF).
DOI: 10.5281/zenodo.18392897
title: Rural distribution power line vegetation management dataset (vegetation, power line, power pole/structure, and background)

description: This dataset comprises 2,404 images of rural distribution power lines (and some abutting areas in urban zones), categorized into four classes: vegetation, power line, power pole/structure, and background. It is one of the results of Jean Cassio Peres Barbosa's master's thesis, advised by Prof. Dr. Rafael Rieder. This study was also supported by Charles Leonardo Israel, Ademilson Setti, Mateus Goetz, Diego Darci Langaro, Juliano Wagner Daronch, Cristiane de Fatima Ribeiro, and Fabrício Páris.

From this dataset, we labeled:- 3093 polygons as vegetation (class 0);- 6807 polygons as power line (class 1);- 2224 polygons as power pole/structure (class 2);- 386 polygon masks (holes) as background (class 3).

The authors acknowledge the financial support from Companhia Paulista de Força e Luz (CPFL – Distribuição) through the Research, Development, and Innovation Program of the Brazilian Electricity Regulatory Agency (ANEEL), under contract PD-00063-3099/2024, and the institutional support from Fundação Universidade de Passo Fundo (FUPF).