cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.3rax9g
title: Occurrence Download

description: A dataset containing 1147 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lophiolepis morisiana (Rchb.fil.) Del Guacchio, Bures, Iamonico & P.Caputo",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1147 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001333-240202131308920/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bx8lwb
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Côte d’Ivoire",
 "TaxonKey is Croton mubango Müll.Arg."
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022682-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dnecdr
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus rubicundus Podlech & Sytin"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036221-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3qynw
title: Occurrence Download

description: A dataset containing 9926 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepidochelys olivacea (Eschscholtz, 1829)"
 ]
}

 The dataset includes 9926 records from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022701-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3bl8wp
title: Occurrence Download

description: A dataset containing 862 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "Country is China",
 "Country is Hong Kong",
 "Country is Indonesia",
 "Country is India",
 "Country is Belgium"
 ]
 },
 "TaxonKey is Vespa velutina Lepeletier, 1836"
 ]
}

 The dataset includes 862 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0022708-190621201848488/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ak8yux
title: Occurrence Download

description: A dataset containing 461 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sachatamia albomaculata (Taylor, 1949)"
 ]
}

 The dataset includes 461 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0133028-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sdapm8
title: Occurrence Download

description: A dataset containing 1647632 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Phaeophyceae"
 ]
}

 The dataset includes 1647632 records from 980 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0082273-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14029383
title: Raw data of the measurements and simulations of the dump leakage calorimeter

description: Raw data of the measurements and simulations of the dump leakage calorimeter of DESY. The analysis can be found on Github (https://github.com/ivoschulthess/dumpLeakageCalorimeter and https://doi.org/10.5281/zenodo.15281065).
DOI: 10.5281/zenodo.14029384
title: Raw data of the measurements and simulations of the dump leakage calorimeter

description: Raw data of the measurements and simulations of the dump leakage calorimeter of DESY. The analysis can be found on Github (https://github.com/ivoschulthess/dumpLeakageCalorimeter and https://doi.org/10.5281/zenodo.15281065).
DOI: 10.15468/dl.bkhahp
title: Occurrence Download

description: A dataset containing 25 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Bryophyte herbarium TRH, NTNU University Museum",
 "Country is Croatia"
 ]
}

 The dataset includes 25 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050656-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wpx3ts
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Vascular plant herbarium, The Arctic University Museum of Norway (TROM)",
 "Country is Croatia"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050659-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ww54v9
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ophioglossum lancifolium C.Presl",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.7576 -24.3688,20.529 -24.0715,20.509 -24.0715,20.509 -28.5786,25.5395 -28.5786,25.5395 -24.0715,25.1306 -24.0715,24.9333 -24.4571,23.8962 -24.2467,22.8065 -24.295,22.3719 -24.7207,22.2323 -25.547,22.0387 -25.7188,21.7833 -25.7784,21.5388 -25.7113,21.3553 -25.5415,20.7576 -24.3688))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050660-250525065834625/datasets/export for details.
DOI: 10.5281/zenodo.15281124
title: Data from: Methodological validation and inter-site analysis in Late Bronze and Early Iron Age cremations using tooth cementum annulation

description: Most TCA studies have been conducted on contemporary materials from individuals of known calendar age and sex who underwent tooth extraction in dental clinics. Only a few studies have been undertaken on archaeological human skeletal remains and occasionally on cremated remains. 62 cremated tooth roots from 60 individuals from eight Lusatian Urnfield Culture cemeteries from SW Poland were studied. Based on analyses of 292 undecalcified slides with an average thickness of 36.1 µm embedded in methyl methacrylate  resin, tests were carried out to estimate the age at death of individuals using the tooth cementum annulation (TCA) technique and, for slides with insufficient incremental lines of Salter counts (ILSc) identification, the incremental lines of Salter width (ILSw) parameter and the of acellular extrinsic fiber cementum thickness to line width (AEFCt/ILSw) ratio were introduced. The intra-observer error of repeatability of ILSc was 18.3%, while the inter-observer error was 29.6%. The expected statistically significant differences in AEFCt (P=0.0027) and an increase in ILSc (P=0.0068) with the ageing of individuals were shown. The TCA age corresponded with the individuals’ morphological age and with the age estimated based on AEFCt/ILSw ratio. The phenomenon of partial multiplication of the number of ILS was identified in two individuals. No differences in the ILSw were found within different parts of the dental root or between individuals of various ages and sexes. Differences in ILSw between individuals from different cemeteries proved to be statistically significant (P<0.001). Considering the absence of analogous studies, the explanation for this variation is multifaceted and may relate to genetic, ecological, nutritional and disease differences.
DOI: 10.5281/zenodo.15281125
title: Data from: Methodological validation and inter-site analysis in Late Bronze and Early Iron Age cremations using tooth cementum annulation

description: Most TCA studies have been conducted on contemporary materials from individuals of known calendar age and sex who underwent tooth extraction in dental clinics. Only a few studies have been undertaken on archaeological human skeletal remains and occasionally on cremated remains. 62 cremated tooth roots from 60 individuals from eight Lusatian Urnfield Culture cemeteries from SW Poland were studied. Based on analyses of 292 undecalcified slides with an average thickness of 36.1 µm embedded in methyl methacrylate  resin, tests were carried out to estimate the age at death of individuals using the tooth cementum annulation (TCA) technique and, for slides with insufficient incremental lines of Salter counts (ILSc) identification, the incremental lines of Salter width (ILSw) parameter and the of acellular extrinsic fiber cementum thickness to line width (AEFCt/ILSw) ratio were introduced. The intra-observer error of repeatability of ILSc was 18.3%, while the inter-observer error was 29.6%. The expected statistically significant differences in AEFCt (P=0.0027) and an increase in ILSc (P=0.0068) with the ageing of individuals were shown. The TCA age corresponded with the individuals’ morphological age and with the age estimated based on AEFCt/ILSw ratio. The phenomenon of partial multiplication of the number of ILS was identified in two individuals. No differences in the ILSw were found within different parts of the dental root or between individuals of various ages and sexes. Differences in ILSw between individuals from different cemeteries proved to be statistically significant (P<0.001). Considering the absence of analogous studies, the explanation for this variation is multifaceted and may relate to genetic, ecological, nutritional and disease differences.
DOI: 10.15468/rs5z6j
title: 2022-2024 FISP: Ecosystem Benefits of UK Oyster Aquaculture Sites Lindisfarne Sediment Sampling Survey

description: As part of the Fisheries Industry Science Partnerships (FISP) project 'Ecosystem Benefits of UK Oyster Aquaculture Sites' project partners Tethys Oysters Ltd. / Atlantic Edge Oysters Ltd., Envision Marine Ltd. and the University of Essex have collaborated in a research project to determine ecosystem benefits provided by oyster aquaculture by measuring biodiversity and denitrification activity at a variety of sites in England and Wales. Surveys were undertaken by ENVISION in 2023 to measure the biodiversity associated with three oyster farms and one naturalised rock oyster reef in comparison to control sites with similar environmental conditions, as well as ecosystem function (nitrification/denitrification activity) at these sites. Recognising the importance of conservation and restoration of native oyster populations, surveys were also carried out in 2022 and 2023 to measure oyster abundance and associated biodiversity at an historic native oyster site, commercially restocked with native oysters in 2021. Survey works included recording of underwater imagery, sediment sampling, oyster dredging and ecosystem function sampling. Underwater camera systems were used to record the diversity of biota around the oysters during submersion. Sediment samples were taken for measurement of diversity of macrofauna, particle size distribution and total organic carbon, and the ecosystem function testing involved sampling of sediment and swabs of oysters/hard surfaces to determine the abundance and activity of denitrifying/nitrifying microorganisms on oyster site substrates, through genomic analysis. The results of the denitrification and biodiversity services provided by oyster aquaculture were communicated to consumers, industry and decision makers to increase understanding and promote awareness of the ecosystem benefits provided by aquaculture.
DOI: 10.15468/dl.u9zw74
title: Occurrence Download

description: A dataset containing 4 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Alabama Museum of Natural History Invertebrate Zoology (Arctos)",
 "Country is Croatia"
 ]
}

 The dataset includes 4 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050662-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rpdyby
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is The lichen collection of the National Museum of Natural History, Sofia",
 "Country is Croatia"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050663-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fmxfd5
title: Occurrence Download

description: A dataset containing 12 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is Queensland Museum provider for OZCAM",
 "Country is Croatia"
 ]
}

 The dataset includes 12 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050666-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rgy4zs
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Ophioglossum lancifolium C.Presl",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((20.529 -24.0715,20.509 -24.0455,20.509 -24.0715,20.529 -24.0715))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050667-250525065834625/datasets/export for details.
DOI: 10.15468/dl.36wyqp
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((102.03044 6.2181,102.02918 6.2185,102.02811 6.21857,102.02462 6.21741,102.01997 6.21047,102.02113 6.14428,102.00414 6.07209,102.05115 6.06214,102.10096 6.12971,102.08095 6.20977,102.03044 6.2181))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (EN, CR, VU)",
 "Year 2010-2025"
 ]
}

 The dataset includes 3 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050664-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.8108971
title: CLARA Knowledge Graph of licensed educational resources (RDF-star)

description: /!\ This deposit is deprecated; a more complete version of the deposit can be found here: 8403142. /!\

CLARAThis deposit is part of the CLARA project. The CLARA project aims to empower teachers in the task of creating new educational resources. And in particular with the task of handling the licenses of reused educational resources.

The present deposit contains the RDF files created using an RDF mapping (RML-star) and a mapper (Morph-KGC). The files used as inputs can be found here. That pipeline can be found on Gitlab. The data used in that pipeline originate from X5GON, a European project aiming to generate and gather open educational resources.

ContentThe present Knowledge Graph contains information about 45K educational resources and 135K subjects (extracted from DBpedia).That information contains 



the author,

its title and description

the license,

a URL to the resource itself,

the language of the educational resource,

its mimetype,

and finally which subject it talks about, and to what extent.


That extent is given by two scores, a PageRank score and a cosinus score (that were not calculated on our graph but during the X5GON project)

A particularity of the Knowledge Graph is its heavy use of RDF reification, across large multi-valued properties.Other versions of the same deposit can be found using different reification models:



Standard reification

Named graphs

Singleton properties


The Knowledge Graph also contains categories originating from DBpedia. They help precise the subjects that are also extracted from DBpedia.

The deposit contains five types of files:



Authors_[X].nt - Those contain the authors' nodes, their type, and name.

ER_[X].ttl - Those contain the educational resources and their information using RDF-star.

categories_skos_[X].ttl - Those contain the hierarchy of DBpedia categories.

categories_labels.ttl  - This file contains additional information about the categories.

categories_article.ttl - This file contains the RDF triples that link the DBpedia subjects to the DBpedia categories.
description: This record and the related records are deprecated, move to this one for easier usability:  https://doi.org/10.5281/zenodo.8403142
DOI: 10.5281/zenodo.14738836
title: mmRadPose

description: Welcome to the official repository for our mmRadPose datatset.

A detailed explanation of the dataset is provided in the corresponding publication.

If you use our dataset, please cite the following paper:

"Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data"

LUKAS ENGEL, JONAS MUELLER , EDUARDO JAVIER FERIA RENDON, EVA DORSCHKY, DANIEL KRAUSS, INGRID ULLMANN, BJOERN M. ESKOFIER, AND MARTIN VOSSIEK 

published in IEEE Journal of Microwaves (https://ieeexplore.ieee.org/document/10904474).

L. Engel et al., "Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data," in IEEE Journal of Microwaves, doi: 10.1109/JMW.2025.3535525. keywords: {Radar;Pose estimation;Deep learning;Skeleton;Laser radar;Sensors;Radar measurements;Motion capture;Cameras;Synchronization;Human pose estimation;radar;optical motion capture;millimeter wave;target list;point cloud;machine learning;deep learning},

Datasets:

POINTCLOUDS 

The pointcloud dataset contains radar pointclouds processed from raw radar data and skeleton ground truth data.

mmRadPose_pointclouds/├── p1/                  │   ├── angle0/ # angles    │   │   ├── 0 # activities│   │   │    ├── 0 # recordings│   │   │    │    ├── skeleton.npy│   │   │    │    ├── targetlist_64.npy│   │   │    ├── 1 │   │   ├── 1│   │   ├── 2│   │   ├── ... │   │   ├── 10│   │   ├── 11│   ├── angle1/│   ├── angle2/├── p2                   ├── ... ├── p12 

RAW RADAR DATA

The raw radar data dataset contains  parsed () and cutted radar and skeleton ground truth (obained via OMC) data.

radar folder:    Contains the radar data in numpy compressed archive file format (e.g. data_cube_parsed_p1_an0_ac0_r0.npz)

skeletons folder:    Contains the skeleton GT data in numpy array file format (e.g. skeleton_p1_an0_ac0_r0.npy)

File relation:    All files have an unique ID (e.g. p1_an0_ac0_r0) to identify related radar and skeleton recordings.        ID meaning:        p X = participant X        an X = angle X        ac X = action X        r X = recording X

 

Edit:

The skeleton files contain 26 keypoints provided by the OMC. However, only 24 keypoints are used in the paper.
DOI: 10.5281/zenodo.14738837
title: mmRadPose

description: Welcome to the official repository for our mmRadPose datatset.

A detailed explanation of the dataset is provided in the corresponding publication.

If you use our dataset, please cite the following paper:

"Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data"

LUKAS ENGEL, JONAS MUELLER , EDUARDO JAVIER FERIA RENDON, EVA DORSCHKY, DANIEL KRAUSS, INGRID ULLMANN, BJOERN M. ESKOFIER, AND MARTIN VOSSIEK 

published in IEEE Journal of Microwaves (https://ieeexplore.ieee.org/document/10904474).

L. Engel et al., "Advanced Millimeter Wave Radar-Based Human Pose Estimation Enabled by a Deep Learning Neural Network Trained With Optical Motion Capture Ground Truth Data," in IEEE Journal of Microwaves, doi: 10.1109/JMW.2025.3535525. keywords: {Radar;Pose estimation;Deep learning;Skeleton;Laser radar;Sensors;Radar measurements;Motion capture;Cameras;Synchronization;Human pose estimation;radar;optical motion capture;millimeter wave;target list;point cloud;machine learning;deep learning},

Datasets:

POINTCLOUDS 

The pointcloud dataset contains radar pointclouds processed from raw radar data and skeleton ground truth data.

mmRadPose_pointclouds/├── p1/                  │   ├── angle0/ # angles    │   │   ├── 0 # activities│   │   │    ├── 0 # recordings│   │   │    │    ├── skeleton.npy│   │   │    │    ├── targetlist_64.npy│   │   │    ├── 1 │   │   ├── 1│   │   ├── 2│   │   ├── ... │   │   ├── 10│   │   ├── 11│   ├── angle1/│   ├── angle2/├── p2                   ├── ... ├── p12 

RAW RADAR DATA

The raw radar data dataset contains  parsed () and cutted radar and skeleton ground truth (obained via OMC) data.

radar folder:    Contains the radar data in numpy compressed archive file format (e.g. data_cube_parsed_p1_an0_ac0_r0.npz)

skeletons folder:    Contains the skeleton GT data in numpy array file format (e.g. skeleton_p1_an0_ac0_r0.npy)

File relation:    All files have an unique ID (e.g. p1_an0_ac0_r0) to identify related radar and skeleton recordings.        ID meaning:        p X = participant X        an X = angle X        ac X = action X        r X = recording X

 

Edit:

The skeleton files contain 26 keypoints provided by the OMC. However, only 24 keypoints are used in the paper.