cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.17609223
title: Point Cloud Dataset - Pinuccio Sciola's Sound Stones

description: This dataset includes original Point Clouds representing the artworks of a Sardinian sculptor named Pinuccio Sciola. These artworks are called Sound Stones because they were played by Pinuccio using his hands or other smaller dedicated stones. Each stone produces a different sound depending on its material and texture. The dataset includes a total of 176 PCs (including both single sound stones or a block of more sound stones) scannerized from Pinuccio Sciola's garden museum in San Sperate, Cagliari, Italy.
DOI: 10.5281/zenodo.17609224
title: Point Cloud Dataset - Pinuccio Sciola's Sound Stones

description: This dataset includes original Point Clouds representing the artworks of a Sardinian sculptor named Pinuccio Sciola. These artworks are called Sound Stones because they were played by Pinuccio using his hands or other smaller dedicated stones. Each stone produces a different sound depending on its material and texture. The dataset includes a total of 176 PCs (including both single sound stones or a block of more sound stones) scannerized from Pinuccio Sciola's garden museum in San Sperate, Cagliari, Italy.
DOI: 10.6084/m9.figshare.30518093
title: Statistics Raw (all trails)

description: The raw force statistics (R-Script, R-Output, R-SVG, R-PNG, R-XLSX) for all trails.For each ofstat_CT: Contact Timestat_Max: Maximum forcestat_Max_1: Maximum force for range 0% - 50%stat_Max_2: Maximum force for range 25% - 75%stat_Max_3: Maximum force for range 50% - 100%stat_Mean: Mean forcestat_Mean_1: Mean force for range 0% - 50%stat_Mean_2: Mean force for range 25% - 75%stat_Mean_3: Mean force for range 50% - 100%stat_Median: Median forcestat_Median_1: Median force for range 0% - 50%stat_Median_2: Median force for range 25% - 75%stat_Median_3: Median force for range 50% - 100%stat_Mid: Minimum force for range 5% - 95% stat_Mid_1: Minimum force for range 10% - 40% stat_Mid_2: Minimum force for range 35% - 65% stat_Mid_3: Minimum force for range 60% - 90% stat_Min: Minimum forcestat_Min_1: Minimum force for range 0% - 50%stat_Min_2: Minimum force for range 25% - 75%stat_Min_3: Minimum force for range 50% - 100%stat_Momentum: Total areastat_Momentum_-: Negative areastat_Momentum_+: Positive area stat_Pos_Max: Position of step length with maximum forcestat_Pos_Max_1: Position of step length with maximum force for range 0% - 50%stat_Pos_Max_2: Position of step length with maximum force for range 25% - 75%stat_Pos_Max_3: Position of step length with maximum force for range 50% - 100%stat_Pos_Mid: Position of step length with minimum force for range 5% - 95%stat_Pos_Mid_1: Position of step length with minimum force for range 10% - 40%stat_Pos_Mid_2: Position of step length with minimum force for range 35% - 65%stat_Pos_Mid_3: Position of step length with minimum force for range 60% - 90%stat_Pos_Min: Position of step length with minimum forcestat_Pos_Min_1: Position of step length with minimum force for range 0% - 50%stat_Pos_Min_2: Position of step length with minimum force for range 25% - 75%stat_Pos_Min_3: Position of step length with minimum force for range 50% - 100% stat_Q25: At 25 % step lengthstat_Q50: At 50 % step lengthstat_Q75: At 75 % step length
DOI: 10.6084/m9.figshare.30518093.v1
title: Statistics Raw (all trails)

description: The raw force statistics (R-Script, R-Output, R-SVG, R-PNG, R-XLSX) for all trails.For each ofstat_CT: Contact Timestat_Max: Maximum forcestat_Max_1: Maximum force for range 0% - 50%stat_Max_2: Maximum force for range 25% - 75%stat_Max_3: Maximum force for range 50% - 100%stat_Mean: Mean forcestat_Mean_1: Mean force for range 0% - 50%stat_Mean_2: Mean force for range 25% - 75%stat_Mean_3: Mean force for range 50% - 100%stat_Median: Median forcestat_Median_1: Median force for range 0% - 50%stat_Median_2: Median force for range 25% - 75%stat_Median_3: Median force for range 50% - 100%stat_Mid: Minimum force for range 5% - 95% stat_Mid_1: Minimum force for range 10% - 40% stat_Mid_2: Minimum force for range 35% - 65% stat_Mid_3: Minimum force for range 60% - 90% stat_Min: Minimum forcestat_Min_1: Minimum force for range 0% - 50%stat_Min_2: Minimum force for range 25% - 75%stat_Min_3: Minimum force for range 50% - 100%stat_Momentum: Total areastat_Momentum_-: Negative areastat_Momentum_+: Positive area stat_Pos_Max: Position of step length with maximum forcestat_Pos_Max_1: Position of step length with maximum force for range 0% - 50%stat_Pos_Max_2: Position of step length with maximum force for range 25% - 75%stat_Pos_Max_3: Position of step length with maximum force for range 50% - 100%stat_Pos_Mid: Position of step length with minimum force for range 5% - 95%stat_Pos_Mid_1: Position of step length with minimum force for range 10% - 40%stat_Pos_Mid_2: Position of step length with minimum force for range 35% - 65%stat_Pos_Mid_3: Position of step length with minimum force for range 60% - 90%stat_Pos_Min: Position of step length with minimum forcestat_Pos_Min_1: Position of step length with minimum force for range 0% - 50%stat_Pos_Min_2: Position of step length with minimum force for range 25% - 75%stat_Pos_Min_3: Position of step length with minimum force for range 50% - 100% stat_Q25: At 25 % step lengthstat_Q50: At 50 % step lengthstat_Q75: At 75 % step length
DOI: 10.6084/m9.figshare.30518096
title: Data Raw (all trails)

description: The raw data for all trails.For each ofNon: Non-perturbed locomotion.Cau5: 5 mm backwards shifts of the platform, and Cau10: 10 mm backwards shifts of the platform, both in 0.05 s.Cra5: 5 mm forward shifts of the platform, and Cra10: 10 mm forward shifts of the platform, both in 0.05 s.
DOI: 10.6084/m9.figshare.30518096.v1
title: Data Raw (all trails)

description: The raw data for all trails.For each ofNon: Non-perturbed locomotion.Cau5: 5 mm backwards shifts of the platform, and Cau10: 10 mm backwards shifts of the platform, both in 0.05 s.Cra5: 5 mm forward shifts of the platform, and Cra10: 10 mm forward shifts of the platform, both in 0.05 s.
DOI: 10.34740/kaggle/dsv/13733705
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.57745/xsiiqb
title: Entretien avec Vladimir Svetlov. Histoire de vie et expériences de déportation en URSS

description: Cet entretien a eu lieu le 13 décembre 2009 à Minsk, Biélorussie, au Masterskaja de Kuz’ma Kozak. Il a été mené par Alain Blum et Nathalie Moine. L'entretien a été réalisé en russe. Il a duré 1 heure et 27 minutes.
DOI: 10.17043/tarfala-rivgojiehkki-res-1
title: Ice thickness and bed topography for Rivgojiehkki, northern Sweden
DOI: 10.21227/mapd-gs31
title: "LEMPS_LDWSS_12345678_TOP"

description: "Lightning Electric Field recorded by the LDWSS"
DOI: 10.15468/dl.gcqvaz
title: Occurrence Download

description: A dataset containing 229 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Endressia castellana",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 229 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008047-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/p6plxm
title: Replication Data for "The knowledge base of university branding: A science mapping review and future research agenda"

description: This dataset contains bibliographic records retrieved from the Scopus database
covering publications on university branding published between 2002 and 2025.
The records were filtered based on title, abstract, and keywords to retain
relevant publications, resulting in a final dataset of 655 documents.
The dataset was used to conduct science mapping analyses, including co-authorship 
analysis and bibliographic coupling analysis, using VOSviewer
description: Scopus, Export version
description: VOSviewer, 1.6.20
description: The sources consist of bibliographic metadata of peer-reviewed journal articles indexed in Scopus. The dataset includes information such as authors, titles, abstracts, keywords, publication years, journals, affiliations, and citation counts. Irrelevant records were excluded based on predefined inclusion and exclusion criteria, resulting in a final sample of 655 publications.
description: The dataset was exported from the Scopus database and is documented through the metadata description provided in this repository. Access to the data is available via the Harvard Dataverse using the assigned DOI.
description: This dataset contains raw bibliographic records exported from Scopus and subsequently filtered based on predefined inclusion and exclusion criteria to support a bibliometric analysis of university branding research. The dataset is intended for replication and transparency purposes.
DOI: 10.15468/dl.wjehgz
title: Occurrence Download

description: A dataset containing 323 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eleutherodactylus eneidae"
 ]
}

 The dataset includes 323 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008049-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.99z759
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eremocharis longiramea",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 20 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008050-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3nvsnm
title: Occurrence Download

description: A dataset containing 104804 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2025-12-29",
 "EventDate is less than or equal to 2026-01-28",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 },
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 104804 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008036-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kprnex
title: Occurrence Download

description: A dataset containing 87 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Stagnicola emarginata"
 ]
}

 The dataset includes 87 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008052-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.13140/rg.2.2.17740.48005
title: MY HALLUCINATION Futuristic Mother-Child Robot Simulating-Teaching Futuristic Perinatal Feeding Education-Exercise
DOI: 10.15468/dl.s4hz3b
title: Occurrence Download

description: A dataset containing 84 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Oxalis adenodes"
 ]
}

 The dataset includes 84 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008053-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xc7f73
title: Occurrence Download

description: A dataset containing 47 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eremodaucus lehmannii",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 47 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008055-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18354824
title: SuperDARN data in netCDF format (2003-Sep)

description: 2003-Sep SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6728468
title: SuperDARN data in netCDF format (2003-Sep)

description: 2003-Sep SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.14991355
title: Softcite Extractions from the Open Access Literature

description: The softcite-extractions-oa dataset is a collection of ML-identified mentions of software detected in about 24 million academic papers. The papers are all open access papers available circa 2024. The extractions were created from academic PDFs using the Softcite mention extraction toolchain, which is built on the Grobid model trained on the Softcite Annotations dataset v2. More details available at the Softcite Org home page.

This work used JetStream 2 at Indiana through allocation CIS220172 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing computational resources that have contributed to the creation and processing of this research dataset. URL: http://www.tacc.utexas.edu

See usage examples, report issues and see more documentation at https://github.com/softcite/softcite-extractions-oa

As documented in the GitHub repo, these parquet files were created by processing the original JSON files created by softcite-mentions. An intermediate dataset (about ~26GiB) is here: https://zenodo.org/records/15149411

Version history:

1.0.2 Updated files due to serialization issue in the parquet files. See https://github.com/softcite/softcite-extractions-oa/issues/29

1.0.0 Removed file restrictions, added instructions on how/where to report extraction problems

0.2.1 Added link to upstream JSONL extractions dataset (which also links to this dataset)

0.2.0 Removed extraneous Mac OS files from the zip

0.1.0 Initial upload
DOI: 10.5281/zenodo.18273457
title: Softcite Extractions from the Open Access Literature

description: The softcite-extractions-oa dataset is a collection of ML-identified mentions of software detected in about 24 million academic papers. The papers are all open access papers available circa 2024. The extractions were created from academic PDFs using the Softcite mention extraction toolchain, which is built on the Grobid model trained on the Softcite Annotations dataset v2. More details available at the Softcite Org home page.

This work used JetStream 2 at Indiana through allocation CIS220172 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing computational resources that have contributed to the creation and processing of this research dataset. URL: http://www.tacc.utexas.edu

See usage examples, report issues and see more documentation at https://github.com/softcite/softcite-extractions-oa

As documented in the GitHub repo, these parquet files were created by processing the original JSON files created by softcite-mentions. An intermediate dataset (about ~26GiB) is here: https://zenodo.org/records/15149411

Version history:

1.0.2 Updated files due to serialization issue in the parquet files. See https://github.com/softcite/softcite-extractions-oa/issues/29

1.0.0 Removed file restrictions, added instructions on how/where to report extraction problems

0.2.1 Added link to upstream JSONL extractions dataset (which also links to this dataset)

0.2.0 Removed extraneous Mac OS files from the zip

0.1.0 Initial upload
DOI: 10.15468/dl.andyn6
title: Occurrence Download

description: A dataset containing 4512 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 {
 "or" : [
 "Geometry POLYGON((76.48714 18.46753,76.48885 18.37722,76.58349 18.37902,76.58177 18.46933,76.48714 18.46753))",
 "Geometry POLYGON((117.74806 38.96292,117.74666 38.87287,117.86194 38.87108,117.86334 38.96113,117.74806 38.96292))",
 "Geometry POLYGON((138.00612 -33.1844,138.00462 -33.27454,138.11188 -33.27633,138.11339 -33.18619,138.00612 -33.1844))",
 "Geometry POLYGON((-7.56253 33.67046,-7.56402 33.58033,-7.45628 33.57854,-7.45478 33.66867,-7.56253 33.67046))",
 "Geometry POLYGON((-57.73589 -25.61634,-57.74402 -25.7063,-57.64491 -25.71526,-57.63678 -25.6253,-57.73589 -25.61634))",
 "Geometry POLYGON((-51.55665 -27.14519,-51.55825 -27.23541,-51.45735 -27.23721,-51.45575 -27.14699,-51.55665 -27.14519))",
 "Geometry POLYGON((-46.83329 -8.55329,-46.83508 -8.64367,-46.74425 -8.64547,-46.74246 -8.55509,-46.83329 -8.55329))",
 "Geometry POLYGON((-48.84506 -18.59435,-48.85703 -18.68396,-48.76317 -18.6965,-48.7512 -18.60689,-48.84506 -18.59435))",
 "Geometry POLYGON((-62.09731 -32.76132,-62.09276 -32.85141,-61.98618 -32.84603,-61.99073 -32.75595,-62.09731 -32.76132))",
 "Geometry POLYGON((77.60127 20.96025,77.59959 20.86996,77.69569 20.86816,77.69738 20.95845,77.60127 20.96025))"
 ]
 },
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4512 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008056-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31129492
title: Transfemoral Amputee Stumble Induction Dataset V2

description: A multivariate gait database pertaining to walking and induced stumbles for five transfemoral amputee subjects. Data are measured at 60 Hz and include 2 6DoF IMU sensors attached to thigh and shank segments proximally to the prosthetic knee system. All participants completed the trials with their personal MPK, the LIMBS M3, and the G-Knee (Galey et al., 2023). Each IMU contained three-dimensional gyroscope and accelerometer. In parallel, surface electromyography (sEMG) signals are recorded at 480 Hz from three thigh muscles (rectus femoris, biceps femoris, and semitendinosus) using differential surface electrodes placed beneath the prosthetic socket. Stumbles are induced in three different methods - bungee, obstacle, and uneven. Stumble events are time-aligned across IMU and sEMG recordings using shared timestamps. Stumble inductions are marked via a binary marker ("stumble" column, "1" or "0"), and files are labeled for which activity, participant, and knee is being recorded.
DOI: 10.6084/m9.figshare.31129492.v1
title: Transfemoral Amputee Stumble Induction Dataset V2

description: A multivariate gait database pertaining to walking and induced stumbles for five transfemoral amputee subjects. Data are measured at 60 Hz and include 2 6DoF IMU sensors attached to thigh and shank segments proximally to the prosthetic knee system. All participants completed the trials with their personal MPK, the LIMBS M3, and the G-Knee (Galey et al., 2023). Each IMU contained three-dimensional gyroscope and accelerometer. In parallel, surface electromyography (sEMG) signals are recorded at 480 Hz from three thigh muscles (rectus femoris, biceps femoris, and semitendinosus) using differential surface electrodes placed beneath the prosthetic socket. Stumbles are induced in three different methods - bungee, obstacle, and uneven. Stumble events are time-aligned across IMU and sEMG recordings using shared timestamps. Stumble inductions are marked via a binary marker ("stumble" column, "1" or "0"), and files are labeled for which activity, participant, and knee is being recorded.
DOI: 10.15468/dl.95gy37
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ergocarpon cryptanthum",
 "HasCoordinate is true",
 "BasisOfRecord is one of (Specimen)"
 ]
}

 The dataset includes 4 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008057-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w6sstf
title: Occurrence Download

description: A dataset containing 20 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Eleutherodactylus jasperi"
 ]
}

 The dataset includes 20 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008058-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.