cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.48597/c53r-p6c6
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.48597/ceqk-qkmr
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.48597/sdyr-vzn9
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.48597/sfxj-mkk9
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.5281/zenodo.11248366
title: Input data for 1d EVP model

description: Data here is the input needed for running the 1D EVP model referenced here:

Rasmussen, T. A. S., Poulsen, J., Ribergaard, M. H., & Rethmeier, S. (2024). dmidk/cice-evp1d: Unit test refactorization of EVP solver CICE (refactorevp1d_v0.1). EGU V. Zenodo. https://doi.org/10.5281/zenodo.10782548.

This is based on a restart on the 2020030100 from the NAAg domain. 

Ponsoni Leandro, Ribergaard Mads Hvid, Nielsen-Englyst Pia, Wulf Tore, Buus-Hinkler Jørgen, Kreiner Matilde Brandt, Rasmussen Till Andreas Soya; Greenlandic sea ice products with a focus on an updated operational forecast system; Frontiers in Marine Science, Volume 10,2023;10.3389/fmars.2023.979782
DOI: 10.5281/zenodo.3728600
title: CICE gx1 WOA Forcing Data - 2020.03.20

description: This file contains the gx1 WOA forcing data for CICE. The latest information about CICE forcing data and files can be found at the GitHub Resource Index: https://github.com/CICE-Consortium/About-Us/wiki/Resource-Index under the "Input Data" link. These data are provided by the CICE Consortium (https://github.com/CICE-Consortium).
DOI: 10.5281/zenodo.5208241
title: CICE gx1 Grid and Initial Condition Data - 2021.08.16

description: Updated initial condition files with monthly initial states for 2005. Updated with new weight mask.
DOI: 10.5281/zenodo.8118062
title: CICE gx1 JRA55do Forcing Data by year - 2023.07.03

description: These files contain the gx1 JRA55do forcing data by year for CICE. The latest information about CICE forcing data and files can be found at the GitHub Resource Index: https://github.com/CICE-Consortium/About-Us/wiki/Resource-Index under the "Input Data" link. This is a dataset remapped from the original JRA55do dataset (Tsujino et al. 2018; https://doi.org/10.1016/j.ocemod.2018.07.002; version 1.5.0.1). These data are provided by the CICE Consortium (https://github.com/CICE-Consortium).
DOI: 10.5281/zenodo.8136635
title: Secondary data: Describing the Status Quo of Person-Centred Dementia Care within Different Types of Care Units in German Nursing Homes

description: This is the secondary data set and R-Code of R statistical software (version 4.2.1) to investigate the differences and commonalities in the existence of policies regarding person-centred dementia care (PCDC) measured with the Dementia Policy Questionnaire (DemPol-Q) in different care unit types in German nursing homes using a contingency table and Fisher’s exact test. The data from the secondary data analysis were collected in the “BeStaDem” Survey Study, funded by the German Research Foundation (DFG, project number: 430919791), and performed by Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) e.V., site Witten. This quantitative analysis is one part of the article “Describing the Status Quo of Person-Centred Dementia Care within Different Types of Care Units in German Nursing Homes – A Convergent Mixed Methods Study”.
description: The data frame DemPol-Q_Data_PUB.sav was also used in our article "Hoffmann AL, Bergmann JM, Fahsold A, Müller-Widmer R, Roes M, Holle B, et al. Measuring person‑centred care in german nursing homes – exploring the construct validity of the Dementia Policy Questionnaire: a cross‑sectional study of a secondary data set. BMC Geriatrics. 2022;22(914):1-12.https://doi.org/10.1186/s12877-022-03586-3". You can finde the data set here: Hoffmann, Anna Louisa, Bergmann, Johannes Michael, Fahsold, Anne, Mueller-Widmer, René, Holle, Bernhard, Roes, Martina, & Palm, Rebecca. (2022). Secondary Data: Measuring Person-centred Care in German Nursing Homes – Exploring Construct Validity of the Dementia Policy Questionnaire using Adjusted Multiple Correspondence Analysis [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6912951

The data set CU_Types_PUB comprises the typology of care units in German nursing homes developed by Bergmann et al. (2023). Reference: Bergmann JM, Hoffmann AL, Müller-Widmer R, Palm R. Typology of Dementia-Specific Care Units: A Nationwide Survey Study in Germany. Innovation in Aging. 2023.https://doi.org/10.1093/geroni/igad062. Data set: Bergmann, Johannes Michael, Hoffmann, Anna Louisa, Mueller-Widmer, René, & Palm, Rebecca. (2022). Supplementary material for: "Typology of Dementia-Specific Care Units: A Nationwide Survey Study in Germany" (Version 1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7215066
DOI: 10.15472/wjgj7v
title: Registros Primates Neotropicales Convocatoria APC

description: Este es el resultado de la iniciativa para la consolidación de una base de datos de registros georreferenciados de primates en el país. La convocatoria se desarrolló por la Asociación Primatológica Colombiana (APC) y con el apoyo del Instituto Alexander von Humboldt (IAvH), el Sistema de Información Biológica (SiB), y el Laboratorio de Ecología de Bosques Tropicales y Primatología (LEBTYP) de la Universidad de Los Andes. Agrupa y divulga la información disponible sobre presencia de primates en Colombia, Brasil, Ecuador, Perú, Costa Rica y México. Esta iniciativa pretende fomentar ciencia abierta y la colaboración entre investigadores e instituciones.
DOI: 10.1594/wdcc/gome-evl_water_vapor_clim_v2.2
title: The GOME-Evolution total column water vapor "climate" product (Version 2.2)

description: Project: GOME Evolution - Within the ESA GOME Evolution project, two different total column water vapor (TCWV) products are developed and applied to the satellite instruments GOME, SCIAMACHY, and GOME-2: 1. The "climate" product with focus on consistent time series of monthly means 2. The "advanced AMF algorithm" (A3) product with focus on accurate retrievals for individual pixels. The GOME Evolution project is funded by European Space Agency (ESA) under contract no. 4000110429 Summary: The "climate" water vapor product developed within ESA's "GOME-Evolution" project provides a consistent time series of monthly mean global maps of total column water vapor derived from the satellite instruments GOME, SCIAMACHY, and GOME-2 (Metop-A). Consistency amongst the different instruments (including cloud treatment) is substantially improved by (1) merging SCIAMACHY and GOME-2 observations to GOME pixel size, and (2) reducing the GOME-2 swath width to GOME/SCIAMACHY swath, thereby mimicking GOME-like observation conditions for all three sensors. This is Version 2.2
DOI: 10.17632/2wby3b28zc.1
title: Replication Package: Systemic Bank Runs without Aggregate Risk: How a Misallocation of Liquidity May Trigger a Solvency Crisis

description: The code in this replication package generates all figures and tables in the paper "Systemic Bank Runs without Aggregate Risk: How a Misallocation of Liquidity May Trigger a Solvency Crisis".
DOI: 10.17632/rdky78bk8r.2
title: Data for "Best Practices for Your Exploratory Factor Analysis: a Factor Tutorial" published by RAC-Revista de Administração Contemporânea

description: This repository contains material related to the analysis performed in the article "Best Practices for Your Exploratory Factor Analysis: a Factor Tutorial". The material includes the data used in the analyses in .dat format, the labels (.txt) of the variables used in the Factor software, the outputs (.txt) evaluated in the article, and videos (.mp4 with English subtitles) recorded for the purpose of explaining the article. The videos can also be accessed in the following playlist: https://youtube.com/playlist?list=PLln41V0OsLHbSlYcDszn2PoTSiAwV5Oda. Below is a summary of the article: "Exploratory Factor Analysis (EFA) is one of the statistical methods most widely used in Administration, however, its current practice coexists with rules of thumb and heuristics given half a century ago. The purpose of this article is to present the best practices and recent recommendations for a typical EFA in Administration through a practical solution accessible to researchers. In this sense, in addition to discussing current practices versus recommended practices, a tutorial with real data on Factor is illustrated, a software that is still little known in the Administration area, but freeware, easy to use (point and click) and powerful. The step-by-step illustrated in the article, in addition to the discussions raised and an additional example, is also available in the format of tutorial videos. Through the proposed didactic methodology (article-tutorial + video-tutorial), we encourage researchers/methodologists who have mastered a particular technique to do the same. Specifically, about EFA, we hope that the presentation of the Factor software, as a first solution, can transcend the current outdated rules of thumb and heuristics, by making best practices accessible to Administration researchers".
DOI: 10.22008/fk2/x9u5bf
title: Geological map of Greenland, 1:500 000, Sheet 3, Kangerlussuaq / Søndre Strømfjord - Nuussuaq, 2nd edition

description: Geologisk kort over Grønland / Geological map of Greenland - 1:500 000, central West Greenland,
DOI: 10.48597/d4ww-6r3c
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.48597/jsm5-bmf4
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.48597/r9g7-wt8r
title: Measurement of Ozone at Lough Navar

description: Measurement of Ozone at Lough Navar
DOI: 10.5066/p92faasd
title: Streamflow Drought Metrics for Select United States Geological Survey Streamgages for Three Different Time Periods from 1921 - 2020

description: This metadata record describes a series of datasets containing metrics used to characterize drought for four sets of United States Geological Survey (USGS) streamgages in the conterminous United States (CONUS) for three different time periods between 1921 and 2020 outlined below. The streamgages used are a subset based on the criteria used in Geospatial Attributes of Gages for Evaluating Streamflow, version II (GAGESII, Falcone, 2011). Time periods use climate years, April 1 through March 31. These metrics include streamflow percentiles, identified drought events, annual low streamflow drought statistics, and various attributes for each of those events. These data are arranged here by study group with the following child items: 1) Select CONUS-wide GAGES-II streamflow drought metrics for the period 1921-2020. 2) Select CONUS-wide GAGES-II streamflow drought metrics for the period 1951-2020. 3) Select CONUS-wide GAGES-II streamflow drought metrics for the period 1980-2020. 4) Select Colorado River basin GAGES-II streamflow drought metrics for the period 1980-2020.
DOI: 10.5067/aura/omi/data3002
title: OMI/Aura TOMS-Like Ozone and Radiative Cloud Fraction Daily L3 Global 0.25x0.25 deg
DOI: 10.5067/kuc55jevo1sr
title: Aqua/AIRS L3 Monthly Standard Physical Retrieval (AIRS+AMSU) 1 degree x 1 degree V7.0
DOI: 10.5281/zenodo.11266662
title: Supplementary data to the paper "Large scale voxel-based FEM formulation for NMR relaxation in porous media"

description: This repository contains supplementary data to the paper "Large scale voxel-based FEM formulation for NMR relaxation in porous media", which is being considered for publication. The files are:**_data.zip - Binary image files;

FEM_T2_**.csv - T2 simulation results using finite elements;

FEM_**_inv.csv - T2 inversion for the finite element simulations;

RW_T2_**.csv - T2 simulation results using random walk;

RW_**_inv.csv - T2 inversion for the random walk simulations;

local_digital_correction.c - Vector containing the local geometry correction factors, accessed integers formed by the 8-bit binary key of the node neighborhood;

Where ** is the rock type:

AC - Austin Chalk

BS - Berea Stripe

DP - Desert Pink

IB - Idaho Brown

Obs.: in order to obtain the relaxation curves the following parameters were utilized in the simulations:

Bulk diffusivity: 2500 micro-m2/s (all rock samples) 

Bulk relaxation: 2.6 s (all rock samples)

Voxel size: {1.0; 2,0; 0.9; 2.0} micro-m (for AC, BS, DP, IB respectively)

Surface relaxivity: {23.3; 12.1; 12.3; 8.3} micro-m/s (for AC, BS, DP, IB respectively)
DOI: 10.5281/zenodo.5367383
title: ResOpsUS

description: Reservoir operations dataset that contains daily time series data of storage, inflow, outflow, elevation and evaporation for all the large dams in the Contiguous United States
DOI: 10.5281/zenodo.7439166
title: Ruegeria pomeroyi digital microbe databases

description: These databases consolidate a variety of datasets related to the model organism Ruegeria pomeroyi DSS-3. The data were primarily generated by members of the Moran Lab at the University of Georgia, and put together in this format using anvi'o v7.1-dev through the collaborative efforts of Zac Cooper, Sam Miller, and Iva Veseli (special thanks to Christa Smith and Lidimarie Trujillo Rodriguez for their help with gene annotations). The data includes: - (R_POM_DSS3-contigs.db) the complete genome and megaplasmid sequence of R. pomeroyi, along with highly-curated gene annotations established by the Moran Lab and automatically-generated annotations from NCBI COGs, KEGG KOfam/BRITE, Pfams, and anvi'o single-copy core gene sets. It also contains annotations for the Moran Lab's TnSeq mutant library. - (PROFILE-VER_01.db) read-mapping data from multiple transcriptome and metatranscriptome samples generated by the Moran lab to the R. pomeroyi genome. Some coverage data is stored in the AUXILIARY-DATA.db file. This data can be visualized using anvi-interactive. Publicly-available samples are labeled with their SRA accession number. - (R_pom_reproducible_workflow.md) a reproducible workflow describing how the databases were generated.
DOI: 10.5281/zenodo.7517480
title: Alteromonas Digital Organism Databases

description: This is the home of the database for the <em>Alteromonas</em> Digital Organism, one of C-CoMP's collaborative efforts. This database was created in anvi'o (v7.1) primarily by Michelle DeMers (Massachusetts Institute of Technology) and Rogier Braakman (Massachusetts Institute of Technology), with significant help from members of the Meren Lab (A. Murat Eren, Iva Veseli, and Matthew Schechter) and Moran Lab (Zac Cooper). This version upload consists of: Alteromonas_Pangenome_v1_1.md: A reproducible workflow that details making the <em>Alteromonas</em> digital organism, from fasta files to database creation. alteromonas_genomes_databases_v1.tar.gz: A compressed directory consisting of all contigs databases used to make the digital organism. external-genomes-v1.txt: Text file consisting of a list of the genomes used in this digital organism with ID, strain, and source information. Alteromonas-GENOMES-v1.db: Genomes storage database created in anvi'o from all of the contigs files and external-genomes file. Alteromonas_Pangenome_v1.1.tar.gz: Compressed file containing the <em>Alteromonas</em> pangenome (digital organism). misc_Alteromonas_Pan_v1.tar.gz: Compressed directory containing any information that anvi'o created when forming the pangenome. *concatenated-proteins.fa: Concatenated core protein files for all three types of core gene sets. RAxML_bestTree*: Trees determined for all three sets of core genes from RAxML. midpoint_complete_*: Midpoint rooted trees for all three sets of core genes. layer_orders.txt: Tab-delimited file used to import newick tree into the pangenome.
DOI: 10.5281/zenodo.7924420
title: Lagrangian trajectory dataset for AMOC lower limb

description: These Lagrangian trajectory files were generated by TRACMASS, a Lagrangian parcel tracing algorithm, using data from a high-resolution (1/12o) ocean sea-ice hindcast. Two set of experiments were performed to trace the Atlantic Meridional Overturning Circulation (AMOC) lower limb; 1) Initiated only southward trajectories across the Fram Strait (fs) that corresponds to Arctic outflow and 2) traced only northward trajectories across the easten Subpolar North Atlantic (SPNA) Section which corresponds to Atlantic inflow and associated with the North Atlantic Current (nac).


_ini.csv = store positions and properties of trajectories at the starting location


_run.csv = store positions and properties of trajectories during the trajectory simulation


_out.csv = store positions and properties of trajectories at the ending location


_rerun.csv = This file is used to select trajectories that have reached a particular ending section. Column 2 in this file contain kill zone flag. Flag 1 means trajectories reaching the surface, 2 indicates trajectories reaching the Fram Strait , 3 means trajectories reaching the eastern SPNA section and finally 4 illustrate trajectories aprroaching the Barents Sea.


TRACMASS documentation is available at https://www.tracmass.org/docs.html
DOI: 10.5439/1110710
title: ARM: Shortwave Array Spectroradiometer-Hemispheric, NIR Aerosol Optical Depths

description: Shortwave Array Spectroradiometer-Hemispheric, NIR Aerosol Optical Depths
DOI: 10.5439/1110768
title: ARM: Shortwave Array Spectroradiometer-Hemispheric, VIS Aerosol Optical Depths

description: Shortwave Array Spectroradiometer-Hemispheric, VIS Aerosol Optical Depths
DOI: 10.5439/1461660
title: Cimel Sunphotometer Quality Checked and filtered Aerosol Optical Thickness

description: This is a quality checked aerosol optical depth (version 3) data ingested from Aeronet.
DOI: 10.5440/1798170
title: End-of-Winter Snow Depth, Temperature, Density, and SWE Measurements at Teller Road Site, Seward Peninsula, Alaska, 2019

description: Measurements of end-of-winter snow properties were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) from March 31 to April 7, 2019. This dataset contains three *.csv data files of spatially distributed values of snow depth, snow water equivalent (SWE), and temperature at the snow surface and at the bottom of the snowpack. Data were collected toward the end of the winter season from late March to early April, when the snowpack would be near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used to improve collection efficiency and enhance spatial coverage. A user guide included as a *.pdf. This dataset is a continuation of the previous end- of-winter snow surveys conducted at the Teller Road Site in 2016-2018 (Wilson et al., 2020; https://doi.org/10.5440/1592103). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
DOI: 10.5440/1887250
title: End-of-Winter Snow Depth, Temperature, Density, and SWE Measurements at Teller Road Site, Seward Peninsula, Alaska, 2022

description: Measurements of end-of-winter snow properties were collected at the NGEE Arctic Teller Road Site at mile marker 27 (TL_MM27) from March 28 to April 1, 2022. This dataset contains three *.csv data files of spatially distributed values of snow depth, snow water equivalent (SWE), and temperature at the snow surface and at the bottom of the snowpack. Data were collected toward the end of the winter season from late March to early April, when the snowpack would be near its maximum. A Snow-Hydro MagnaProbe (http://www.snowhydro.com/products/column2.html) was used to improve collection efficiency and enhance spatial coverage. A user guide included as a *.pdf. This dataset is a continuation of the previous end-of-winter snow surveys conducted at the Teller Road Site in 2016-2018 (Wilson et al., 2020; https://doi.org/10.5440/1592103) and 2019 (Bennett et al., 2021; https://doi.org/10.5440/1798170). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
DOI: 10.5523/bris.3vjlolgemmsza2m65dovn8gyah
title: Out-of-vacuum bag consolidation of composites for manufacturing multi-matrix composites

description: Data for the paper of Arjun Radhakrishnan et al: "Out-of-vacuum bag consolidation of composites for manufacturing multi-matrix composites". The work has been supported by the EPSRC through the ACCIS Doctoral Training Centre [grant number EP/G036772/1]. This work was also supported by the EPSRC through the Future Composites Manufacturing Research Hub [EP/ P006701/1] as part of the Core Project “Manufacturing for structural applications of multifunctional composites”.
DOI: 10.5676/eum_saf_cm/gvap/v001
title: The GEWEX water vapor assessment archive of water vapour products from satellites and reanalyses

description: The GEWEX Data and Assessments Panel (GDAP) initiated the GEWEX Water Vapor Assessment (G-VAP) which has the main objectives
	to quantify the current state of art in water vapour products being constructed for climate applications and to support the 
	selection process of suitable water vapour products by GDAP for its production of globally consistent water and energy cycle 
	products. During the construction of the G-VAP data archive freely available and mature satellite and reanalysis data records 
	with a minimum temporal coverage of ten years were considered. The data archive contains total column water vapour as well 
	as specific humidity and temperature at four pressure levels (1000, 700, 500, 300 hPa). The following data records are 
	elements of the G-VAP archive: AIRWAVE, AMSR-E (JAXA, REMSS), ATOVS, CFSR, EMiR, ERA-20C, ERA-Interim, GOME/SCIAMACHY/GOME2, 
	HOAPS, JRA-55, MERIS, MERRA, MERRA2, MODIS-AQUA, NVAP-M (Ocean, Climate), REMSS, SSM/I+MERIS, and TMI (further details 
	at http://www.gewex-vap.org/?page_id=309). All data records were remapped to a regular longitude/latitude grid of 2°x2°. 
	The data archive consists of four different folders: 22 TCWV data records covering the period 2003-2008, 11 TCWV data records 
	covering the period 1988-2008 as well as seven specific humidity and seven temperature data records covering the period 
	1988-2009. Besides comprehensive metadata the files contain spatio-temporal averages of TCWV in units of kg/m2, of 
	specific humidity in units of g/kg and of temperature in units of K.     
	
	The data is available at http://gewex-vap.org/?page_id=969.