cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.7hnrtk
title: Occurrence Download

description: A dataset containing 535505 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Insect Species Occurrence Data from Multiple Projects Worldwide with Focus on Bees and Wasps in North America"
 ]
}

 The dataset includes 535505 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018248-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3tnp6w
title: Occurrence Download

description: A dataset containing 458 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Theonoe minutissima (O.Pickard-Cambridge, 1879))",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 458 records from 60 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018333-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10729855
title: Database of fitted spectra for: Changing-Look AGNs - I. Tracking the transition on the main sequence of quasars

description: Results from the spectral fitting for a sample of changing-look active galactic nuclei (AGNs) with SDSS spectroscopy using PyQSOFit.
description: The database contains two master sub-directories: "FITS" and "PDF". The "FITS" contain the fitted parameters in fits table format. Whereas, the "PDF" contains the figure for the fitted spectrum for each source per epoch in pdf format. Each of these master sub-directories contain several sub-directories organized by the names of the first author from where the sources have been collected. For example, "Graham" refers to the sources from SDSS discovered by Graham et al. (2020). Each of these named sub-directories contains the respective SDSS sources procured from the respective discovery papers (the folders are named as per the SDSS nomenclature). Within each of these SDSS-named folders, we have multiple fits (or pdf) files with the format "Plate-MJD-Fiber" from the SDSS. We refer those who are interested in using this dataset to Panda & Sniegowska (2024) for more details. We kindly request if these datasets and the fitted parameter files are useful for your research, please cite our work following the above-mentioned reference.
DOI: 10.15468/dl.dv4aqx
title: Occurrence Download

description: A dataset containing 675 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Theridion melanurum Hahn, 1831)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 675 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018334-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6073/pasta/ebb3fa1a74b462f43e0191d1458123e0
title: Data from "Examining potential PFAS Contamination of Private Wells from a High School in Rural Maine"

description: Data from "Schools as Sources of PFAS Contamination of private wells in Rural Maine communities"
 
 In a community-engaged research project near Mount Desert Island High School in Bar Harbor, Maine, efforts were made to understand potential well contamination. This involved attending public meetings, distributing PFAS drinking water sample kits to homeowners, and collaborating on sample collection protocols. Surface water samples were collected from wetlands adjacent to the school, while drinking water samples were obtained from eight property owners, with careful adherence to sampling procedures to prevent contamination. Samples were analyzed for PFAS content and data are reported here.
DOI: 10.15468/dl.6suft8
title: Occurrence Download

description: A dataset containing 985 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Theridion pictum (Walckenaer, 1802))",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 985 records from 88 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018335-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hh68gz
title: Occurrence Download

description: A dataset containing 335 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Thyreosthenius parasiticus (Westring, 1851))",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 335 records from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018337-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5j77eb
title: Occurrence Download

description: A dataset containing 62957 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Riccardia Gray"
 ]
}

 The dataset includes 62957 records from 569 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018336-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wfx2fz
title: Occurrence Download

description: A dataset containing 601 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Tibellus maritimus (Menge, 1875))",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 601 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018338-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7de4gg
title: Occurrence Download

description: A dataset containing 2621 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Tipula fulvipennis De Geer, 1776)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2621 records from 76 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018341-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ydbzv9
title: Occurrence Download

description: A dataset containing 4816 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Tipula lateralis Meigen, 1804)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 4816 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018342-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p9y2re
title: Occurrence Download

description: A dataset containing 2414 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Tipula luna Westhoff, 1879)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2414 records from 72 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018343-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hthj5v
title: Occurrence Download

description: A dataset containing 427 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Felovia Lataste, 1886"
 ]
}

 The dataset includes 427 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018344-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.9kn2pz
title: Occurrence Download

description: A dataset containing 561820 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Bee Biology and Systematics Laboratory"
 ]
}

 The dataset includes 561820 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018329-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rzfp6f
title: Occurrence Download

description: A dataset containing 8289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Tipula oleracea Linnaeus, 1758)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 8289 records from 235 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018345-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kbwz8z
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Specimen",
 "TaxonKey is Dipodomys elephantinus (Grinnell, 1919)"
 ]
}

 The dataset includes 34 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018346-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p9vun0q9
title: Movement Data for Migrating Geese Over the Northeast Pacific Ocean, 2018-2021

description: This dataset consists of one table with a record (row) for each goose location and columns containing location information and covariates. The dataset was used in an analysis of altitude selection and flight propensity in an accompanying paper (Weiser et al. 2024) and is being provided here to allow replication of that analysis. Goose locations (latitude, longitude, and altitude) were collected with GPS tags and represent three subspecies: Pacific Greater White-fronted Goose, Tule Greater White-fronted Goose, and Lesser Snow Goose. Covariates include weather information from ERA5 (Hersbach et al. 2022). In addition to the 'used' locations (altitudes at which birds were recorded), the dataset also includes 'available' locations: altitude bands that the bird could have reached by that time, given its previous altitude, elapsed time, and maximum climb rate.
DOI: 10.15468/dl.xdcpvp
title: Occurrence Download

description: A dataset containing 9590 species occurrences available in GBIF matching the query:
{
 "and" : [
 "SpeciesKey is one of (Tipula paludosa Meigen, 1830)",
 "BasisOfRecord is one of (Human Observation, Observation, Occurrence evidence)",
 "Year is greater than or equal to 1901",
 "Year is less than or equal to 2019",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 9590 records from 152 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0018347-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10259014
title: A dataset of GitHub Actions workflow histories

description: This is a replication package for the dataset and exploratory empirical analysis reported in the paper "A dataset of GitHub Actions workflow histories" submitted to the MSR 2024 conference. 
The Jupyter notebook Exploratory_Analysis.ipynb requires Python 3.11.6 and some dependencies that are listed in the notebook and in the file "requirements_notebook.txt".
"workflows.tar.gz" contains the dataset of GitHub Actions workflow file histories.
"repositories.csv.gz" contains metadata about the GitHub repositories containing the workflow files. This metadata was extracted using the SEART GitHub Search tool. 
"workflows.csv.gz" contains the metadata for the extracted workflow files. The metadata is separated in different columns:

`repository`: The repository (author and repository name) from which the workflow was extracted. The separator "---" allows to distinguish between the author and the repository name.
`commit_hash`: The commit hash returned by git
`author_name`: The name of the author that changed this file
`author_email`: The email of the author that changed this file
`committer_name`: The name of the committer
`committer_email`: The email of the committer
`committed_date`: The committed date of the commit
`authored_date`:  The authored date of the commit
`file_path`:  The path to this file in the repository
`file_hash`: The name of the related workflow file in the dataset
`change_type`: A single letter (A,D or M) representing the type of change made to the workflow (Added, Deleted or Modified)
`is_workflow`: Boolean flag following aforementioned heuristic.
 "rename.csv.gz" contains the metadata for renamed files in the dataset. This metadata consists of the following columons:

`repository`: The repository (author and repository name) from which the workflow was extracted. The separator "---" allows to distinguish between the author and the repository name.
`commit`: The commit hash referring to the commit in which the file was renamed
`old_name`: The name of the file before the renaming
`new_name`: The name of the file after the renaming
DOI: 10.5281/zenodo.10566003
title: A dataset of GitHub Actions workflow histories

description: This replication package accompagnies the dataset and exploratory empirical analysis reported in the paper "A dataset of GitHub Actions workflow histories" published in the IEEE MSR 2024 conference. 

The Jupyter notebook Exploratory_Analysis.ipynb requires Python 3.11.6 and some dependencies that are listed in the notebook and in the file "requirements_notebook.txt".

"workflows.tar.gz" contains the dataset of GitHub Actions workflow file histories.

"repositories.csv.gz" contains metadata about the GitHub repositories containing the workflow files. This metadata was extracted using the SEART GitHub Search tool. 

"workflows.csv.gz" contains the metadata for the extracted workflow files. The metadata is separated in different columns:



`repository`: The repository (author and repository name) from which the workflow was extracted. The separator "---" allows to distinguish between the author and the repository name.

`commit_hash`: The commit hash returned by git

`author_name`: The name of the author that changed this file

`author_email`: The email of the author that changed this file

`committer_name`: The name of the committer

`committer_email`: The email of the committer

`committed_date`: The committed date of the commit

`authored_date`:  The authored date of the commit

`file_path`:  The path to this file in the repository

`previous_file_path`: The path to this file before it has been touched

`file_hash`: The name of the related workflow file in the dataset

`previous_file_hash: The name of the related workflow file in the dataset, before it has been touched

`change_type`: A single letter (A,D or M) representing the type of change made to the workflow (Added, Deleted or Modified)


"auxiliaries.csv.gz" is a similar file for auxiliary files.
DOI: 10.5281/zenodo.10808952
title: A dataset of GitHub Actions workflow histories

description: This replication package accompagnies the dataset and exploratory empirical analysis reported in the paper "A dataset of GitHub Actions workflow histories" published in the IEEE MSR 2024 conference. (The Jupyter notebook can be found in previous version of this dataset).

The dataset was created as follow : 



First, we used GitHub SEART to get a list of every non-fork repositories created before January 1st, 2023. having at least 300 commits and at least 100 stars where at least one commit was made after January 1st, 2023. (The goal of these filter is to exclude experimental and personnal repositories).

We checked if a folder .github/workflows existed. We filtered out those that did not contained this folder.

We applied the tool gigawork (version 1.3.0) to extract every files from this folder. The exact command used is python scripts/batch.py -d /ourDataFolder/repositories/ -e /ourDataFolder/errors -o /ourDataFolder/output -- -w /ourDataFolder/workflows. (The script batch.py can be found on GitHub).


Using the extracted data, the following files were created :



workflows.tar.gz contains the dataset of GitHub Actions workflow file histories.

repositories.csv.gz contains metadata about the GitHub repositories containing the workflow files. These metadata were extracted using the SEART Search tool. 

workflows.csv.gz contains the metadata for the extracted workflow files.

auxiliaries.csv.gz is a similar file for auxiliary files.


The metadata is separated in different columns:



repository: The repository (author and repository name) from which the workflow was extracted. The separator "---" allows to distinguish between the author and the repository name

commit_hash: The commit hash returned by git

author_name: The name of the author that changed this file

author_email: The email of the author that changed this file

committer_name: The name of the committer

committer_email: The email of the committer

committed_date: The committed date of the commit

authored_date:  The authored date of the commit

file_path:  The path to this file in the repository

previous_file_path: The path to this file before it has been touched

file_hash: The name of the related workflow file in the dataset

previous_file_hash: The name of the related workflow file in the dataset, before it has been touched

change_type: A single letter (A,D or M) representing the type of change made to the workflow (Added, Deleted or Modified)

valid_yaml: A boolean indicating if the file is a valid YAML file.

probably_workflow: A boolean representing if the file contains the YAML key on and jobs. (Note that it can still be an invalid YAML file).

valid_workflow: A boolean indicating if the file respect the syntax of GitHub Actions workflow. A freely available JSON Schema (used by gigawork) was used in this goal.


Both repositories.csv.gz and auxiliaries.csv.gz are following this format.
DOI: 10.15468/dl.3bddvj
title: Occurrence Download

description: A dataset containing 34017 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Calystegia soldanella"
 ]
}

 The dataset includes 34017 records from 636 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042018-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w56b5j
title: Occurrence Download

description: A dataset containing 611 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Diplectria",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 611 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042021-250827131500795/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25402/epi.14473257.v1
title: Supplementary table 4. Investigating DNA Methylation as the link between migration and the major non-communicable diseases. The RODAM study

description: n/a
DOI: 10.25402/epi.14519205
title: Supplementary Table 2. Gestational Sleep Apnea Perturbations Induce Metabolic Disorders by Divergent Epigenomic Regulation.

description: <b>Supplementary</b> <b>Table 2.</b> DMRs detected when comparing LG-SF and LG-IH groups.
DOI: 10.25402/epi.14519205.v1
title: Supplementary Table 2. Gestational Sleep Apnea Perturbations Induce Metabolic Disorders by Divergent Epigenomic Regulation.

description: <b>Supplementary</b> <b>Table 2.</b> DMRs detected when comparing LG-SF and LG-IH groups.
DOI: 10.15468/dl.yd3xcx
title: Occurrence Download

description: A dataset containing 60 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Halimede ochtodes (Herbst, 1783)"
 ]
}

 The dataset includes 60 records from 18 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019912-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.uscqgx
title: Occurrence Download

description: A dataset containing 1361 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is one of (Sporobolus tenuissimus (Mart. ex Schrank) Kuntze)"
 ]
}

 The dataset includes 1361 records from 148 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0019913-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25402/pmt.14753976
title: Supplementary Table 2: Evaluating predictors of pain reduction after genicular nerve radiofrequency ablation for chronic knee pain

description: Supplementary
presenting data from the logistical regression analysis, used in this study to
identify correlations between potential factors influencing pain outcomes after
radiofrequency ablation of the genicular nerve and reported pain intensities
around two months post-procedure.
DOI: 10.25402/epi.14534829
title: Supplementary File 1. Eight-gene prognostic signature associated with hypoxia and ferroptosis for gastric cancer with general applicability

description: <b>Supplemental File 1.</b> The list of 259 hypoxia and ferroptosis related genes.
DOI: 10.25402/pmt.14753982
title: Supplementary Table 1: Evaluating predictors of pain reduction after genicular nerve radiofrequency ablation for chronic knee pain

description: Supplementary
presenting data from the logistical regression analysis, used in this study to
identify correlations between potential factors influencing pain outcomes after
radiofrequency ablation of the genicular nerve and reported pain intensities
around two months post-procedure.