cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc2ffk0g
title: CCDC 2247345: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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.cc2ffk1h
title: CCDC 2247346: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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.cc2ffk2j
title: CCDC 2247347: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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.cc2ffk3k
title: CCDC 2247348: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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.cc2ffk5m
title: CCDC 2247350: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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.cc2ffk6n
title: CCDC 2247351: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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: 10.5281/zenodo.8039185
title: AusLAB

description: Dataset provided alongside the report entitled "BANCAL22: A Probabilistic Algorithm for Bayesian Anelasticity Model Calibration" for Geoscience Australia, for the purposes of inferring Australian lithosphere-asthenosphere boundary (LAB) depth. This set of BANCAL22_samples can be placed inside AusLAB -&gt; infer_LAB -&gt; data_input (https://github.com/JamesHazzard/AusLAB), in order to use the set of samples as an input data set for generation of LAB depth maps. The BANCAL22_samples contained within this repository were generated using BANCAL22 (https://github.com/JamesHazzard/BANCAL22).
DOI: 10.5517/ccdc.csd.cc2fgk1j
title: CCDC 2248307: Experimental Crystal Structure Determination

description: Related Article: Mengyuan Hou, Yahao Wang, Puhui Li, Xingxing Ma, Guan Zhang, Qiuling Song|2023|Org.Lett.|25|4038|doi:10.1021/acs.orglett.3c01190
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: 10.7936/6rxs-103633
title: Experimental observation of the breakdown products of SO2 by electrical discharge under the conditions relevant to the Venus cloud layer and the implication for Venus UV observation [dataset]

description: Sulfur-containing species are suggested as the UV absorbers in Venus’s atmosphere, which can be generated by photochemistry or electrochemistry. Here we report an electrical discharge experiment in the mixtures of SO2 with SO2 + N2, under the conditions relevant to the Venus cloud layer. We directly observed the primary breakdown products of SO2 as free radicals SO*, SI*, SII*, S2*, OI*, OII*; and the stable ending products as S8 particles and H2SO4 droplets. The observation of these products in a short-duration (minutes) experiment implies the formation of short-lived intermediate phases, including (SO)2 and polysulfur, as recognized candidates for the 2nd UV absorber. The simultaneous occurrence of SO* and S2* under all experimental conditions indicates an equal probability for two reaction paths and two groups of products. Compared with photochemistry, the high yields of electrochemistry could be responsible for the inhomogeneous distribution and temporal changes of UV features in Venus images observed by ground-based telescopes and spacecraft.
DOI: 10.5281/zenodo.8039449
title: AusLAB

description: Dataset provided alongside the report entitled "BANCAL22: A Probabilistic Algorithm for Bayesian Anelasticity Model Calibration" for Geoscience Australia, for the purposes of inferring Australian lithosphere-asthenosphere boundary (LAB) depth. This set of BANCAL22_samples can be placed inside AusLAB -&gt; infer_LAB -&gt; data_input (https://github.com/JamesHazzard/AusLAB), in order to use the set of samples as an input data set for generation of LAB depth maps. The BANCAL22_samples contained within this repository were generated using BANCAL22 (https://github.com/JamesHazzard/BANCAL22).
DOI: 10.5281/zenodo.8039184
title: AusLAB

description: Dataset provided alongside the report entitled "BANCAL22: A Probabilistic Algorithm for Bayesian Anelasticity Model Calibration" for Geoscience Australia, for the purposes of inferring Australian lithosphere-asthenosphere boundary (LAB) depth. This set of BANCAL22_samples can be placed inside AusLAB -&gt; infer_LAB -&gt; data_input (https://github.com/JamesHazzard/AusLAB), in order to use the set of samples as an input data set for generation of LAB depth maps. The BANCAL22_samples contained within this repository were generated using BANCAL22 (https://github.com/JamesHazzard/BANCAL22).
DOI: 10.6084/m9.figshare.23515692
title: README.md

description: The fMRI and behavioral data, predictive models, and codes that were used in training and testing predictive models and generating main findings and figures will be shared upon publication.
DOI: 10.6084/m9.figshare.23515692.v1
title: README.md

description: The fMRI and behavioral data, predictive models, and codes that were used in training and testing predictive models and generating main findings and figures will be shared upon publication.
DOI: 10.6084/m9.figshare.23515692.v2
title: Brain Representations of Affective Valence and Intensity in Sustained Pleasure and Pain

description: The fMRI and behavioral data, predictive models, and codes that were used in training and testing predictive models and generating main findings and figures will be shared upon publication.
DOI: 10.17909/wmbn-6n48
title: WASP-31b: TESS Sector 9

description: TESS Sector 9 observations of WASP-31b
DOI: 10.5281/zenodo.8039089
title: List of SHARAD type-III burst candidate based on cross-detections with STEREO and Wind

description: Complete list of SHARAD type-III burst candidate based on cross-detections with STEREO and Wind, including products in which a burst was not seen.
DOI: 10.5281/zenodo.8030683
title: Datasets used in "Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management"

description: Data sets used to train, validate, and test machine learning models for the prediction of 10-hour dead fuel moisture content. The data sets are for 375 m and 1 km resolutions. MADIS climatography data is also included. The datasets may be processed using the code supplied at https://github.com/NCAR/fmc_viirs.
DOI: 10.25740/wc461hp2261
title: David Rumsey Map Collection Text on Maps Data [Version 2]

description: This data package contains datasets of text on maps recognized from a georeferenced subset of ~57k historical maps from the David Rumsey Map Collection. It includes files for different versions of the dataset accompanied by Data Sheets and this Cover Sheet. Each dataset was created with the \\textit{mapKurator} software library and contains all instances of text as it was automatically identified on a single, physical map sheet, or a composite of sheets. Each text identified by \\textit{mapKurator} is saved as a polygon json `Feature` with geospatial coordinates for 16 vertices and has the following properties: `text` (the \\textit{mapKurator} predicted transcription of the text within the polygon), `score` (the confidence score for the text detection), `postocr\\_label` (a prediction for a normalized version of `text` that is based on a post-processing step), and `img\\_coordinates` (the pixel coordinates of the polygon). This data has not been verified or evaluated in any way and will contain significant errors, both in terms of false positives (map features recognized as text, but which are not in fact text), (missing) false negatives (text that \\textit{mapKurator} has failed to recognize), incorrect detection (bounding polygons that do not correctly enclose a word), and incorrect recognition (the transcription of the text contains errors). Please see the Data Sheet for each version for more details."
DOI: 10.5281/zenodo.8030682
title: Datasets used in "Machine Learning and VIIRS Satellite Retrievals for Skillful Fuel Moisture Content Monitoring in Wildfire Management"

description: Data sets used to train, validate, and test machine learning models for the prediction of 10-hour dead fuel moisture content. The data sets are for 375 m and 1 km resolutions. MADIS climatography data is also included. The datasets may be processed using the code supplied at https://github.com/NCAR/fmc_viirs.
DOI: 10.57745/wjcfhk
title: QuestSWYM_EN.pdf

description: Questionnaire for the survey on bathing risks
DOI: 10.17909/8v7h-en48
title: WASP-31b: TESS Sector 9

description: TESS Sector 9 observations of WASP-31b
DOI: 10.5517/ccdc.csd.cc2fs7wc
title: CCDC 2257633: Experimental Crystal Structure Determination

description: Related Article: Huixian Miao, Pingping Wang, Luying Liu, Zetao Huang, Wenjiang Zhaxi, Wei Huang, Dayu Wu|2023|J.Solid State Chem.|324|124098|doi:10.1016/j.jssc.2023.124098
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.cc2fs7xd
title: CCDC 2257634: Experimental Crystal Structure Determination

description: Related Article: Huixian Miao, Pingping Wang, Luying Liu, Zetao Huang, Wenjiang Zhaxi, Wei Huang, Dayu Wu|2023|J.Solid State Chem.|324|124098|doi:10.1016/j.jssc.2023.124098
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: 10.5281/zenodo.7897996
title: WikiCausal Corpus for Evaluation of Causal Knowledge Graph Construction

description: Documentation on the data format and how it can be used can be found on: https://github.com/IBM/wikicausal as well as our paper: <pre><code>@unpublished{, author = {Oktie Hassanzadeh and Mark Feblowitz}, title = {{WikiCausal}: Corpus and Evaluation Framework for Causal Knowledge Graph Construction}, year = {2023}, doi = {10.5281/zenodo.7897996} }</code></pre> <pre>Corpus derived from Wikipedia and Wikidata. Refer to Wikipedia and Wikidata license and terms of use for more details:</pre> <strong>Permission is granted</strong> to copy, distribute and/or modify Wikipedia's text under the terms of the Creative Commons Attribution-ShareAlike 3.0 Unported License and, <em>unless otherwise noted</em>, the GNU Free Documentation License, unversioned, with no invariant sections, front-cover texts, or back-cover texts. A copy of the Creative Commons Attribution-ShareAlike 3.0 Unported License is included in the section entitled "Wikipedia:Text of Creative Commons Attribution-ShareAlike 3.0 Unported License" A copy of the GNU Free Documentation License is included in the section entitled "GNU Free Documentation License". Content on Wikipedia is covered by disclaimers. <pre>THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</pre>
DOI: 10.57745/tkrkzc
title: QuestSWYM_EN.pdf

description: Questionnaire for the survey on bathing risks
DOI: 10.5281/zenodo.7897995
title: WikiCausal Corpus for Evaluation of Causal Knowledge Graph Construction

description: Documentation on the data format and how it can be used can be found on: https://github.com/IBM/wikicausal as well as our paper: <pre><code>@unpublished{, author = {Oktie Hassanzadeh and Mark Feblowitz}, title = {{WikiCausal}: Corpus and Evaluation Framework for Causal Knowledge Graph Construction}, year = {2023}, doi = {10.5281/zenodo.7897996} }</code></pre> <pre>Corpus derived from Wikipedia and Wikidata. Refer to Wikipedia and Wikidata license and terms of use for more details:</pre> <strong>Permission is granted</strong> to copy, distribute and/or modify Wikipedia's text under the terms of the Creative Commons Attribution-ShareAlike 3.0 Unported License and, <em>unless otherwise noted</em>, the GNU Free Documentation License, unversioned, with no invariant sections, front-cover texts, or back-cover texts. A copy of the Creative Commons Attribution-ShareAlike 3.0 Unported License is included in the section entitled "Wikipedia:Text of Creative Commons Attribution-ShareAlike 3.0 Unported License" A copy of the GNU Free Documentation License is included in the section entitled "GNU Free Documentation License". Content on Wikipedia is covered by disclaimers. <pre>THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.</pre>
DOI: 10.5281/zenodo.8039443
title: PubGraph: A Large-Scale Scientific Knowledge Graph

description: We present PubGraph, a new resource for studying scientific progress that takes the form of a large-scale knowledge graph (KG) with more than 385M entities, 13B main edges, and 1.5B qualifier edges. PubGraph is comprehensive and unifies data from various sources, including Wikidata, OpenAlex, and Semantic Scholar, using the Wikidata ontology. Beyond the metadata available from these sources, PubGraph includes outputs from auxiliary community detection algorithms and large language models. To further support studies on reasoning over scientific networks, we create several large-scale benchmarks extracted from PubGraph for the core task of knowledge graph completion (KGC). These benchmarks present many challenges for knowledge graph embedding models, including an adversarial community-based KGC evaluation setting, zero-shot inductive learning, and large-scale learning. All of the aforementioned resources are accessible at https://purl.archive.org/pubgraph and released under the CC-BY-SA license. We plan to update PubGraph quarterly to accommodate the release of new publications.
description: Given the sheer size of the dataset (&gt; 2.2TB), this repository only holds the code for extracting the KG, the data itself can be accessed through the provided PURL.
DOI: 10.5281/zenodo.8039442
title: PubGraph: A Large-Scale Scientific Knowledge Graph

description: We present PubGraph, a new resource for studying scientific progress that takes the form of a large-scale knowledge graph (KG) with more than 385M entities, 13B main edges, and 1.5B qualifier edges. PubGraph is comprehensive and unifies data from various sources, including Wikidata, OpenAlex, and Semantic Scholar, using the Wikidata ontology. Beyond the metadata available from these sources, PubGraph includes outputs from auxiliary community detection algorithms and large language models. To further support studies on reasoning over scientific networks, we create several large-scale benchmarks extracted from PubGraph for the core task of knowledge graph completion (KGC). These benchmarks present many challenges for knowledge graph embedding models, including an adversarial community-based KGC evaluation setting, zero-shot inductive learning, and large-scale learning. All of the aforementioned resources are accessible at https://purl.archive.org/pubgraph and released under the CC-BY-SA license. We plan to update PubGraph quarterly to accommodate the release of new publications.
description: Given the sheer size of the dataset (&gt; 2.2TB), this repository only holds the code for extracting the KG, the data itself can be accessed through the provided PURL.
DOI: 10.5281/zenodo.8039441
title: OntoMaturity Specification

description: Material used as a basis for building the OntoMaturity ontology.
DOI: 10.5281/zenodo.8039440
title: OntoMaturity Specification

description: Material used as a basis for building the OntoMaturity ontology.
DOI: 10.5281/zenodo.8039344
title: BRACE: A Bayesian-based dimension reduction approach for single-cell alternative splicing analysis

description: Datasets to demonstrate the utility of our BRACE method.
DOI: 10.5281/zenodo.8039343
title: BRACE: A Bayesian-based dimension reduction approach for single-cell alternative splicing analysis

description: Datasets to demonstrate the utility of our BRACE method.
DOI: 10.5066/p9unjqeo
title: Results from U.S. Geological Survey Environmental Health Food Resources Lifecycle Integrated Science Team, Graton Pesticides (GRAPE) Study, in Graton, California, April&amp;amp;ndash;May 2021

description: In the spring of 2021, six households with private wells were selected throughout Graton, California, based on proximity to agriculture (within one mile of agriculture), well depth (i.e., less than 150 feet in depth), and well type (i.e., dug versus drilled). Silicone bands were deployed for 30 days at outdoor locations at each household to passively sample pesticides in ambient air. On May 3, 2021, the silicone bands were retrieved and outdoor water samples (i.e., spigot on the side of the house) and indoor tap water samples (i.e., kitchen faucet used for drinking water) were collected and analyzed for 187 pesticides, 57 potential hormonally active chemicals, and estrogenicity. This study was a citizen science effort and samples were collected by individual homeowners with provided sampling kits.
DOI: 10.6084/m9.figshare.20448579
title: Supplementary files for paper, whole sequences, domain sequences, alignments (SBH and SLD)

description: The files attached are the domain sequenes, the full length sequences, and the alignments used for the phylogenetic trees of the SBH and SLD domains: <br> SBH_whole.pep - full length protein sequences SBH_cut.pep - domain seqeunces SBH.aln - alignment used for phylogenetic tree SLD_whole.pep - full length protein sequences SLD_cut.pep - domain seqeunces SLD.aln - alignment used for phylogenetic tree
DOI: 10.6084/m9.figshare.20448579.v2
title: Supplementary files for ‘Lipid biomarkers for algal resistance to viral infection in the ocean’: whole sequences, domain sequences, alignments (SBH and SLD)

description: The files attached are the domain sequenes, the full length sequences, and the alignments used for the phylogenetic trees of the SBH and SLD domains: <br> SBH_whole.pep - full length protein sequences SBH_cut.pep - domain seqeunces SBH.aln - alignment used for phylogenetic tree SLD_whole.pep - full length protein sequences SLD_cut.pep - domain seqeunces SLD.aln - alignment used for phylogenetic tree
DOI: 10.5517/ccdc.csd.cc2ffk4l
title: CCDC 2247349: Experimental Crystal Structure Determination

description: Related Article: Matthew J. Evans, Mathew D. Anker, Claire L. McMullin, Martyn P. Coles|2023|Chemical Science|14|6278|doi:10.1039/D3SC01387A
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: 10.5519/qd.e0ggorm1
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (13 records)
DOI: 10.6084/m9.figshare.23300882
title: data

description: Litter and herbivore grazing
DOI: 10.6084/m9.figshare.23300882.v2
title: mowing data

description: Effects of mowing on plant community
DOI: 10.5281/zenodo.8032717
title: Unlocking the Predictive Power of Quantum-Inspired Representations for Intermolecular Properties in Machine Learning

description: Dataset associated with the manuscript entitled "Unlocking the Predictive Power of Quantum-Inspired Representations for Intermolecular Properties in Machine Learning". See Readme file (markdown format) for details on how the data is structured in the "database" file.
description: Research Funded by the Spanish Ministerio de Economía y Competitividad (Project: CTQ2017-87773-P/AEI/FEDER), and the Spanish Ministerio de Ciencia e Innovación (Projects PID2020-117803GB-I00 and CEX2021-001202-M). The authors also acknowledge support from project grant 2021SGR00354 funded by the Generalitat de Catalunya. R.S. acknowledges a predoctoral FPI grant from MINECO under grant agreement CTQ2017-87773-P, and S.V. acknowledges Generalitat de Catalunya for a Beatriu de Pinós grant (BP00043).