cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25824/redu/x9caea
title: Alessandra p5.mp4

description: Fala Mestra! Alessandra Ribeiro 
parte #5 A Salvaguarda
Especial para a Revista Capoeirando, 3a Edição:
https://issuu.com/revistacapoeirando

gravação e edição: Cristiano M. Gallep
DOI: 10.25824/redu/xa8g8y
title: Alessandra p4.mp4

description: Fala Mestra! Alessandra Ribeiro 
parte #4 A Feijoada, a política e o Jongo
Especial para a Revista Capoeirando, 3a Edição:
https://issuu.com/revistacapoeirando

gravação e edição: Cristiano M. Gallep
DOI: 10.5281/zenodo.15082216
title: KNOT Controlled Vocabularies

description: The KNOT Controlled Vocabularies were developed as part of the KNOT Data Model (KNOT-DM) to answer specific needs of the data model which were not appropriately covered by existing vocabularies, namely the need to classify the types of scholarly digital objects the KNOT project documents and the need to have an authority control for technologies used by these objects. This resulted in the creation of the KNOT Taxonomy and KNOT Technology Thesaurus, two SKOS-based controlled vocabularies. 

The KNOT Taxonomy aims to provide a simple hierarchical classification and definitions for different types of scholarly digital objects produced by humanities research, such as software, databases, digital platforms, and datasets. In the context of this taxonomy scholarly digital objects are understood as being either collections of structured information (such as datasets) or digital forms that enable interaction with information (software, visualization tools, etc.). 

The KNOT Technology Thesaurus aims to provide a hierarchical classification and definitions for a variety of technological concepts related to the research projects and scholarly digital objects catalogued by the KNOT project, such as the formal languages and information architecture used. 

Both vocabularies are used in the KNOT Catalogue (see https://zenodo.org/records/15037686), and intended to help increase the visibility of the scholarly digital objects created by humanities research. Definitions are taken from trusted sources and intended to act as a starting point for the classification of these objects within existing research structures and to improve authority control for the technologies used in humanities research.

The vocabularies are made available in traditional SKOS format and in SKOS with additional DCAT information, similarly to the vocabularies available from Schema, the Italian national catalogue of semantic data. The DCAT versions are labelled as such in the file name. 

Development of the vocabularies is ongoing. At the time of publication of this Zenodo record, the vocabularies are at version 1.3. All versions, as well as additional information about the vocabularies can be found on GitHub. The vocabularies can also be accessed and queried via the /DH.ARC Skosmos repository. 

The KNOT Controlled Vocabularies are part of the KNOT pilot project (2023-2025), tasked with investigating ways to integrate the Digital Cultural Heritage (DCH) of Italian universities into I.PaC, the national infrastructure being built by the Central Institute for the Digitization of Cultural Heritage (ICDP) - Digital Library. More information about the KNOT project is available on the official website.
DOI: 10.5281/zenodo.13803785
title: The Repository for the Manuscript "Temperature and Precipitation Dominate Seasonal Variations in Seismic Velocity and Attenuation in Deserts"

description: Overview

This dataset contains the essential code and data for calculating the Horizontal-to-Vertical Spectral Ratio (HVSR), analyzing vehicle-generated seismic events, retrieving Q-values, and comparing them with meteorological data. It also includes waveform data from 20 seismic events.

The seismic data originate from a temporary broadband seismic array deployed in the Tarim Basin, from July 2017 to October 2019 (Zuo et al., 2022). This dataset focuses on three seismic stations: T12, T52, and T23. Stations T12 and T23 recorded data from July 2017 to October 2019, while station T52 recorded from November 2018 to October 2019.

 

Code

The dataset includes Python scripts for calculating HVSR and retrieving Q-values. The HVSR calculation follows Li et al., (2023), while forward modeling is based on Antonio García-Jerez et al., (2016).

The codes for Q-value estimation are stored in ‘Retrieving Q-value’ folder. The Q-value estimation process, demonstrated for station T12 in Jupyter Notebook, involves extracting single vehicle signals from continuous data, time-frequency spectrogram calculations, two-dimensional correlation coefficient of their time-frequency amplitude calculations, using hierarchical clustering algorithm to classify vehicle signals, vehicle speed estimation, and performing Q-value inversion.

 

Dataset 

HVSR variations over time for three stations are calculated from continuous seismic recordings and are stored in the ‘HVSR’ folder under each station directory. 

Time-frequency spectrograms for Q-value estimation are stored in the ‘Spectrogram’ folder, with filenames indicating the record time of each vehicle signal. The Q-value is inverted using these signals, and for stability, we stacked every 100 individual results, which are stored in the 'Q-values' folder under the corresponding station name folder. Due to interference from wind and other sources, Q-value inversion using vehicle signals was unreliable for T23, so Q-values are only provided for T12 and T52.

Meteorological data (temperature and soil water content) are stored in the ‘temperature’ and ‘soil water content’ folders under each station directory.

Seismic event waveforms for 20 selected strong earthquakes are stored in the ‘events’ folder, with filenames indicating the start and end times of the events.
DOI: 10.5281/zenodo.13803786
title: Seismic Spectrograms and Q-Values of Traffic Signals, and HVSR Results from Ambient Noise at a Seismic Station in the Taklimakan Desert

description: This dataset is based on a temporary broadband seismic array (TASTE) deployed in the Tarim Basin.The TASTE array was operated from July 2017 to November 2019 by Institute of Geology and Geophysics (Zuo et al., 2022), Chinese Academy of Sciences. This dataset contains the time-frequency spectrograms, calculated Q-values, and HVSR results from station T12 of the TASTE network. Station T12, located at kilometer 60 along the Tazhong Highway, recorded numerous vehicle signals. We used individual time-frequency records to invert for changes in Q-values, with the spectrograms stored in the 'Spectrogram' folder and the Q-values stored in the 'Q-values' folder. Additionally, the HVSR variations over time were calculated from continuous seismic recordings and are stored in the 'HVSR' folder.
DOI: 10.5281/zenodo.13911399
title: Seismic Spectrograms and Q-Values of Traffic Signals, and HVSR Results from Ambient Noise at a Seismic Station in the Taklimakan Desert

description: This dataset is based on the temporary broadband seismic array (TASTE), deployed in the Tarim Basin and operated from July 2017 to October 2019 by the Institute of Geology and Geophysics, Chinese Academy of Sciences (Zuo et al., 2022). It contains time-frequency spectrograms, calculated Q-values, and HVSR results for three seismic stations: T12, T23, and T52.

Station T12, located 60 meters along the Tazhong Highway, recorded numerous vehicle signals. We selected symmetric, bell-shaped vehicle signals generated by the same type of vehicle traveling at constant speed. Each signal's time-frequency spectrogram is stored in the 'Spectrogram' folder, with file names containing the record time of each vehicle signal. The dataset consists of 350-second time segments with a frequency range from 0.8 to 45 Hz. The Q-value is inverted using these signals, and for stability, we stacked every 100 individual results, which are stored in the 'Q-values' folder. The HVSR variations over time were calculated from continuous seismic recordings and are stored in the 'HVSR' folder.

For station T52, located 100 meters away from the Tazhong road, the dataset is stored similarly to T12, though the operation period is from November 2018 to October 2019. For station T23, located 200 meters away from the Hotan road, the vehicle signals were influenced by other sources such as wind, making it difficult to invert the Q-value using vehicle signals. Therefore, the dataset for T23 only contains HVSR results from July 2017 to October 2019.
DOI: 10.5281/zenodo.15081401
title: The Repository for the Manuscript "Temperature and Precipitation Dominate Seasonal Variations in Seismic Velocity and Attenuation in Deserts"

description: Overview

This dataset contains the essential code and data for calculating the Horizontal-to-Vertical Spectral Ratio (HVSR), analyzing vehicle-generated seismic events, retrieving Q-values, and comparing them with meteorological data. It also includes waveform data from 20 seismic events.

The seismic data originate from a temporary broadband seismic array deployed in the Tarim Basin, from July 2017 to October 2019 (Zuo et al., 2022). This dataset focuses on three seismic stations: T12, T52, and T23. Stations T12 and T23 recorded data from July 2017 to October 2019, while station T52 recorded from November 2018 to October 2019.

 

Code

The dataset includes Python scripts for calculating HVSR and retrieving Q-values. The HVSR calculation follows Li et al., (2023), while forward modeling is based on Antonio García-Jerez et al., (2016).

The codes for Q-value estimation are stored in ‘Retrieving Q-value’ folder. The Q-value estimation process, demonstrated for station T12 in Jupyter Notebook, involves extracting single vehicle signals from continuous data, time-frequency spectrogram calculations, two-dimensional correlation coefficient of their time-frequency amplitude calculations, using hierarchical clustering algorithm to classify vehicle signals, vehicle speed estimation, and performing Q-value inversion.

 

Dataset 

HVSR variations over time for three stations are calculated from continuous seismic recordings and are stored in the ‘HVSR’ folder under each station directory. 

Time-frequency spectrograms for Q-value estimation are stored in the ‘Spectrogram’ folder, with filenames indicating the record time of each vehicle signal. The Q-value is inverted using these signals, and for stability, we stacked every 100 individual results, which are stored in the 'Q-values' folder under the corresponding station name folder. Due to interference from wind and other sources, Q-value inversion using vehicle signals was unreliable for T23, so Q-values are only provided for T12 and T52.

Meteorological data (temperature and soil water content) are stored in the ‘temperature’ and ‘soil water content’ folders under each station directory.

Seismic event waveforms for 20 selected strong earthquakes are stored in the ‘events’ folder, with filenames indicating the start and end times of the events.
DOI: 10.15468/dl.ftn4zc
title: Occurrence Download

description: A dataset containing 57931 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Iguana iguana (Linnaeus, 1758)"
 ]
}

 The dataset includes 57931 records from 489 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000048-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.42gtx4
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Carpodacus eos (Stresemann, 1930)"
 ]
}

 The dataset includes 106 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000057-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rryfgk
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is India",
 "DatasetKey is one of (iNaturalist Research-grade Observations, Hornbill Watch - Occurrence Dataset (India), Vertebrate Zoology Division - Ornithology, Yale Peabody Museum, Observation.org, Nature data from around the World)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anorrhinus austeni Jerdon, 1872"
 ]
}

 The dataset includes 57 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000058-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8a27me
title: Occurrence Download

description: A dataset containing 76829 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-7.67898 35.20973,35.38217 35.20973,35.38217 52.42682,-7.67898 52.42682,-7.67898 35.20973))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Fraxinus angustifolia Vahl"
 ]
}

 The dataset includes 76829 records from 706 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000050-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tp4zwb
title: Occurrence Download

description: A dataset containing 40121 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Pakistan, Nepal, Bhutan, Sri Lanka, Bangladesh, Myanmar)",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Papilionidae, Nymphalidae, Pieridae, Hesperiidae, Lycaenidae, Riodinidae)"
 ]
}

 The dataset includes 40121 records from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000060-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7jy4tb
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Nanorana conaensis (Fei & Huang, 1981)"
 ]
}

 The dataset includes 8 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000061-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15124/91b354b1-44aa-440d-b4dd-b496d74d0cc4
title: Cladonia thallus enzymes 2024

description: Data on the activity of four hydrolytic enzymes from Cladonia arbuscula thalli ocurring alone, or in concert with dwarf shrubs.
DOI: 10.5517/ccdc.csd.cc27tpg7
title: CCDC 2080269: Experimental Crystal Structure Determination

description: Related Article: Li Tang, Zhengmao Yin, Ru Wang, Bin Wang, Kefan Jiang, Mei Ding, Shuxin Wang|2022|Nanoscale|14|8842|doi:10.1039/D2NR01765B
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h7b36
title: CCDC 2300947: Experimental Crystal Structure Determination

description: Related Article: Ahmetjan Ababekri|2023|CSD Communication|||
description: Related Article: Aihaimaitijiang Ababaikeri, Xueting Pan, Xueling Hou, Jian Han|2024|New J.Chem.|48|19501|doi:10.1039/D4NJ04016C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2hgx96
title: CCDC 2308238: Experimental Crystal Structure Determination

description: Related Article: Arup Kumar  Das|2023|CSD Communication|||
description: Related Article: Arup Kumar Das, Sukanta Mandal, Narottam Mukhopadhyay, Francesc Lloret, Rabindranath Mukherjee|2025|Inorg.Chim.Acta|577|122501|doi:10.1016/j.ica.2024.122501
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gnmxp
title: CCDC 2283953: Experimental Crystal Structure Determination

description: Related Article: Bo-Chao Zhou, Bing-Zhi Chen, Ting-Ting Song, Yang Yang, Li-Ming Zhang, Ding-Wei Ji, Boshun Wan, Qing-An Chen|2024|Angew.Chem.,Int.Ed.|63|e202317299|doi:10.1002/anie.202317299
description: Related Article: Bochao Zhou|2023|CSD Communication|||
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2h7b25
title: CCDC 2300946: Experimental Crystal Structure Determination

description: Related Article: Ahmetjan Ababekri|2023|CSD Communication|||
description: Related Article: Aihaimaitijiang Ababaikeri, Xueting Pan, Xueling Hou, Jian Han|2024|New J.Chem.|48|19501|doi:10.1039/D4NJ04016C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.15468/dl.2anjkr
title: Occurrence Download

description: A dataset containing 298059 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "OccurrenceStatus is Present",
 "TaxonKey is Sciurus carolinensis Gmelin, 1788",
 "Year 1925-2025"
 ]
}

 The dataset includes 298059 records from 141 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000059-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4sz33c
title: Occurrence Download

description: A dataset containing 190 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Specimen, Material sample, Observation, Machine Observation, Human Observation, Material citation, Fossil, Living Specimen, Occurrence evidence)",
 "Country is India",
 "DatasetKey is one of (Hornbill Watch - Occurrence Dataset (India), Rapid Documentation Avifaunal Diversity of Buxa Tiger Reserve, Alipurduar, West Bengal, India, Literature based species occurrence data of birds of North-East India, Xeno-canto - Bird sounds from around the world, Vertebrate Zoology Division - Ornithology, Yale Peabody Museum, NABU|naturgucker, University of Michigan Museum of Zoology, Division of Birds, Observation.org, Nature data from around the World, iNaturalist Research-grade Observations)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Rhyticeros undulatus (Shaw, 1812)"
 ]
}

 The dataset includes 190 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000062-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/11160509
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.25405/data.ncl.28633358
title: Extended data for Case Report: Novel neuroinflammatory syndrome associated with TONSL-related SPONASTRIME dysplasia

description: The contained data supports our publication on TONSL-related SPONASTRIME Dysplasia and its association with a novel neuroinflammatory syndrome.
DOI: 10.25405/data.ncl.28633358.v1
title: Extended data for Case Report: Novel neuroinflammatory syndrome associated with TONSL-related SPONASTRIME dysplasia

description: The contained data supports our publication on TONSL-related SPONASTRIME Dysplasia and its association with a novel neuroinflammatory syndrome.
DOI: 10.15468/dl.dqf8kg
title: Occurrence Download

description: A dataset containing 63496 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Issue is one of (Zero coordinate, Coordinate out of range, Coordinate invalid, Geodetic datum invalid, Geodetic datum assumed WGS84, Coordinate reprojected, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate accuracy invalid, Coordinate precision/uncertainty mismatch, Footprint WKT invalid, Country coordinate mismatch, Country mismatch, Country invalid, Country derived from coordinates, Continent coordinate mismatch, Continent country mismatch, Continent invalid, Continent derived from country, Continent derived from coordinates, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Recorded date unlikely, Taxon match fuzzy, Taxon match higher rank, Taxon match aggregate, The taxon ID was not used in backbone matching, The scientific name ID was not found in the checklist, The taxon concept ID was not found in the checklist, The taxon ID was not found in the checklist, The scientific name differs on the record from that found in the checklist, Taxon match none, The backbone match found using the taxon IDs differs from what would be found if using the scientific names, Depth not metric, Depth unlikely, Depth min max swapped, Depth non numeric, Elevation unlikely, Elevation not metric, Elevation non numeric, Modified date unlikely, Identified date unlikely, Basis of record invalid, Type status invalid, Multimedia date invalid, Multimedia URI invalid, Error during interpretation, ccurrence status inferred from basis of record, Georeferenced date unlikely, Georeferenced date invalid, Ambiguous institution, Ambiguous collection, Institution match none, Collection match none, Institution match fuzzy, Collection match fuzzy, Institution collection mismatch, Possibly on loan, Different owner institution)",
 "OccurrenceStatus is Present",
 "TaxonKey is Larix decidua Mill.",
 "Year 2005-2025"
 ]
}

 The dataset includes 63496 records from 429 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000056-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.etrcv4
title: Occurrence Download

description: A dataset containing 90 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Albizia splendens)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 90 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005591-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/6kgt2jbr9c
title: Paired Lithium and Barium Isotopes Uncover Weathering and Productivity Controls on the Late Cambrian SPICE Event

description: Supplementary_material_GCA