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

description: A dataset containing 918 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chamaedaphne calyculata (L.) Moench",
 "BasisOfRecord is one of (Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is North America"
 ]
}

 The dataset includes 918 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0164503-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4f52ey
title: Occurrence Download

description: A dataset containing 836 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (United States of America, Nicaragua)",
 "DatasetKey is ORN",
 "Month is one of (March, April, May, June, August, September, October, November)",
 "RecordedBy is Window kill",
 "Year 2017-2023"
 ]
}

 The dataset includes 836 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047855-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.readct
title: Occurrence Download

description: A dataset containing 4289 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Juglans mandshurica Maxim.)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 4289 records from 119 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047854-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ujmfvp
title: Occurrence Download

description: A dataset containing 28 species occurrences available in GBIF matching the query:
{
 "or" : [
 "TaxonKey is Melipona nebulosa Camargo, 1988",
 "TaxonKey is Melipona mondury Smith, 1863"
 ]
}

 The dataset includes 28 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024114-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vpbmsy
title: Occurrence Download

description: A dataset containing 101 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bergia texana (Hook.) Seub. ex Walp.",
 "BasisOfRecord is one of (Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is North America"
 ]
}

 The dataset includes 101 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0164480-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fp8915
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rudgea reflexa Zappi"
 ]
}

 The dataset includes 32 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024114-190415153152247/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x7kqbe
title: Occurrence Download

description: A dataset containing 1084 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Equisetum scirpoides Michx.",
 "BasisOfRecord is one of (Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Continent is North America"
 ]
}

 The dataset includes 1084 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0164494-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ggl9sy
title: Occurrence Download

description: A dataset containing 631 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-94.48242187499999 9.223575600684129,-84.11132812500001 19.095345039005593,-86.220703125 25.276492369053017,-90.96679687499999 26.38399830452333,-93.779296875 31.608482865344655,-100.10742187500001 34.6982694632668,-105.380859375 35.98867592117699,-111.884765625 32.35398080148735,-117.15820312499999 21.894125043900246,-94.48242187499999 9.223575600684129))",
 "HasCoordinate is true",
 "TaxonKey is Pistacia mexicana Kunth",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 631 records from 43 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024115-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.gtx4sy
title: Occurrence Download

description: A dataset containing 501760 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "GadmGid is CHN.22_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 501760 records from 268 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001685-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tx782x
title: Occurrence Download

description: A dataset containing 54054 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CRIS data set"
 ]
}

 The dataset includes 54054 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001706-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.epu3du
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trifolium isodon Murb.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001708-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xyvs4c
title: Occurrence Download

description: A dataset containing 83 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trifolium kingii var. productum (Greene) Jeps., Trifolium kingii subsp. productum (Greene) D.Heller)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 83 records from 13 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001710-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14055725
title: Amtliche Begründungen zu hochschulrechtlichen Open-Access-Definitionen in Deutschland

description: Der aus dem Englischen stammende Begriff Open Access ist längst kein urheberrechtlicher Spezialbegriff mehr, sondern feste Größe im deutschen Hochschulrecht. Was aber bedeutet dieses unverändert in die deutsche Rechtssprache übernommene Lehnwort? Der vorliegende Datensatz versammelt erstmals alle Gesetzesbegründungen zu denjenigen Vorschriften, die sich zum 31.12.2024 auf „Open Access“ bezogen:



Berlin: § 41 Abs. 3 Satz 1 HG und § 6 Abs. 4 Satz 2 PflAV

Brandenburg: § 37 Abs. 2 HG

Bremen: § 6 Abs. 3 Satz 2 BibG und § 75 Abs. 5 Satz 1 HSchulG

Nordrhein-Westfalen: § 50 Abs. 2 Satz 2 KulturGB

Sachsen-Anhalt: § 24 Abs. 5 HSG

Schleswig-Holstein: § 4 Abs. 2 BiblG


Auf den zusammengetragenen Dokumenten beruht ein juristischer Fachaufsatz, der die Gemeinsamkeiten und Unterschiede der gewählten Legaldefinitionen und die politischen Prozesse ihrer Ausarbeitung untersucht:

Hamann, Open Access als Rechtsbegriff: Eine Bestandsaufnahme zwischen Urheberrecht und Hochschulrecht, JZ 2025, S. 217–227

Die Untersuchung ergibt, dass das politische Schlagwort „Open Access“ noch nicht konsistent verrechtlicht wurde, obwohl die Wissenschaft mit der sogenannten Berliner Erklärung längst einen konsensfähigen und urheberrechtlich nachvollziehbaren Gebrauch etabliert hat.
DOI: 10.5281/zenodo.14055726
title: Amtliche Begründungen zu hochschulrechtlichen Open-Access-Definitionen in Deutschland

description: Der aus dem Englischen stammende Begriff Open Access ist längst kein urheberrechtlicher Spezialbegriff mehr, sondern feste Größe im deutschen Hochschulrecht. Was aber bedeutet dieses unverändert in die deutsche Rechtssprache übernommene Lehnwort? Der vorliegende Datensatz versammelt erstmals alle Gesetzesbegründungen zu denjenigen Vorschriften, die sich zum 31.12.2024 auf „Open Access“ bezogen:



Berlin: § 41 Abs. 3 Satz 1 HG und § 6 Abs. 4 Satz 2 PflAV

Brandenburg: § 37 Abs. 2 HG

Bremen: § 6 Abs. 3 Satz 2 BibG und § 75 Abs. 5 Satz 1 HSchulG

Nordrhein-Westfalen: § 50 Abs. 2 Satz 2 KulturGB

Sachsen-Anhalt: § 24 Abs. 5 HSG

Schleswig-Holstein: § 4 Abs. 2 BiblG


Auf den zusammengetragenen Dokumenten beruht ein juristischer Fachaufsatz, der die Gemeinsamkeiten und Unterschiede der gewählten Legaldefinitionen und die politischen Prozesse ihrer Ausarbeitung untersucht:

Hamann, Open Access als Rechtsbegriff: Eine Bestandsaufnahme zwischen Urheberrecht und Hochschulrecht, JZ 2025, S. 217–227

Die Untersuchung ergibt, dass das politische Schlagwort „Open Access“ noch nicht konsistent verrechtlicht wurde, obwohl die Wissenschaft mit der sogenannten Berliner Erklärung längst einen konsensfähigen und urheberrechtlich nachvollziehbaren Gebrauch etabliert hat.
DOI: 10.5281/zenodo.15087490
title: Fig3b,c
DOI: 10.5281/zenodo.15087491
title: Fig3b,c
DOI: 10.15468/dl.z9mups
title: Occurrence Download

description: A dataset containing 6038 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Trifolium lappaceum L.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6038 records from 275 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001711-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.15039562
title: Dataset for "Holmium-Doped Silica Fibers Combining High Doping and High Efficiency"

description: Dataset for paper called "Holmium-Doped Silica Fibers Combining High Doping and High Efficiency" including experimental and simulation data.
DOI: 10.5281/zenodo.15039563
title: Dataset for "Holmium-Doped Silica Fibers Combining High Doping and High Efficiency"

description: Dataset for paper called "Holmium-Doped Silica Fibers Combining High Doping and High Efficiency" including experimental and simulation data.
DOI: 10.15468/dl.h8qv7w
title: Occurrence Download

description: A dataset containing 744 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dorcus japonicus Nakane & Makino, 1985, Prosopocoilus pseudodissimilis Kurosawa, 1976, Figulus yujii Fujita, 1994, Nigidius lewisi Boileau, 1905, Prosopocoilus dissimilis Boileau, 1898, Prismognathus dauricus (Motschulsky, 1860), Aegus ogasawarensis Okajima & Kobayashi, 1975, Figulus punctatus Waterhouse, 1872, Neolucanus protogenetivus Kurosawa, 1976, Prismognathus angularis Waterhouse, 1874, Prosopocoilus hachijoensis Nomura, 1960, Platycerus albisomni Kubota, Kubota & Otobe, 2008, Aesalus asiaticus Lewis, 1883, Dorcus amamianus (Nomura, 1964))",
 "HasCoordinate is true"
 ]
}

 The dataset includes 744 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001712-250325103851331/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4121/dfbe9109-d058-4a64-a5b4-1cc9d9a5f836.v1
title: SPAMS10 Krimpenerwaard: Soil motion parameters to model relative surface elevation changes

description: SPAMS (Simple Parameterization for the Motion of Soils) is a model that provides a first approximation of vertical soil motion for a particular location described by four parameters, given the availability of meteorological data. SPAMS estimates surface motion parameters based on physical processes by assuming that soil displacement is mainly driven by meteorological factors, and distinguishes between reversible and irreversible subsidence. The model uses precipitation and evapotranspiration data from nearby meteorological stations. The SPAMS parameters can be estimated using a certain period of observations from Interferometric Synthetic Aperture Radar (InSAR), extensometers, or other instruments that can measure vertical displacement. The estimated SPAMS parameters are then used to model relative surface elevation over time. These parameters rely on the assumption that the conditions of the area of interest, i.e., soil stratigraphy, ground water management, and land use, remain the same over time.<br>This repository provides the so-called SPAMS10 parameters over the Krimpenerwaard region in the Netherlands. The SPAMS10 dataset includes:the scaling factor of precipitation: xP [-], see [1]the scaling factor of evapotranspiration: xE [-], see[1]the irreversible subsidence rate: xI [mm/day], see [1]the integration time: tau [days], see [1]the variance of xP: var_xP,the variance of xE: var_xE,the variance of xI: var_xI,the covariance between xP and xE: cov_xPxE,the covariance between xP and xI: cov_xPxI, andand the covariance between xE and xI: cov_xExI.<br>Each set of 10 SPAMS parameters in the dataset refers to a single parcel, including the geolocation of its center-of-mass and relevant contextual information for each parcel. The contextual information includes the ID of the closest meteorological station and the soil code describing the shallow soil type. The meteorological data is provided by the Royal Netherlands Meteorological Institute (KNMI), and details about soil code can be accessed through the basisregistratie ondergrond (BRO—PDOK).<br>The dataset is stored in a parquet data format. In addition, the JSON file provides the metadata related to this dataset. The GitHub repository provides an example script on how to read and model relative surface elevation changes using SPAMS parameters provided in this SPAMS10 dataset.<br>[1] Conroy, P., S. A. N. van Diepen and R. F. Hanssen, "SPAMS: A new empirical model for soft soil surface displacement based on meteorological input data", Geoderma, vol. 440, pp. 1-4, 2023, https://doi.org/10.1016/j.geoderma.2023.116699.
DOI: 10.21227/jgxc-5e85
title: S5P2PM

description: Data associated with the article: "PM2.5 Retrieval with Sentinel-5P Data over Europe Exploiting Deep Learning"This dataset provides pre-processed Sentinel-5P imagery reprojected onto the CAMS grid for PM2.5 estimation. Each sample contains the first 60 principal components extracted from the Sentinel-5P spectral bands, excluding the UV range, after applying Principal Component Analysis (PCA). The final band in each sample represents the PM2.5 concentration values obtained from the CAMS dataset. The dataset is divided into four subsets: training, validation, testing, and generalization, enabling the evaluation of deep learning models under different conditions. Training and validation data are provided in 32×32 pixel patches. This dataset supports research in air quality monitoring and deep learning-based PM2.5 retrieval from satellite observations.
DOI: 10.15468/dd.xu8gr9
title: Distribution records of Bolinichthys supralateralis

description: These records of Bolinichthys supralateralis were downloaded from GBIF on 2019-09-11.
DOI: 10.15468/dl.kk6fhx
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "Geometry POLYGON((-75.12016 10.70915,-75.11759 10.70915,-75.11759 10.71088,-75.12016 10.71088,-75.12016 10.70915))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004160-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bk8fqy
title: Occurrence Download

description: A dataset containing 408057 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-62 -27,-40 -27,-40 -1,-62 -1,-62 -27))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Hymenoptera"
 ]
}

 The dataset includes 408057 records from 231 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0004144-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dd.3g235f
title: Distribution records of Diaphus meadi

description: These records of Diaphus meadi were downloaded from GBIF on 2019-09-11.
DOI: 10.15156/bio/sh1163700.10fu
title: SH1163700.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163703.10fu
title: SH1163703.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163705.10fu
title: SH1163705.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163706.10fu
title: SH1163706.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163708.10fu
title: SH1163708.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1163710.10fu
title: SH1163710.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.