cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr38464.v2
title: Annotated Clinical MRIs and Linked Metadata of Patients with Acute Stroke, Baltimore, Maryland, 2009-2019
title: Version 2

description: This is a collection of 2,888 clinical MRIs of patients admitted at a National Stroke Center, over ten years, with clinical diagnosis of acute or early subacute stroke. The collection includes diverse MRI modalities and protocols. The infarct core was manually defined in the diffusion weighted images; the images are provided in native subject space and in standard space (MNI), in Neuroimaging Informatics Technology Initiative (NIfTI) format. The data format and organization follows Brain Imaging Data Structure (BIDS) guidelines. The collection includes diverse metadata, comprised of demographic information, basic clinical profile (NIH Stroke Scale/Score (NIHSS), hospitalization duration, blood pressure at admission, BMI, and associated health conditions), and expert description of the acute lesion. This resource provides high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.
description: The purpose of the study was to provide high quality, large scale, human-supervised knowledge to feed artificial intelligence models and enable further development of tools to automate several tasks that currently rely on human labor, such as lesion segmentation, labeling, calculation of disease-relevant scores, and lesion-based studies relating function to frequency lesion maps.
description: Datasets: DS1: Annotated Clinical MRIs and Linked Metadata of Patients with Acute Stroke, Baltimore, Maryland, 2009-2019
description: record abstracts
DOI: 10.5287/bodleian:pzq8zyxnz
title: WEALTHPOL 1 Micro-data Wealth Information and Attitudes Dictionary Dataset
DOI: 10.5281/zenodo.6866114
title: Data and Code for figures of "Long-range transport and fate of DMS-oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes"

description: This database includes the material to create the figures in "Measurement Report: Long-range transport and fate of DMS-oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes" and the analyzed time series of all atmospheric variables presented.
DOI: 10.5281/zenodo.6866115
title: Data and Code for figures of "Long-range transport and fate of DMS-oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes"

description: This database includes the material to create the figures in "Measurement Report: Long-range transport and fate of DMS-oxidation products in the free troposphere derived from observations at the high-altitude research station Chacaltaya (5240 m a.s.l.) in the Bolivian Andes" and the analyzed time series of all atmospheric variables presented.
DOI: 10.5281/zenodo.6816429
title: Submitted data in re: Macrophage NFATC2 Mediates Angiogenic Signaling During Mycobacterial Infection

description: Dataset accompanying "Macrophage NFATC2 Mediates Angiogenic Signaling During Mycobacterial Infection". This dataset was uploaded to Zenodo using the "zen4R" packages from CRAN in the R programming environment. Updates to the scripts in this repository will primarily be able to be found at https://github.com/jaredbrewer/image-analysis.
description: Supported by NIH grants AI130236, AI125517, and AI166304 (D.M.T.) and HL160239 (W.J.B.)
DOI: 10.5281/zenodo.6816428
title: Submitted data in re: Macrophage NFATC2 Mediates Angiogenic Signaling During Mycobacterial Infection

description: Dataset accompanying "Macrophage NFATC2 Mediates Angiogenic Signaling During Mycobacterial Infection". This dataset was uploaded to Zenodo using the "zen4R" packages from CRAN in the R programming environment. Updates to the scripts in this repository will primarily be able to be found at https://github.com/jaredbrewer/image-analysis.
description: Supported by NIH grants AI130236, AI125517, and AI166304 (D.M.T.) and HL160239 (W.J.B.)
DOI: 10.25824/redu/reety6
title: dataset_deep_tech_article-rausp.csv
DOI: 10.25824/redu/nbrf7u
title: Inputs of national entrepreneurial ecosystem & outputs of deep-tech startups

description: This is a database that we created by collecting data from 2 different sources, namely: Global Innovation Index (GII), CrunchBase. The first comprises (GII) key variables that aim to evaluate de inputs of an entrepreneurial ecosystem. They are: Political environment, Regulatory environment, Business environment, Education, Tertiary education, Research and development, Information and communication technologies, General infrastructure, Ecological sustainability, Credit, Investment, Market size, Knowledge workers, Innovation linkages, Knowledge absorption. The second (CrunchBase) has one of the most important variables used to measure ambitious entrepreneurial activity: number of deep-tech startups. All was collected at national level, and all range from 0 to 1, using min-max method to normalization.
DOI: 10.5287/bodleian:mvg80dxny
title: Long-Run Wealth Inequality Dataset
DOI: 10.57833/cidacs/o6th5u
title: Medida de distanciamento social em outros países

description: Dados referentes ao monitoramento da mobilidade nas áreas residenciais e não-residenciais em outros países, desagregado por região e sub-região, no período entre 15 de fevereiro de 2020 e 15 de outubro de 2022. Esta medida de tendência de mobilidade é calculada diariamente segundo seis dimensões e pode ser útil ao conhecimento sobre como se deu a adesão às medidas de distanciamento social adotadas durante a pandemia em cada lugar.
DOI: 10.57833/cidacs/olhira
title: Medida de distanciamento social no Brasil

description: Dados referentes ao monitoramento da mobilidade nas áreas residenciais e não-residenciais nos municípios e estados do Brasil, no período entre 15 de fevereiro de 2020 e 15 de outubro de 2022. Esta medida de tendência de mobilidade é calculada diariamente segundo seis dimensões e pode ser útil ao conhecimento sobre como se deu a adesão às medidas de distanciamento social adotadas durante a pandemia em cada lugar.
DOI: 10.21223/64dnhf/tzmayk
title: 03_DataDictionary_LBHT_advanced_OXA.tab

description: :unav
DOI: 10.21223/64dnhf/2cpvuf
title: 01_Advanced_Trial_LBHTC2_Oxapampa_2021-2022.tab

description: :unav
DOI: 10.21223/64dnhf/szpfxc
title: 02_Field_Layout_Advanced_Trial_LBHTC2_Oxapampa_2021-2022.tab

description: :unav
DOI: 10.57833/cidacs/wbdi09
title: Campanha nacional de vacinação contra Covid-19 no Brasil

description: Registros de vacinação referentes à campanha de vacinação contra Covid-19 no Brasil, disponibilizados pelo Ministério da Saúde por meio do Sistema de Informação do Programa Nacional de Imunizações (SI-PNI). Tratam-se dos dados desidentificados e individualizados acerca das doses aplicadas, com informações sobre idade, gênero, município de residência, data da aplicação, estabelecimento de saúde da aplicação, tipo da vacina, identificação da dose, etc.
DOI: 10.17909/e40m-z102
title: Data from SPT0607 Paper

description: HST data on SPT-CL J0607-4448, used in Masterson et al. 2022 (Evidence for AGN-Regulated Cooling in Clusters at z ~ 1.4: A Multi-Wavelength View of SPT-CL J0607-4448)
DOI: 10.5066/p92d15j8
title: Gravity data and geophysical gradient data of the Stockton 30 x 60 minute quadrangle, California

description: This data release presents point data associated with the geologic and geophysical maps of the Stockton 30 x 60 minute quadrangle, California. Data include principal fact information for new gravity measurements collected by the U.S. Geological Survey from 2015 to 2018 and for existing gravity data. Gravity and magnetic gradients were also calculated in the Stockton 30 x 60 minute quadrangle, California. The gravity data have been processed to isostatic residual gravity anomalies that reflect crustal density variations. Maximum horizontal gradients were calculated from gravity and magnetic potential grids of the Stockton quadrangle to map out structures that juxtapose rocks of differing density and magnetization, respectively.
DOI: 10.6073/pasta/a425174e1b1247d7dac4ee6a17bf9bee
title: Database of Geographic Information: Change in groundwater level, Central Arizona-Phoenix, 1985-2000

description: Change in Level of Groundwater in central Arizona-Phoenix, 1985-2000. This file shows spatial changes in groundwater levels for two separate time periods: 1985-1989 and 1996-2000. This is a spatial data object with a Coordinate Reference System (CRS) of EPSG:3479 NAD83(NSRS2007) / Arizona Central (ft); https://www.spatialreference.org/ref/epsg/3479/). The coordinate reference system (CRS) associated with these data when they were constructed initially was misrepresented in early versions (&lt;= knb-lter-cap.101.8) of this dataset. The CAP LTER has attempted to assign a CRS based on reasonable values but the accuracy of the identified CRS cannot be certain.
DOI: 10.6084/m9.figshare.21712106
title: Supplementary files Norberg 2020

description: <strong>Identification of Genetic Loci Associated with Five Agronomic Traits in Alfalfa Using</strong> <strong>Multi-Environment Trials</strong>
DOI: 10.5281/zenodo.7317325
title: Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data

description: WebAUGUSTUS input and output data used in for eukaryotic gene prediction in <em>Sirsoe methanicola</em>: <strong>WebAUGUSTUS input data:</strong> capitella.fa - Nucleotide genomic sequence of <em>Capitella teleta</em> (NCBI accession: GCA_000328365.1) capitella-protein.faa - Protein sequences in the <em>Capitella teleta </em>genome (NCBI accession: GCA_000328365.1) big-contigs-wrapped.fa - Contigs &gt;= 3,000 bp long assembled from the <em>S. methanicola </em>metagenomes (NCBI BioProject ID PRJNA689840) that did not bin into any bacterial MAGs small-contigs-wrapped.fa - Contigs&lt; 3,000 bp long assembled from the <em>S. methanicola </em>metagenomes (NCBI BioProject ID PRJNA689840) that did not bin into any bacterial MAGs <strong>WebAUGUSTUS output data:</strong> augustus.bigcontigs.gff - WebAUGUSTUS GFF output file for contigs &gt;=3,000 bp augustus.smallcontigs.gff - WebAUGUSTUS GFF output file for contigs &lt;3,000 bp augustus.all.faa - All protein sequences predicted from the <em>S. methanicola </em>metagenomes using WebAUGUSTUS
DOI: 10.5281/zenodo.7317326
title: Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data

description: Datasets used in "Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data"
DOI: 10.5281/zenodo.7324091
title: Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data

description: Datasets used in "Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data"
DOI: 10.5281/zenodo.7327996
title: Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data

description: Datasets used in "Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data"
DOI: 10.5281/zenodo.7429720
title: Genetic Features of the Marine Polychaete Sirsoe methanicola from Metagenomic Data

description: WebAUGUSTUS input and output data used in for eukaryotic gene prediction in <em>Sirsoe methanicola</em>: <strong>WebAUGUSTUS input data:</strong> capitella.fa - Nucleotide genomic sequence of <em>Capitella teleta</em> (NCBI accession: GCA_000328365.1) capitella-protein.faa - Protein sequences in the <em>Capitella teleta </em>genome (NCBI accession: GCA_000328365.1) big-contigs-wrapped.fa - Contigs &gt;= 3,000 bp long assembled from the <em>S. methanicola </em>metagenomes (NCBI BioProject ID PRJNA689840) that did not bin into any bacterial MAGs small-contigs-wrapped.fa - Contigs&lt; 3,000 bp long assembled from the <em>S. methanicola </em>metagenomes (NCBI BioProject ID PRJNA689840) that did not bin into any bacterial MAGs <strong>WebAUGUSTUS output data:</strong> augustus.bigcontigs.gff - WebAUGUSTUS GFF output file for contigs &gt;=3,000 bp augustus.smallcontigs.gff - WebAUGUSTUS GFF output file for contigs &lt;3,000 bp augustus.all.faa - All protein sequences predicted from the <em>S. methanicola </em>metagenomes using WebAUGUSTUS
DOI: 10.5281/zenodo.7429820
title: Appendix 3.2 HLF FOI request.xlsx

description: This dataset comes from a FOI request to the HLF regarding funded projects related to black history/heritage that have a digital component.
DOI: 10.5281/zenodo.7429819
title: Appendix 3.2 HLF FOI request.xlsx

description: This dataset comes from a FOI request to the HLF regarding funded projects related to black history/heritage that have a digital component.
DOI: 10.6084/m9.figshare.6815705
title: JARVIS-DFT 2D dataset (jdft_2d.json)

description: Dataset for 2D materials Websites: 1) https://jarvis.nist.gov/jarvisdft ,<br> 2) https://jarvis-tools.readthedocs.io/en/master/databases.html , 3) https://jarvis-tools.readthedocs.io/en/master/publications.html <br> Loading the dataset: <br> unzip d2-12-12-2022.json.zip <br> import os, json import pandas as pd f = open('d2-12-12-2022.json', 'r') data2d=json.load(f) f.close() <br> df=pd.DataFrame(data2d) print (df) <br> or <br> pip install jarvis-tools from jarvis.db.figshare import data data2d = data('dft_2d') <br> ######################################### For more details about using the dataset, use the jupyter-notebooks: https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks
DOI: 10.6084/m9.figshare.6815705.v7
title: JARVIS-DFT 2D dataset (jdft_2d.json)

description: Website: https://www.ctcms.nist.gov/~knc6/JVASP.html<br><br>Dataset for 2D materials<br>#########################################Lading the dataset:<br>import os,jsonimport pandas as pdf = open(os.path.join(os.getcwd(),'jdft_2d-4-26-2020.json'),'r')data2d=json.load(f)f.close()df=pd.DataFrame(data2d)<br>#########################################For more details about using the dataset, use the jupyter-notebooks:https://github.com/usnistgov/jarvis
DOI: 10.6084/m9.figshare.20779072.v1
title: Data for "Snow Effective Grain Size and Albedo Patterns Mapped from UAV Hyperspectral Imaging to Assess Landsat 9 OLI Pixel Variability: A Case Study from Senator Beck Basin, Colorado"

description: Uploaded here are the UAV-hyperspectral datacubes and ASD field spectrometer measurements used in the manuscript submitted to Frontiers in Remote Sensing entitled " Snow Effective Grain Size and Albedo Patterns Mapped from UAV Hyperspectral Imaging to Assess Landsat 9 OLI Pixel Variability: A Case Study from Senator Beck Basin, Colorado". Dataset includes: UAV-hyperspectral mosaic datacube in raw reflectance UAV-hyperspectral mosaic relfectance datacube which has been vicariously calibrated following the methods outlined in the paper. ASD field spectrometer point measurements (HDRF) GPS coordinates for each ASD measurement
DOI: 10.6084/m9.figshare.20779072.v2
title: Data for "Snow Effective Grain Size and Albedo Patterns Mapped from UAV Hyperspectral Imaging to Assess Landsat 9 OLI Pixel Variability: A Case Study from Senator Beck Basin, Colorado"

description: Uploaded here the code and data repository for "UAV hyperspectral imaging for multi-scale assessment of Landsat 9 effective snow grain size and albedo" published in Frontiers of Remote Sensing (2022/2023). <br> Description of the data and scripts that are located in the repository. <br> field_spectrometer This folder contains two matlab data files. 1) "ASD spectra" contains 34 ASD field spectrometer reflectance measurements that are resampled to the Resonon NIR-HSI wavelengths. 2) "ASD_gps_coordinates" contains UTM coordinates for for the 34 ASD field spectrometer meassurments from (1). Example: ASD_spec(:,1) is located at ASD_coords(1,:). <br> landsat_retrievals This folder contains Landsat 9 grain size and albedo retrievals, and corresponding statistical runs as geotiffs. <br> nir_hsi_mosaics (1)This folder contains the mosaiced reflectance datacube pre- and post-vicarious calibration. (2) The grain size retrieval for the post-vicariously calibrated reflectance mosaic (3) The raw radiance mosaic (used for georeference in the spatial comparison script) <br> matlab_code albedo_landsat_visualization contains the proram that performs the spatial analysis between ASD, UAV-HSI, and Landsat. The UAV-HSI albedo calculation is also performed in this program. <br> <br> grain_size_retreival contains the grain size retrieval algroithms for ASD and NIR-HSI and the corresponding SNICAR lookup table for a 41deg zenith angle. <br> matlab functions folder should be in the path and are called in the codes provdied. <br> <br> THE SOFTWARE 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.
DOI: 10.6084/m9.figshare.6815699
title: JARVIS-DFT 3D dataset (jdft_3d.json)

description: Dataset for 3D materials <br> Websites: 1) https://jarvis.nist.gov/jarvisdft ,<br> 2) https://jarvis-tools.readthedocs.io/en/master/databases.html , 3) https://jarvis-tools.readthedocs.io/en/master/publications.html <br> Loading the dataset: <br> unzip jdft_3d-12-12-2022.json.zip import os, json import pandas as pd f = open(' jdft_3d-12-12-2022.json', 'r') data3d=json.load(f) f.close() df=pd.DataFrame(data3d) print (df) <br> or <br> pip install jarvis-tools from jarvis.db.figshare import data data2d = data('dft_3d') <br> ######################################### For more details about using the dataset, use the jupyter-notebooks: https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks<br> <br>
DOI: 10.5281/zenodo.7030038
title: Arctic specimens in the NHMO DNA bank Fish & Herptile collection 2022

description: All Arctic specimens in the NHMO DNA bank Fish & Herptile collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7030037
title: Arctic specimens in the NHMO DNA bank Fish & Herptile collection 2022

description: All Arctic specimens in the NHMO DNA bank Fish & Herptile collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7429853
title: Arctic specimens in the NHMO DNA bank Fish & Herptile collection 2022

description: All Arctic specimens in the NHMO DNA bank Fish & Herptile collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7030026
title: Arctic specimens in the NHMO DNA bank Arthropod collection 2022

description: All Arctic specimens in the NHMO DNA bank Arthropod collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7030025
title: Arctic specimens in the NHMO DNA bank Arthropod collection 2022

description: All Arctic specimens in the NHMO DNA bank Arthropod collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7429843
title: Arctic specimens in the NHMO DNA bank Arthropod collection 2022

description: All Arctic specimens in the NHMO DNA bank Arthropod collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7030007
title: Arctic specimens in the NHMO Mammal collection 2022

description: All Arctic specimens in the NHMO Mammal collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7429827
title: Arctic specimens in the NHMO Mammal collection 2022

description: All Arctic specimens in the NHMO Mammal collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5281/zenodo.7030006
title: Arctic specimens in the NHMO Mammal collection 2022

description: All Arctic specimens in the NHMO Mammal collection as of August 2022. See Johannessen et al. 2023 "Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)" for further details.
description: {"references": ["Johannessen et al. 2023. Arctic specimens in the zoological collections at the Natural History Museum, University of Oslo, Norway (NHMO)"]}
DOI: 10.5517/ccdc.csd.cc298d44
title: CCDC 2123225: Experimental Crystal Structure Determination

description: Related Article: Aron Peter|2022|CSD Communication|||
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.cc29l85c
title: CCDC 2132712: Experimental Crystal Structure Determination

description: Related Article: Claudia Castillo, Asiloé J. Mora, Marilia Guillén, Pilar delgado-Niño, Cesar Araque, Edward Ávila, Ricardo R. Contreras, Gerzon E. Delgado|2023|J.Mol.Struct.|1275|134640|doi:10.1016/j.molstruc.2022.134640
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.