cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.20995492.v1
title: VT Bldgs - ORNL USA Structure Dataset

description: Vermont building outline dataset.
DOI: 10.6084/m9.figshare.20514312.v1
title: MI Bldgs - ORNL USA Structure Dataset

description: Michigan building outline dataset.
DOI: 10.6084/m9.figshare.20514222
title: CT Bldgs - ORNL USA Structure Dataset

description: Connecticut building outline dataset.
DOI: 10.6084/m9.figshare.20514222.v1
title: CT Bldgs - ORNL USA Structure Dataset

description: Connecticut building outline dataset.
DOI: 10.6084/m9.figshare.20514270
title: KS Bldgs - ORNL USA Structure Dataset

description: Kansas building outline dataset.
DOI: 10.6084/m9.figshare.20514270.v1
title: KS Bldgs - ORNL USA Structure Dataset

description: Kansas building outline dataset.
DOI: 10.6084/m9.figshare.20514306.v1
title: MA Bldgs - ORNL USA Structure Dataset

description: Massachusetts building outline dataset.
DOI: 10.6084/m9.figshare.20518611
title: MN Bldgs - ORNL USA Structure Dataset

description: Minnesota building outline dataset.
DOI: 10.6084/m9.figshare.20518611.v1
title: MN Bldgs - ORNL USA Structure Dataset

description: Minnesota building outline dataset.
DOI: 10.6084/m9.figshare.20518635
title: MO Bldgs - ORNL USA Structure Dataset

description: Missouri building outline dataset.
DOI: 10.6084/m9.figshare.20995873
title: PR Bldgs - ORNL USA Structure Dataset

description: Puerto Rico building outline dataset.
DOI: 10.6084/m9.figshare.20512833
title: MS Bldgs - ORNL USA Structure Dataset

description: Mississippi building outline dataset.
DOI: 10.6084/m9.figshare.20512833.v1
title: MS Bldgs - ORNL USA Structure Dataset

description: Mississippi building outline dataset.
DOI: 10.6084/m9.figshare.20518770
title: PA Bldgs - ORNL USA Structure Dataset

description: Pennsylvania building outline dataset.
DOI: 10.6084/m9.figshare.20518770.v1
title: PA Bldgs - ORNL USA Structure Dataset

description: Pennsylvania building outline dataset.
DOI: 10.6084/m9.figshare.20995732.v1
title: WY Bldgs - ORNL USA Structure Dataset

description: Wyoming building outline dataset.
DOI: 10.6084/m9.figshare.20995873.v1
title: PR Bldgs - ORNL USA Structure Dataset

description: Puerto Rico building outline dataset.
DOI: 10.6084/m9.figshare.20519871
title: TX Bldgs - ORNL USA Structure Dataset

description: Texas building outline dataset.
DOI: 10.6084/m9.figshare.20519871.v1
title: TX Bldgs - ORNL USA Structure Dataset

description: Texas building outline dataset.
DOI: 10.6084/m9.figshare.20995732
title: WY Bldgs - ORNL USA Structure Dataset

description: Wyoming building outline dataset.
DOI: 10.6084/m9.figshare.20995837
title: VI Bldgs - ORNL USA Structure Dataset

description: United States Virgin Islands building outline dataset.
DOI: 10.6084/m9.figshare.20995837.v1
title: VI Bldgs - ORNL USA Structure Dataset

description: United States Virgin Islands building outline dataset.
DOI: 10.6084/m9.figshare.20969185
title: Substrate characterization for development of biogas prediction model by thermogravimetry

description: Supplementary Material related to the manuscript " Thermogravimetric substrate analysis as a tool for prediction of biogas and methane yields"
DOI: 10.6084/m9.figshare.20969185.v2
title: Substrate characterization for development of biogas prediction model by thermogravimetry

description: Supplementary Material related to the manuscript " Thermogravimetric substrate analysis as a tool for prediction of biogas and methane yields"
DOI: 10.6084/m9.figshare.20969185.v1
title: Substrate characterization for development of biogas prediction model by thermogravimetry

description: Supplementary Material related to the manuscript " Thermogravimetric substrate analysis as a tool for prediction of biogas and methane yields"
DOI: 10.6084/m9.figshare.20518686
title: ND Bldgs - ORNL USA Structure Dataset

description: North Dakota building outline dataset.
DOI: 10.6084/m9.figshare.20518686.v1
title: ND Bldgs - ORNL USA Structure Dataset

description: North Dakota building outline dataset.
DOI: 10.5281/zenodo.7058425
title: A map of human modification for Colorado in 2020

description: The purpose of this note is to briefly describe a detailed (30 m) spatial dataset that estimates the degree of human modification for the lands of Colorado reflecting ~2020 conditions. The degree of human modification is a well-established method to estimate the proximate human activities or processes that have caused, are causing, or may cause impacts on biodiversity and ecosystems. This includes stressors for: urban and built-up, crop and pasture lands, livestock grazing, oil and gas production, mining and quarrying, power generation (renewable and nonrenewable), roads, railways, power lines and towers, logging and wood harvesting, human intrusions, and air pollution. Please see the attached PDF -- <em>Technical note on a map of human modification in Colorado for 2020 -- </em>that provides further details.
DOI: 10.5281/zenodo.7058424
title: A map of human modification for Colorado in 2020

description: The purpose of this note is to briefly describe a detailed (30 m) spatial dataset that estimates the degree of human modification for the lands of Colorado reflecting ~2020 conditions. The degree of human modification is a well-established method to estimate the proximate human activities or processes that have caused, are causing, or may cause impacts on biodiversity and ecosystems. This includes stressors for: urban and built-up, crop and pasture lands, livestock grazing, oil and gas production, mining and quarrying, power generation (renewable and nonrenewable), roads, railways, power lines and towers, logging and wood harvesting, human intrusions, and air pollution. Please see the attached PDF -- <em>Technical note on a map of human modification in Colorado for 2020 -- </em>that provides further details.
DOI: 10.5281/zenodo.5600468
title: Ländervergleich Kooperationstiefe

description: Das hier publizierte Material ergänzt einen Artikel der gleichen Autoren, der 2022 im Journal Wirtschaftsinformatik & Management [von der Heyde et al., 2022] erschien. Im Rahmen einer Studie sind in fünf Bundesländern -- Baden-Württemberg (BaWü), Bayern (BY), Brandenburg (BRB), Niedersachsen (NDS), Nordrhein-Westfalen (NRW) -- eine Reihe von Themenfeldern der Digitalisierung bzw. der IT-Governance identifiziert worden, bei der die Kooperation zwischen Hochschulen Vorteile erwarten lässt. Den Themen wurden die aktuellen bzw. zukünftigen Kooperations-Optionen zugeordnet. Wir verstehen die folgenden Optionen nicht als Reifegradstufen, sondern als gleichzeitig vorkommende, je nach Sachverhalt gewählte Alternativen. Entsprechende Formulierungen wurden gewählt, wenn die aufgeführten Optionen bisher noch nicht erreicht wurden, sondern der beschriebene Zustand eher angestrebt wird oder sich bereits in der Umsetzung befindet.<br> Option A: kooperative Planung / Konzeption -&gt; Austausch von Pilotierungen, Information und Ideen<br> Option B: individueller Service -&gt; Austausch von Lösungen / Erfahrungen / Best Practices<br> Option C: gemeinsame Servicespezifikation -&gt; Mengenmehrung bei Beschaffung / politische Wirksamkeit / standardisierte Umsetzung<br> Option D: ein Service für alle -&gt; zentrale Spezialisierung bzw. zentraler Realisierung oder Beratungskompetenzen<br> Option E: ein Service für alle, aber Leistungserbringung über mehrere Standorte verteilt -&gt; redundante Realisierung bzw. verteilte Spezialisierung Kooperationsbereiche und aktuelle bzw. geplante Optionen im typischen Handlungsbereich der CIOs und RZ-Leiter:innen in den Ländern. Die Buchstaben beziehen sich auf das oben beschriebene Options-Modell. Bereiche, die institutionalisiert begonnen oder umgesetzt wurden, haben einen einheitlichen Hintergrund; Überlegungen und offene Planungen sind schraffiert. Die Spalte BaWü enthält bisher primär die Kooperationsoptionen der Universitäten, die sich in machen Feldern deutlich von den HAW unterscheiden.
description: {"references": ["Gemeinsame Digitalisierung durch die Entwicklung von IT-Governance-Strukturen auf Landesebene - Vergleich von Zielen und Steuerung der Hochschul-Kooperation von f\u00fcnf Bundesl\u00e4ndern in Deutschland."]}
DOI: 10.5281/zenodo.5600467
title: Ländervergleich Kooperationstiefe

description: Das hier publizierte Material ergänzt einen Artikel der gleichen Autoren, der 2022 im Journal Wirtschaftsinformatik & Management [von der Heyde et al., 2022] erschien. Im Rahmen einer Studie sind in fünf Bundesländern -- Baden-Württemberg (BaWü), Bayern (BY), Brandenburg (BRB), Niedersachsen (NDS), Nordrhein-Westfalen (NRW) -- eine Reihe von Themenfeldern der Digitalisierung bzw. der IT-Governance identifiziert worden, bei der die Kooperation zwischen Hochschulen Vorteile erwarten lässt. Den Themen wurden die aktuellen bzw. zukünftigen Kooperations-Optionen zugeordnet. Wir verstehen die folgenden Optionen nicht als Reifegradstufen, sondern als gleichzeitig vorkommende, je nach Sachverhalt gewählte Alternativen. Entsprechende Formulierungen wurden gewählt, wenn die aufgeführten Optionen bisher noch nicht erreicht wurden, sondern der beschriebene Zustand eher angestrebt wird oder sich bereits in der Umsetzung befindet.<br> Option A: kooperative Planung / Konzeption -&gt; Austausch von Pilotierungen, Information und Ideen<br> Option B: individueller Service -&gt; Austausch von Lösungen / Erfahrungen / Best Practices<br> Option C: gemeinsame Servicespezifikation -&gt; Mengenmehrung bei Beschaffung / politische Wirksamkeit / standardisierte Umsetzung<br> Option D: ein Service für alle -&gt; zentrale Spezialisierung bzw. zentraler Realisierung oder Beratungskompetenzen<br> Option E: ein Service für alle, aber Leistungserbringung über mehrere Standorte verteilt -&gt; redundante Realisierung bzw. verteilte Spezialisierung Kooperationsbereiche und aktuelle bzw. geplante Optionen im typischen Handlungsbereich der CIOs und RZ-Leiter:innen in den Ländern. Die Buchstaben beziehen sich auf das oben beschriebene Options-Modell. Bereiche, die institutionalisiert begonnen oder umgesetzt wurden, haben einen einheitlichen Hintergrund; Überlegungen und offene Planungen sind schraffiert. Die Spalte BaWü enthält bisher primär die Kooperationsoptionen der Universitäten, die sich in machen Feldern deutlich von den HAW unterscheiden.
description: {"references": ["Gemeinsame Digitalisierung durch die Entwicklung von IT-Governance-Strukturen auf Landesebene - Vergleich von Zielen und Steuerung der Hochschul-Kooperation von f\u00fcnf Bundesl\u00e4ndern in Deutschland."]}
DOI: 10.6084/m9.figshare.21045793
title: dataset-09-07-22_17-06-52

description: This description is a placeholder
DOI: 10.6084/m9.figshare.21045793.v1
title: dataset-09-07-22_17-06-52

description: This description is a placeholder
DOI: 10.17909/se6w-0h98
title: Data used in paper https://arxiv.org/abs/2208.02233

description: The early release JWST observations of the SMACS 0723 cluster contain the photometry of the Sparkler galaxy used in this analysis.
DOI: 10.5281/zenodo.6828667
title: Dataset: Enhancing Spin Coherence in Optically Addressable Molecular Qubits through Host-Matrix Control

description: Dataset: Enhancing Spin Coherence in Optically Addressable Molecular Qubits through Host-Matrix Control
DOI: 10.5281/zenodo.6828666
title: Dataset: Enhancing Spin Coherence in Optically Addressable Molecular Qubits through Host-Matrix Control

description: Dataset: Enhancing Spin Coherence in Optically Addressable Molecular Qubits through Host-Matrix Control
DOI: 10.6084/m9.figshare.21045733
title: Concatenated molecular matrix in phylip format

description: Here, I provide the concatenated alignment of 5,928 base pairs from eight genes fragments (12S, 16S, Cox1, Cytb, Bdnf, Cmos, Nt3, Rag1) used in our maximum likelihood (ML) analysis in the study where we describe a new species of Tantilla from southern Brazil.
DOI: 10.6084/m9.figshare.21046285
title: model-09-07-22_17-22-50

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21046285.v1
title: model-09-07-22_17-22-50

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21046342
title: model-09-07-22_17-24-42

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21046342.v1
title: model-09-07-22_17-24-42

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.20995642.v1
title: WI Bldgs - ORNL USA Structure Dataset

description: Wisconsin building outline dataset.
DOI: 10.6084/m9.figshare.20518719.v1
title: OH Bldgs - ORNL USA Structure Dataset

description: Ohio building outline dataset.
DOI: 10.21227/4s2y-5260
title: Frequency Spectrum for two classes of manufacturing process

description: Frequency Spectra for an industrial polishing process under two different process conditions. The silhouettes of the spectra correspond to the 25th and 75th percentile of the energy for the 600 samples of spectra from each class.
DOI: 10.6084/m9.figshare.21046327
title: Concatenated molecular matrix in XML format

description: Here, I provide the concatenated alignment of 5,928 base pairs from eight genes fragments (12S, 16S, Cox1, Cytb, Bdnf, Cmos, Nt3, Rag1) used in our Divergence time estimation (Beast) analysis in the study where we describe a new species of Tantilla from southern Brazil.
DOI: 10.5281/zenodo.6626508
title: MBW Zoo Data

description: Labeling articulated objects in unconstrained settings have a wide variety of applications including entertainment, neuroscience, psychology, ethology, and many fields of medicine. Large offline labeled datasets do not exist for all but the most common articulated object categories (e.g., humans). With just a few annotations (representing 1-2% of the frames), we are able to produce 2D results comparable to state-of-the-art fully supervised methods, and obtain 3D reconstructions that are impossible with other existing approaches. Our Multi-view Bootstrapping in the Wild (MBW) approach demonstrates results on standard human datasets, as well as tigers, cheetahs, fish, colobus monkeys, chimpanzees, and flamingos from videos captured casually in a zoo. We release this challenging dataset consisting image frames of tail-end distribution categories (such as Fish, Colobus Monkeys, Chimpanzees, etc.) with their corresponding 2D, 3D, and Bounding-Box labels generated from minimal human intervention.
description: https://github.com/mosamdabhi/MBW-Data
DOI: 10.5281/zenodo.6644389
title: MBW Zoo Data

description: We release a challenging dataset consisting image frames of tail-end distribution categories (such as Fish, Colobus Monkeys, Chimpanzees, etc.) with their corresponding 2D, 3D, and Bounding-Box labels generated from minimal human intervention. Some of the prominent use cases of this dataset include not only sparse <strong>2D and 3D landmark prediction</strong>, but also dense reconstruction tasks such as <strong>dense deformable shape reconstruction</strong>, novel view rendering (<strong>NeRF</strong>), <strong>Detection and Tracking,</strong> and finally this dataset could also be used for camera estimation in Simultaneous Localization and Mapping (<strong>SLAM</strong>) frameworks.
description: https://github.com/mosamdabhi/MBW-Data
DOI: 10.5281/zenodo.6626507
title: MBW Zoo Data

description: We release a challenging dataset consisting image frames of tail-end distribution categories (such as Fish, Colobus Monkeys, Chimpanzees, etc.) with their corresponding 2D, 3D, and Bounding-Box labels generated from minimal human intervention. Some of the prominent use cases of this dataset include not only sparse <strong>2D and 3D landmark prediction</strong>, but also dense reconstruction tasks such as <strong>dense deformable shape reconstruction</strong>, novel view rendering (<strong>NeRF</strong>), <strong>Detection and Tracking,</strong> and finally this dataset could also be used for camera estimation in Simultaneous Localization and Mapping (<strong>SLAM</strong>) frameworks.
description: https://github.com/mosamdabhi/MBW-Data
DOI: 10.5281/zenodo.7011549
title: MBW Zoo Data

description: We release a challenging dataset consisting image frames of tail-end distribution categories (such as Fish, Colobus Monkeys, Chimpanzees, etc.) with their corresponding 2D, 3D, and Bounding-Box labels generated from minimal human intervention. Some of the prominent use cases of this dataset include not only sparse <strong>2D and 3D landmark prediction</strong>, but also dense reconstruction tasks such as <strong>dense deformable shape reconstruction</strong>, novel view rendering (<strong>NeRF</strong>), <strong>Detection and Tracking,</strong> and finally this dataset could also be used for camera estimation in Simultaneous Localization and Mapping (<strong>SLAM</strong>) frameworks.
description: https://github.com/mosamdabhi/MBW-Data
DOI: 10.5281/zenodo.7058567
title: MBW Zoo Data

description: We release a challenging dataset consisting image frames of tail-end distribution categories (such as Fish, Colobus Monkeys, Chimpanzees, etc.) with their corresponding 2D, 3D, and Bounding-Box labels generated from minimal human intervention. Some of the prominent use cases of this dataset include not only sparse <strong>2D and 3D landmark prediction</strong>, but also dense reconstruction tasks such as <strong>dense deformable shape reconstruction</strong>, novel view rendering (<strong>NeRF</strong>), <strong>Detection and Tracking,</strong> and finally this dataset could also be used for camera estimation in Simultaneous Localization and Mapping (<strong>SLAM</strong>) frameworks.
description: https://github.com/mosamdabhi/MBW-Data
DOI: 10.6084/m9.figshare.21046852
title: model-09-07-22_17-42-16

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21046852.v1
title: model-09-07-22_17-42-16

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21046819
title: LPEM Data for PEG Diffusion Paper

description: The three datasets and R script used to analyze solute transport in hydrogels data via the large pore effective medium model.
DOI: 10.6084/m9.figshare.21046819.v1
title: LPEM Data for PEG Diffusion Paper

description: The three datasets and R script used to analyze solute transport in hydrogels data via the large pore effective medium model.
DOI: 10.6084/m9.figshare.21046987
title: Non-LPEM Data for PEG Diffusivity Paper

description: Compiled FRAP, partitioning, and swelling data for solute transport in multi-arm PEG hydrogels as well as structural predictions of solute diffusivity in those hydrogels using the swollen polymer network model.
DOI: 10.6084/m9.figshare.21047119
title: model-09-07-22_17-47-52

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21047119.v1
title: model-09-07-22_17-47-52

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21047275
title: model-09-07-22_17-52-50

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21047275.v1
title: model-09-07-22_17-52-50

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.21233/ns4t-bz61
title: Chamboite site 12 pollen surface sample dataset

description: Raw data for the Chamboite site 12 pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/agt4-5w62
title: Prairie Owl water chemistry dataset

description: Raw data for the Prairie Owl water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/9vqn-ez46
title: Hackberry Lake water chemistry dataset

description: Raw data for the Hackberry Lake water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/f8kb-0646
title: Nieuwe Veen pollen dataset

description: Raw data for the Nieuwe Veen pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.6084/m9.figshare.21047347
title: model-09-07-22_17-53-58

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.6084/m9.figshare.21047347.v1
title: model-09-07-22_17-53-58

description: Dataset of chessboard states (fen strings), Stockfish move probabilities, and position evaluations
DOI: 10.21233/82gq-2548
title: Oskino-09 pollen dataset

description: Raw data for the Oskino-09 pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/fjkj-qp65
title: Upper Tree Claim water chemistry dataset

description: Raw data for the Upper Tree Claim water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/6gcq-2q96
title: War Axe diatom surface sample dataset

description: Raw data for the War Axe diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/mc7d-y923
title: Chamboite site 14 pollen surface sample dataset

description: Raw data for the Chamboite site 14 pollen surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/faae-e428
title: Christ water chemistry dataset

description: Raw data for the Christ water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/sg71-6764
title: Shaup diatom surface sample dataset

description: Raw data for the Shaup diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/ckmt-y509
title: Gimlet water chemistry dataset

description: Raw data for the Gimlet water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/md5r-xa51
title: Cheyenne water chemistry dataset

description: Raw data for the Cheyenne water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/6cgx-fj22
title: Welfleet diatom surface sample dataset

description: Raw data for the Welfleet diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/xpd3-0f47
title: Gourds des Aillères pollen dataset

description: Raw data for the Gourds des Aillères pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/ea5w-x712
title: Chadron water chemistry dataset

description: Raw data for the Chadron water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/yham-g877
title: West Long diatom surface sample dataset

description: Raw data for the West Long diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/f6zk-vm98
title: Aluaipugua pollen dataset

description: Raw data for the Aluaipugua pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/9yf2-tj70
title: Nemra pollen dataset

description: Raw data for the Nemra pollen dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/39eb-rr44
title: Reno water chemistry dataset

description: Raw data for the Reno water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/2tf5-9427
title: School Section water chemistry dataset

description: Raw data for the School Section water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/fmdc-ma31
title: Hayes Center water chemistry dataset

description: Raw data for the Hayes Center water chemistry dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/3xnn-y945
title: Big Alkali Lake diatom surface sample dataset

description: Raw data for the Big Alkali Lake diatom surface sample dataset obtained from the Neotoma Paleoecology Database.
DOI: 10.21233/jdv2-xk11
title: Island Lake (Ga) diatom surface sample dataset

description: Raw data for the Island Lake (Ga) diatom surface sample dataset obtained from the Neotoma Paleoecology Database.