cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14798993
title: Code and Data: Generic Multimodal Spatially Graph Network for Spatially Embedded Network Representation Learning (GMu-SGCN)

description: Abstract

Spatially embedded networks (SENs) represent a special type of complex graph, whose topologies are constrained by the networks' embedded spatial environments. The graph representation of such networks is thereby influenced by the embedded spatial features of both nodes and edges. Accurate network representation of the graph structure and graph features is a fundamental task for various graph-related tasks. In this study, a Generic Multimodal Spatially Graph Convolutional Network (GMu-SGCN) is developed for efficient representation of spatially embedded networks. The developed GMu-SGCN model has the ability to learn the node connection pattern via multimodal node and edge features. In order to evaluate the developed model, a river network dataset and a power network dataset have been used as test beds. The river network represents the naturally developed SENs, whereas the power network represents a man-made network. Both types of networks are heavily constrained by the spatial environments and uncertainties from nature. Comprehensive evaluation analysis shows the developed GMu-SGCN can improve accuracy of the edge existence prediction task by 37.1% compared to a GraphSAGE model which only considers the node's position feature in a power network test bed. Our model demonstrates the importance of considering the multidimensional spatial feature for spatially embedded network representation.

Content

The folder contains the codes and dataset used for the paper "Generic Multimodal Spatially Graph Convolutional Network (GMu-SGCN)" arXiv:2502.00530
DOI: 10.5281/zenodo.14798994
title: Code and Data: Generic Multimodal Spatially Graph Network for Spatially Embedded Network Representation Learning (GMu-SGCN)

description: Abstract

Spatially embedded networks (SENs) represent a special type of complex graph, whose topologies are constrained by the networks' embedded spatial environments. The graph representation of such networks is thereby influenced by the embedded spatial features of both nodes and edges. Accurate network representation of the graph structure and graph features is a fundamental task for various graph-related tasks. In this study, a Generic Multimodal Spatially Graph Convolutional Network (GMu-SGCN) is developed for efficient representation of spatially embedded networks. The developed GMu-SGCN model has the ability to learn the node connection pattern via multimodal node and edge features. In order to evaluate the developed model, a river network dataset and a power network dataset have been used as test beds. The river network represents the naturally developed SENs, whereas the power network represents a man-made network. Both types of networks are heavily constrained by the spatial environments and uncertainties from nature. Comprehensive evaluation analysis shows the developed GMu-SGCN can improve accuracy of the edge existence prediction task by 37.1% compared to a GraphSAGE model which only considers the node's position feature in a power network test bed. Our model demonstrates the importance of considering the multidimensional spatial feature for spatially embedded network representation.

Content

The folder contains the codes and dataset used for the paper "Generic Multimodal Spatially Graph Convolutional Network (GMu-SGCN)" arXiv:2502.00530
DOI: 10.15468/dl.p66mh9
title: Occurrence Download

description: A dataset containing 6927 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "License is one of (CC-BY 4.0, CC-BY-NC 4.0)",
 "OccurrenceStatus is Present",
 "TaxonKey is Vitex negundo L."
 ]
}

 The dataset includes 6927 records from 105 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011432-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14800464
title: Comprehensive Dataset of Fusion Therapy Using ARMin 5 Rehabilitation Robot: Electromyography and Kinematic Data from Able-Bodied Individuals and Stroke Patients

description: This dataset contains synchronized muscle activity data (Electromyography, EMG) and arm angle measurements (acquired using the Optitrack System) from two separate studies: the Able-Bodied Participant Study (84-04) and the Stroke Patient Study (05, 06, 07). The dataset is organized by different study movements and conditions, capturing detailed information on each movement repetition.

For each movement, the dataset provides synchronized EMG data (which reflects muscle activity) alongside the corresponding arm angle data (which records the position of the arm during the movement). This data was collected across various repetitions, offering a comprehensive look at how muscle activity and arm movement angles change over time, under both typical (able-bodied) and impaired (stroke patient) conditions.

The dataset is structured to facilitate analysis of both group-specific patterns and movement-specific dynamics, supporting research into motor control, rehabilitation, and the effects of stroke on movement coordination.
DOI: 10.5281/zenodo.14800465
title: Comprehensive Dataset of Fusion Therapy Using ARMin 5 Rehabilitation Robot: Electromyography and Kinematic Data from Able-Bodied Individuals and Stroke Patients

description: This dataset contains synchronized muscle activity data (Electromyography, EMG) and arm angle measurements (acquired using the Optitrack System) from two separate studies: the Able-Bodied Participant Study (84-04) and the Stroke Patient Study (05, 06, 07). The dataset is organized by different study movements and conditions, capturing detailed information on each movement repetition.

For each movement, the dataset provides synchronized EMG data (which reflects muscle activity) alongside the corresponding arm angle data (which records the position of the arm during the movement). This data was collected across various repetitions, offering a comprehensive look at how muscle activity and arm movement angles change over time, under both typical (able-bodied) and impaired (stroke patient) conditions.

The dataset is structured to facilitate analysis of both group-specific patterns and movement-specific dynamics, supporting research into motor control, rehabilitation, and the effects of stroke on movement coordination.
DOI: 10.15468/dl.33nzy4
title: Occurrence Download

description: A dataset containing 1875581 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lamium L."
 ]
}

 The dataset includes 1875581 records from 3953 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011411-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/nbe3s4
title: New Species And New Records Of Ichneumon Wasps From The Eastern Mediterranean And The Black Sea Regions (Hymenoptera: Ichneumonidae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Vas, Zoltán (2019): New Species And New Records Of Ichneumon Wasps From The Eastern Mediterranean And The Black Sea Regions (Hymenoptera: Ichneumonidae). Acta Zoologica Academiae Scientiarum Hungaricae 65 (1): 19-30, DOI: 10.17109/AZH.65.1.19.2019
DOI: 10.5281/zenodo.15165597
title: 2-year cGPS time series following the 2021 Maduo earthquake

description: The dataset includes the 2-year cGPS-derived postseismic displacements following the 2021 Maduo earthquake in Qinghai province, China. The tectonic deformations  are removed from the original GPS time series. Pre-earthquake observations are contained in some of the cGPS data.
DOI: 10.5281/zenodo.15165598
title: 2-year cGPS time series following the 2021 Maduo earthquake

description: The dataset includes the 2-year cGPS-derived postseismic displacements following the 2021 Maduo earthquake in Qinghai province, China. The tectonic deformations  are removed from the original GPS time series. Pre-earthquake observations are contained in some of the cGPS data.
DOI: 10.15468/dl.sjsapt
title: Occurrence Download

description: A dataset containing 190280 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Occurrence records of southern African aquatic biodiversity"
 ]
}

 The dataset includes 190280 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007811-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/aajpir
title: Replication Data for: Carbon Disclosure and Corporate Value: A Scientometric Review Based on CiteSpace

description: &lt;p&gt;&lt;strong&gt;Data Description:&lt;/strong&gt;&lt;/p&gt;

&lt;p&gt;This study is based on a dataset of &lt;strong&gt;143 peer-reviewed articles&lt;/strong&gt; published between &lt;strong&gt;2012 and 2025&lt;/strong&gt;, focusing on the relationship between &lt;em&gt;carbon disclosure&lt;/em&gt; and &lt;em&gt;corporate value&lt;/em&gt;.&lt;/p&gt;

&lt;p&gt;The bibliometric data were retrieved from &lt;strong&gt;Web of Science Core Collection&lt;/strong&gt;, using a comprehensive search strategy that incorporated relevant keywords such as &lt;em&gt;“carbon disclosure”, “carbon reporting”, “corporate value”, “firm performance”&lt;/em&gt;, and &lt;em&gt;“sustainability”&lt;/em&gt;.&lt;/p&gt;

&lt;p&gt;Data analysis was conducted using &lt;strong&gt;CiteSpace&lt;/strong&gt;, a widely used bibliometric visualization tool. Through co-citation, keyword co-occurrence, and clustering analyses, the study reveals the knowledge structure and emerging trends in the literature.&lt;/p&gt;

&lt;p&gt;The dataset includes information on:&lt;/p&gt;
&lt;ul&gt;
 &lt;li&gt;&lt;strong&gt;Publication year&lt;/strong&gt; (2012–2025)&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Authors&lt;/strong&gt; and &lt;strong&gt;affiliations&lt;/strong&gt;&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Journals&lt;/strong&gt; and &lt;strong&gt;citations&lt;/strong&gt;&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Keywords&lt;/strong&gt; and &lt;strong&gt;research themes&lt;/strong&gt;&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Collaboration networks&lt;/strong&gt; (institutional and regional)&lt;/li&gt;
&lt;/ul&gt;

&lt;p&gt;The final dataset was cleaned and validated to remove duplicates and ensure the accuracy of bibliometric indicators.&lt;/p&gt;
DOI: 10.5281/zenodo.15731475
title: DLVS3-HST Pose Estimation Dataset

description: The DLVS3-HST dataset is a large-scale, physically-based synthetic image collection designed to advance deep learning and computer vision research in satellite pose estimation. It features over 640,000 high-resolution images of the Hubble Space Telescope (HST), each rendered with accurate lighting, realistic material properties, and comprehensive ground-truth annotations. The dataset includes precise 6-DoF pose information, 37 keypoint locations per image, and additional pixel-level data such as segmentation masks, depth maps, and surface normals.

DLVS3 was developed to address the scarcity of real-world annotated space imagery and to support the development and benchmarking of robust, generalizable algorithms for autonomous spacecraft operations, rendezvous, servicing, and debris removal. The dataset leverages advanced rendering pipelines and domain randomization to ensure diversity and realism, hopefully making it a foundational resource for both academic research and industrial applications in vision-based navigation.

A small portion of the dataset is available here for direct download. It contains 100 multilayer 16-bit floating HDR EXR and 10,000 post-processed panchromatic PNG images.

For access to the complete dataset (approx. 3.2 TB), please read the licence and register at:https://mi.services/dlvs3-hst-dataset-access/
DOI: 10.5281/zenodo.15731476
title: DLVS3-HST Pose Estimation Dataset

description: The DLVS3-HST dataset is a large-scale, physically-based synthetic image collection designed to advance deep learning and computer vision research in satellite pose estimation. It features over 640,000 high-resolution images of the Hubble Space Telescope (HST), each rendered with accurate lighting, realistic material properties, and comprehensive ground-truth annotations. The dataset includes precise 6-DoF pose information, 37 keypoint locations per image, and additional pixel-level data such as segmentation masks, depth maps, and surface normals.

DLVS3 was developed to address the scarcity of real-world annotated space imagery and to support the development and benchmarking of robust, generalizable algorithms for autonomous spacecraft operations, rendezvous, servicing, and debris removal. The dataset leverages advanced rendering pipelines and domain randomization to ensure diversity and realism, hopefully making it a foundational resource for both academic research and industrial applications in vision-based navigation.

A small portion of the dataset is available here for direct download. It contains 100 multilayer 16-bit floating HDR EXR and 10,000 post-processed panchromatic PNG images.

For access to the complete dataset (approx. 3.2 TB), please read the licence and register at:https://mi.services/dlvs3-hst-dataset-access/
DOI: 10.15468/dl.knd6n6
title: Occurrence Download

description: A dataset containing 440293 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Accipitriformes",
 "Year 1981-1990"
 ]
}

 The dataset includes 440293 records from 299 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0068323-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.79fdc7
title: Occurrence Download

description: A dataset containing 128022 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Fauna registrada mediante cámaras trampa en el marco del proyecto Expedición del Oso Palmero en el departamento del Casanare"
 ]
}

 The dataset includes 128022 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001204-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5517/ccdc.csd.cc2k68rt
title: CCDC 2359526: Experimental Crystal Structure Determination

description: Related Article: Xiangyu Liu, Jing Liu, Danlei Zhu, Xinghua Yan, Jiawei Chen, Lian Duan, Yuetong Kang, Dongxin Ma|2024|J.Am.Chem.Soc.|146|29955|doi:10.1021/jacs.4c12454
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.cc2k6dz5
title: CCDC 2359657: Experimental Crystal Structure Determination

description: Related Article: Mª Ángeles García-Monforte, Miguel Baya, Antonio Martín, Babil Menjón|2024|J.Organomet.Chem.|1022|123385|doi:10.1016/j.jorganchem.2024.123385
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.cc2k6f07
title: CCDC 2359658: Experimental Crystal Structure Determination

description: Related Article: Mª Ángeles García-Monforte, Miguel Baya, Antonio Martín, Babil Menjón|2024|J.Organomet.Chem.|1022|123385|doi:10.1016/j.jorganchem.2024.123385
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.cc2k6f18
title: CCDC 2359659: Experimental Crystal Structure Determination

description: Related Article: Mª Ángeles García-Monforte, Miguel Baya, Antonio Martín, Babil Menjón|2024|J.Organomet.Chem.|1022|123385|doi:10.1016/j.jorganchem.2024.123385
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.cc2kb5fj
title: CCDC 2363267: Experimental Crystal Structure Determination

description: Related Article: Benjamin Wittwer, Florian Hett, Michael Seidl, Stephan Hohloch|2024|Inorg.Chem.|63|20448|doi:10.1021/acs.inorgchem.4c02897
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.cc2kb5hl
title: CCDC 2363269: Experimental Crystal Structure Determination

description: Related Article: Benjamin Wittwer, Florian Hett, Michael Seidl, Stephan Hohloch|2024|Inorg.Chem.|63|20448|doi:10.1021/acs.inorgchem.4c02897
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.cc2kstry
title: CCDC 2377351: Experimental Crystal Structure Determination

description: Related Article: Jagajiban Sendh, Jubaraj B. Baruah|2024|RSC Advances|14|31598|doi:10.1039/D4RA06309K
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.cc2flbw8
title: CCDC 2251960: Experimental Crystal Structure Determination

description: Related Article: K. Inoue, S. Nakami, M. Kumasaki, S. Matsumoto|2024|Acta Crystallogr.,Sect.E:Cryst.Commun.|80|1161|doi:10.1107/S2056989024009265
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.te87c8
title: Occurrence Download

description: A dataset containing 452075 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Anolis Daudin, 1802"
 ]
}

 The dataset includes 452075 records from 686 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001311-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.pgerse
title: Occurrence Download

description: A dataset containing 301869 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 2024-10-12",
 "EventDate is less than or equal to 2024-11-11",
 {
 "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)"
 ]
 }
 }
 ]
}

 The dataset includes 301869 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001210-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zpu4v4
title: Occurrence Download

description: A dataset listing the 12 species recorded in GBIF matching the query:
{
 "and" : [
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "TaxonKey is Cyanosporus McGinty, 1909"
 ]
}

 The dataset's 12 records were derived from 59 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001321-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ssfea6
title: Occurrence Download

description: A dataset containing 12160119 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is Ecuador"
 ]
}

 The dataset includes 12160119 records from 1909 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001313-241106120511685/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/5p2atq
title: Données naturalistes opportunistes issues de la plateforme INaturalist-Données naturalistes opportunistes "lubie"

description: Données naturalistes opportunistes saisies sur iNaturalist à partir du compte "lubie"
DOI: 10.15468/dl.f9qzfw
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Amphibia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((67.5 -7.5,75 -7.5,75 0,67.5 0,67.5 -7.5))"
 ]
}

 The dataset includes 23 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041379-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8gmppz
title: Occurrence Download

description: A dataset containing 6921 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Amphibia)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Geometry POLYGON((105 7.5,112.5 7.5,112.5 15,105 15,105 7.5))"
 ]
}

 The dataset includes 6921 records from 23 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0041381-251009101135966/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.