cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.4309837
title: 3D mesh model and raw images of a drifting iceberg in Nuup Kangerlua (Godthåbsfjord), SW Greenland on 17 August 2017

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Nuup Kangerlua (Godthåbsfjord) in southwest Greenland on 17 August 2017. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_528, 530, 531-533 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>
DOI: 10.5281/zenodo.4309836
title: 3D mesh model and raw images of a drifting iceberg in Nuup Kangerlua (Godthåbsfjord), SW Greenland on 17 August 2017

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Nuup Kangerlua (Godthåbsfjord) in southwest Greenland on 17 August 2017. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_528, 530, 531-533 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>
DOI: 10.5281/zenodo.4309843
title: 3D mesh model and raw images of a drifting iceberg in Nuup Kangerlua (Godthåbsfjord), SW Greenland on 22 August 2017

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Nuup Kangerlua (Godthåbsfjord) in southwest Greenland on 17 August 2017. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_659-662 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>
DOI: 10.5281/zenodo.4309842
title: 3D mesh model and raw images of a drifting iceberg in Nuup Kangerlua (Godthåbsfjord), SW Greenland on 22 August 2017

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Nuup Kangerlua (Godthåbsfjord) in southwest Greenland on 17 August 2017. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_659-662 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>
DOI: 10.21227/1kft-dn93
title: Temp OA

description: Test
DOI: 10.21227/44ex-f585
title: Temp OA

description: Test
DOI: 10.15468/6xm7be
title: Narrow-winged pyralids (Lepidoptera, Pyraloidea, Pyralidae, Phycitinae) of Leningrad Province and the city of St. Petersburg, Russia

description: This dataset contains the digitized treatments in Plazi based on the original journal article Tsvetkov, Eugene (2020): Narrow-winged pyralids (Lepidoptera, Pyraloidea, Pyralidae, Phycitinae) of Leningrad Province and the city of St. Petersburg, Russia. Zootaxa 4890 (3): 361-374, DOI: https://doi.org/10.11646/zootaxa.4890.3.4
DOI: 10.6084/m9.figshare.13341674
title: Structure data collection for Saccharomyces cerevisiae

description: Residue distance data for protein 3D structures.
DOI: 10.34812/a272-9961
title: Broadsides printed in Scotland 1650-1910

description: This dataset represents the Broadsides printed in Scotland 1650-1910. It comprises  nearly 1,800 broadsides printed in Scotland.
Date range: 1650-1910
OCR quality: corrected transcriptions
File types/numbers: 1,727 ALTO XML files; 1,727 image files; 1,727 METS files; 1,726 plain text files.
DOI: 10.15468/rpyfey
title: Three new species of Gelechiidae (Lepidoptera) from Panama

description: This dataset contains the digitized treatments in Plazi based on the original journal article Chang, Patricia Esther Corro, Bidzilya, Oleksiy (2020): Three new species of Gelechiidae (Lepidoptera) from Panama. Zootaxa 4890 (3): 407-416, DOI: https://doi.org/10.11646/zootaxa.4890.3.7
DOI: 10.5281/zenodo.4309851
title: 3D mesh model and raw images of a drifting iceberg in Dickson Fjord (NE Greenland) on 20 August 2018 at 12:41 UTC

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Dickson Fjord in northeast Greenland on 20 August 2018. The UAV survey commenced at 12:41 UTC. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_493-497 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>
DOI: 10.5281/zenodo.4309850
title: 3D mesh model and raw images of a drifting iceberg in Dickson Fjord (NE Greenland) on 20 August 2018 at 12:41 UTC

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Dickson Fjord in northeast Greenland on 20 August 2018. The UAV survey commenced at 12:41 UTC. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_493-497 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>
DOI: 10.21227/3pnq-fy60
title: Temp OA

description: Test
DOI: 10.6084/m9.figshare.13341830.v1
title: ASIP CNV in Malaguena goats

description: The agouti signaling protein (ASIP) gene has a crucial role in pigmentation by encoding a protein that binds the melanocortin 1 receptor and stimulates the synthesis of pheomelanin rather than eumelanin. Several studies have suggested that an increased copy number of the ASIP gene might explain the white pigmentation of certain goat breeds, as previously demonstrated in sheep. In the current work, we have identified the segregation of the ASIP CNV in Murciano-Granadina (black or brown coat), Malagueña (brown, blond or white coat) and Saanen (white coat) goats with available Illumina Goat SNP50 BeadChip (Illumina Inc., San Diego, CA) genotypes by using the PennCNV v1.0.5 and QuantiSNP v2 tools. This result shows that the ASIP CNV segregates in dark-colored breeds. To gain new insights into this issue, we have estimated the copy number of the ASIP gene in 83 goats from 8 breeds with different coloration patterns using a real-time quantitative PCR approach. Our results showed an increased ASIP copy number not only in Saanen (3.50 ± 0.23 copies relative to the calibrator) and white Malagueña (3.51 ± 0.51 copies) goats, but also in the Murciano-Granadina breed (3.33 ± 0.58 copies) as well as in blond/brown individuals from the Malagueña (3.58 ± 0.73 copies) breed. The number of ASIP copies was not significantly different in these four caprine populations (P value &gt; 0.05). Moreover, we did not observe a trend towards increased ASIP copy number in breeds with predominantly white colors, such as Maltese (2.85 ± 0.28 copies), Jonica (2.82 ± 0.39 copies) and Blanca de Rasquera (2.37 ± 0.33 copies). Our results, combined with recent findings demonstrating the high structural complexity of the ASIP locus, indicate that additional functional and expression studies should be performed in order to fully understand the role of ASIP structural variation in goat pigmentation. <br>
DOI: 10.6084/m9.figshare.13341830
title: ASIP CNV in Malaguena goats

description: The agouti signaling protein (ASIP) gene has a crucial role in pigmentation by encoding a protein that binds the melanocortin 1 receptor and stimulates the synthesis of pheomelanin rather than eumelanin. Several studies have suggested that an increased copy number of the ASIP gene might explain the white pigmentation of certain goat breeds, as previously demonstrated in sheep. In the current work, we have identified the segregation of the ASIP CNV in Murciano-Granadina (black or brown coat), Malagueña (brown, blond or white coat) and Saanen (white coat) goats with available Illumina Goat SNP50 BeadChip (Illumina Inc., San Diego, CA) genotypes by using the PennCNV v1.0.5 and QuantiSNP v2 tools. This result shows that the ASIP CNV segregates in dark-colored breeds. To gain new insights into this issue, we have estimated the copy number of the ASIP gene in 83 goats from 8 breeds with different coloration patterns using a real-time quantitative PCR approach. Our results showed an increased ASIP copy number not only in Saanen (3.50 ± 0.23 copies relative to the calibrator) and white Malagueña (3.51 ± 0.51 copies) goats, but also in the Murciano-Granadina breed (3.33 ± 0.58 copies) as well as in blond/brown individuals from the Malagueña (3.58 ± 0.73 copies) breed. The number of ASIP copies was not significantly different in these four caprine populations (P value &gt; 0.05). Moreover, we did not observe a trend towards increased ASIP copy number in breeds with predominantly white colors, such as Maltese (2.85 ± 0.28 copies), Jonica (2.82 ± 0.39 copies) and Blanca de Rasquera (2.37 ± 0.33 copies). Our results, combined with recent findings demonstrating the high structural complexity of the ASIP locus, indicate that additional functional and expression studies should be performed in order to fully understand the role of ASIP structural variation in goat pigmentation. <br>
DOI: 10.5281/zenodo.4309747
title: Marine terraces of the last interglacial period along the Pacific coast of South America (1°N-40°S)

description: This database comprises ~2,000 measurements of last interglacial marine terrace elevations along ~5,000 km of the western South American coast from northern Ecuador to south-central Chile (1°N-40°S). We used quantitatively replicable approaches constrained by previously published terrace-age estimates. Uncertainties were estimated on the basis of measurement errors and the distance from these referencing points.
DOI: 10.5281/zenodo.4309797
title: Global database of U-series dated fossil coral sea-level indicators for the Last Interglacial period

description: This database is a global compilation of age, elevation, and relevant metadata for U-series fossil coral sea-level indicators from the Last Interglacial period (MIS 5e). It has been exported from the World Atlas of Last Interglacial Shorelines (WALIS) database (https://warmcoasts.eu/world-atlas.html).
description: Also supported by NSF grant #1702740.
DOI: 10.25592/uhhfdm.8387
title: 3D Model of Pinus sylvestris

description: Pinus sylvestris_Common Pine - Gemeine Kiefer<br> scientific name: Pinus sylvestris<br> vernacular name: common pine<br> object: Wooden library in book form made of wood from common pine, spine with bark, cover with habit, inside with leafy branches, flowers and fruits as well as mushrooms (Ischnoderma benzoinum/Gloeophyllum odoratum) characteristic of the common pine.
DOI: 10.25592/uhhfdm.8284
title: 3D Model of Pinus sylvestris

description: Pinus sylvestris_Common Pine - Gemeine Kiefer<br> scientific name: Pinus sylvestris<br> vernacular name: common pine<br> object: Wooden library in book form made of wood from common pine, spine with bark, cover with habit, inside with leafy branches, flowers and fruits as well as mushrooms (Ischnoderma benzoinum/Gloeophyllum odoratum) characteristic of the common pine.
DOI: 10.34740/kaggle/dsv/1721465
title: COVID-19 Indonesia Dataset
DOI: 10.6084/m9.figshare.13341865
title: Mount Early and Sheridan Bluff: petrology

description: Mineral chemistry (olivine, clinopyroxene, plagioclase, titanomagntite, ilmenite, Cr-spinel).
DOI: 10.6084/m9.figshare.13341865.v1
title: Mount Early and Sheridan Bluff: petrology

description: Mineral chemistry (olivine, clinopyroxene, plagioclase, titanomagntite, ilmenite, Cr-spinel).
DOI: 10.26300/fxga-1g27
title: Identifying Sources and Impacts of Precipitation-Derived Nitrogen in Narragansett Bay, RI
DOI: 10.34740/kaggle/dsv/1721498
title: COVID-19 Indonesia Dataset
DOI: 10.5281/zenodo.4309421
title: Ergänzungsmaterialien zum Artikel "Schreibprozesse und Texte im Zeitalter der Digitalisierung: Herausforderungen für eine zeitgemäße Schreibwissenschaft und -didaktik. Ein Werkstatt- und Forschungsgespräch der SIG Digitalisierung"

description: Mit der Fragestellung „Wie berücksichtigt die Schreibwissenschaft Veränderungen durch digitale Schreibprozesse und digitale Texte von Studierenden?“ kam die SIG Digitalisierung in einem virtuellen Werkstatt- und Forschungsgespräch zusammen, um Aspekte der Digitalisierung hinsichtlich Schreibforschung und -beratung zu diskutieren. Im Gespräch wurde deutlich, dass Digitalisierung wesentliche Aspekte des Schreibens (Schreibprozesse, Text-Definition) verändert. Dabei gewinnen Informations- sowie Medienkompetenz einen hohen Stellenwert und können schreibdidaktisch gefördert werden. In diesem Sinne gibt es weiterhin einen Bedarf von Train-the-Trainer-Angeboten, welche die Besonderheiten digitalen Schreibens für die Lehre vermitteln.
DOI: 10.5281/zenodo.3953432
title: Ergänzungsmaterialien zum Artikel "Schreibprozesse und Texte im Zeitalter der Digitalisierung: Herausforderungen für eine zeitgemäße Schreibwissenschaft und -didaktik. Ein Werkstatt- und Forschungsgespräch der SIG Digitalisierung"

description: Mit der Fragestellung „Wie berücksichtigt die Schreibwissenschaft Veränderungen durch digitale Schreibprozesse und digitale Texte von Studierenden?“ kam die SIG Digitalisierung in einem virtuellen Werkstatt- und Forschungsgespräch zusammen, um Aspekte der Digitalisierung hinsichtlich Schreibforschung und -beratung zu diskutieren. Im Gespräch wurde deutlich, dass Digitalisierung wesentliche Aspekte des Schreibens (Schreibprozesse, Text-Definition) verändert. Dabei gewinnen Informations- sowie Medienkompetenz einen hohen Stellenwert und können schreibdidaktisch gefördert werden. In diesem Sinne gibt es weiterhin einen Bedarf von Train-the-Trainer-Angeboten, welche die Besonderheiten digitalen Schreibens für die Lehre vermitteln.
DOI: 10.15468/t9m5jr
title: A new species of Rutaraphes Jałoszyński in Taiwan (Coleoptera, Staphylinidae Scydmaeninae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Jałoszyński, Paweł (2020): A new species of Rutaraphes Jałoszyński in Taiwan (Coleoptera, Staphylinidae Scydmaeninae). Zootaxa 4890 (3): 446-450, DOI: https://doi.org/10.11646/zootaxa.4890.3.11
DOI: 10.21227/wmfc-zm04
title: LowEndInsight-PyPI

description: The Python Packaging Index is an invaluable resource that is used by developers to improve their projects; however, there are glaring issues in its implementation that will hinder development until resolved. The Python Packaging Index (PyPI) is the official third-party software repository for Python where the majority of open-source Python packages are published. Each package has wheel and egg files accessible from the Python package management system PIP, as well as queryable metadata that contains important package information. The PyPI metadata provides key information such as package license, source code, and dependencies which are necessary for developers working with a given open-source package to ascertain its security and legal risks; however since PyPI currently does not support an effective means of tracking some of this information, it forces a developer to cope with uncertain risk if they wish to use open-source code. In its current state, Python open-source code facilitates project development at the risk of unknown vulnerabilities; however, developers should not be sacrificing efficiency for security. This dataset provides some insight into the PyPI ecosystem, using the LowEndInsight analyzer to process all packages, traverse from module to source code, and then identify potential risks. The dataset is the result of upstream HPC processing against the PyPI generated raw data.
DOI: 10.21227/764e-hp65
title: LowEndInsight-PyPI

description: The Python Packaging Index is an invaluable resource that is used by developers to improve their projects; however, there are glaring issues in its implementation that will hinder development until resolved. The Python Packaging Index (PyPI) is the official third-party software repository for Python where the majority of open-source Python packages are published. Each package has wheel and egg files accessible from the Python package management system PIP, as well as queryable metadata that contains important package information. The PyPI metadata provides key information such as package license, source code, and dependencies which are necessary for developers working with a given open-source package to ascertain its security and legal risks; however since PyPI currently does not support an effective means of tracking some of this information, it forces a developer to cope with uncertain risk if they wish to use open-source code. In its current state, Python open-source code facilitates project development at the risk of unknown vulnerabilities; however, developers should not be sacrificing efficiency for security. This dataset provides some insight into the PyPI ecosystem, using the LowEndInsight analyzer to process all packages, traverse from module to source code, and then identify potential risks. The dataset is the result of upstream HPC processing against the PyPI generated raw data.
DOI: 10.15468/ucjtzf
title: Reinstatement of the Patagonian moss Ulota glabella Mitt. (Bryophyta, Orthotrichaceae)

description: This dataset contains the digitized treatments in Plazi based on the original journal article Garilleti, Ricardo, Albertos, Belén, Draper, Isabel, Calleja, Juan Antonio, Lara, Francisco (2020): Reinstatement of the Patagonian moss Ulota glabella Mitt. (Bryophyta, Orthotrichaceae). European Journal of Taxonomy 726: 83-101, DOI: https://doi.org/10.5852/ejt.2020.726.1177
DOI: 10.5281/zenodo.4309930
title: 3D mesh model and raw images of a drifting iceberg in Dickson Fjord (NE Greenland) on 20 August 2018 at 16:56 UTC

description: This dataset consists of low-altitude aerial imagery that was acquired by a DJI Phantom 3 Standard unoccupied aerial vehicle (UAV) in Dickson Fjord in northeast Greenland on 20 August 2018. The UAV survey commenced at 16:56 UTC. These images were processed in Agisoft PhotoScan Pro (v1.4; Linux Ubuntu). During the image alignment step in PhotoScan, the ‘High’ accuracy setting and key point and tie point limits of 60000 and 0 were used. Generic and reference preselection were disabled. Gradual selection was used to remove tie points that exceeded thresholds for the projection accuracy, reconstruction uncertainty, and reprojection error and the lens parameters were computed. Reference data from images DJI_814-817 were used to scale the sparse point cloud. The dense point cloud was then computed using the ‘High’ setting, followed by the textured mesh. The mesh model was exported in .obj and .pdf formats. A complete file list is provided in the README file that accompanies this dataset. This dataset is discussed in: Carlson et al. Quantifying iceberg deterioration using UAV imagery and Structure from Motion photogrammetry software. Submitted to <em>Remote Sensing.</em>