cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.3631710
title: iMGMC - integrated Mouse Gut Metagenomic Catalog

description: <em>Creation of an new mouse gut gene catalog with special features:</em> more diverse samples from different studies (12 Vendors incl. wild mice and various gut locations) clustering-free approach: all-in-one assembly, keeping track of each ORF to contigs to bins higher taxonomic resolution and more accuracy by using contigs for annotation 16S rRNA gene integration via linkage to bins expansion by 20,927 MAGs from sample-wise assembly of 871 mouse gut metagenomic samples, representing 1,296 species Code used: https://github.com/tillrobin/iMGMC The vast complexity of host-associated microbial ecosystems requires host-specific reference catalogs to survey the functions and diversity of these communities. We generated a comprehensive resource, the integrated mouse gut metagenome catalog (iMGMC), comprising 4.6 million unique genes and 660 metagenome-assembled genomes (MAGs) with many of them (485 MAGs, 73%) linked to reconstructed full-length 16S rRNA gene sequences. iMGMC enables unprecedented coverage and taxonomic resolution of the mouse gut microbiota, i.e. more than 92% of MAGs lack species-level representatives in public repositories (&lt;95% ANI match). The integration of MAGs and 16S rRNA gene data allows a more accurate prediction of functional profiles of communities than based on 16S rRNA amplicons alone. Accompanying iMGMC we provide a set of MAGs representing 1,296 gut bacteria obtained through complementary assembly strategies. We envision that integrated resources such as iMGMC together with MAG collections will enhance the resolution of numerous existing and future sequencing-based studies. Genecatalog: Description Size Filename<br> Catalog ORF sequences 1 GB iMGMC-GeneID.fasta.gz<br> Full assembly contigs 1.3 GB iMGMC-ConitgID.fasta.gz<br> Mapping File (GeneID-&gt;ContigID-&gt;BinID) 30 MB iMGMC-map-Gene-Contig-Bin.tab.gz<br> Taxonomic annotations 40 MB iMGMC_map_taxonomy.tar.gz<br> Functional annotations 36 MB iMGMC_map_functionality.tar.gz<br> 16S rRNA sequences 2 MB iMGMC-16SrRNAgenes.fasta Metagenome-assembled genomes (MAGs) : Description Size Filename<br> integrated MAGs 0.5 GB iMGMC_MAGs.tar.gz<br> representave mMAGs (n=1296) 1 GB iMGMC-mMAGs-dereplicated_genomes.tar.gz<br> representave hqMAGs (n=830) 0.7 GB iMGMC-hqMAGs-dereplicated_genomes.tar.gz<br> all mMAGs (n=20,927) 15 GB iMGMC-mMAGs.tar.gz<br> Annotations by CheckM, dRep-Clustering, GTDB-Tk 2 MB MAG-annotation_CheckM_dRep_GTDB-Tk.tar.gz<br> Functional annotations (hqMAGs by eggNOG mapper v2) 187 MB hqMAGs.emapper.annotations.gz
description: Acknowledgements: TS was funded by the Helmholtz Association (VH-NG-933), by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, STR-1343/1 and STR-1343/2) and the European Union (StG337251). JFB was funded by the DFG under Germany`s Excellence Strategy – EXC 22167-390884018 and by the DFG Collaborative Research Center (CRC) 1182 "Origin and Function of Metaorganisms". TC received funding from the DFG (project CL481/2-1 and grants within Collaborative Research Center 1382).
DOI: 10.5281/zenodo.3631711
title: iMGMC - integrated Mouse Gut Metagenomic Catalog

description: <em>Creation of an new mouse gut gene catalog with special features:</em> more diverse samples from different studies (12 Vendors incl. wild mice and various gut locations) clustering-free approach: all-in-one assembly, keeping track of each ORF to contigs to bins higher taxonomic resolution and more accuracy by using contigs for annotation 16S rRNA gene integration via linkage to bins expansion by 20,927 MAGs from sample-wise assembly of 871 mouse gut metagenomic samples, representing 1,296 species Code used: https://github.com/tillrobin/iMGMC The vast complexity of host-associated microbial ecosystems requires host-specific reference catalogs to survey the functions and diversity of these communities. We generated a comprehensive resource, the integrated mouse gut metagenome catalog (iMGMC), comprising 4.6 million unique genes and 660 metagenome-assembled genomes (MAGs) with many of them (485 MAGs, 73%) linked to reconstructed full-length 16S rRNA gene sequences. iMGMC enables unprecedented coverage and taxonomic resolution of the mouse gut microbiota, i.e. more than 92% of MAGs lack species-level representatives in public repositories (&lt;95% ANI match). The integration of MAGs and 16S rRNA gene data allows a more accurate prediction of functional profiles of communities than based on 16S rRNA amplicons alone. Accompanying iMGMC we provide a set of MAGs representing 1,296 gut bacteria obtained through complementary assembly strategies. We envision that integrated resources such as iMGMC together with MAG collections will enhance the resolution of numerous existing and future sequencing-based studies. Genecatalog: Description Size Filename<br> Catalog ORF sequences 1 GB iMGMC-GeneID.fasta.gz<br> Full assembly contigs 1.3 GB iMGMC-ConitgID.fasta.gz<br> Mapping File (GeneID-&gt;ContigID-&gt;BinID) 30 MB iMGMC-map-Gene-Contig-Bin.tab.gz<br> Taxonomic annotations 40 MB iMGMC_map_taxonomy.tar.gz<br> Functional annotations 36 MB iMGMC_map_functionality.tar.gz<br> 16S rRNA sequences 2 MB iMGMC-16SrRNAgenes.fasta Metagenome-assembled genomes (MAGs) : Description Size Filename<br> integrated MAGs 0.5 GB iMGMC_MAGs.tar.gz<br> representave mMAGs (n=1296) 1 GB iMGMC-mMAGs-dereplicated_genomes.tar.gz<br> representave hqMAGs (n=830) 0.7 GB iMGMC-hqMAGs-dereplicated_genomes.tar.gz<br> all mMAGs (n=20,927) 15 GB iMGMC-mMAGs.tar.gz<br> Annotations by CheckM, dRep-Clustering, GTDB-Tk 2 MB MAG-annotation_CheckM_dRep_GTDB-Tk.tar.gz<br> Functional annotations (hqMAGs by eggNOG mapper v2) 187 MB hqMAGs.emapper.annotations.gz
description: Acknowledgements: TS was funded by the Helmholtz Association (VH-NG-933), by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, STR-1343/1 and STR-1343/2) and the European Union (StG337251). JFB was funded by the DFG under Germany`s Excellence Strategy – EXC 22167-390884018 and by the DFG Collaborative Research Center (CRC) 1182 "Origin and Function of Metaorganisms". TC received funding from the DFG (project CL481/2-1 and grants within Collaborative Research Center 1382).
DOI: 10.6073/pasta/3536449c8a45492ae1fb20dadcc618ae
title: North Temperate Lakes LTER Regional Survey Water Chemistry 2015 - current

description: The Northern Highlands Lake District (NHLD) is one of the few regions in the world with periodic comprehensive water chemistry data from hundreds of lakes spanning almost a century. Birge and Juday directed the first comprehensive assessment of water chemistry in the NHLD, sampling more than 600 lakes in the 1920s and 30s. These surveys have been repeated by various agencies and we now have data from the 1920s (UW), 1960s (WDNR), 1970s (EPA), 1980s (EPA), 1990s (EPA), and 2000s (NTL). The 28 lakes sampled as part of the Regional Lake Survey have been sampled by at least four of these regional surveys including the 1920s Birge and Juday sampling efforts. These 28 lakes were selected to represent a gradient of landscape position and shoreline development, both of which are important factors influencing social and ecological dynamics of lakes in the NHLD. This long-term regional dataset will lead to a greater understanding of whether and how large-scale drivers such as climate change and variability, lakeshore residential development, introductions of invasive species, or forest management have altered regional water chemistry. The regional lakes survey in 2015 followed the standard LTER protocol for standard water chemistry and biology. Samples were taken as close to solar noon as possible. Seven lakes had replicates performed, which were chosen at random.
DOI: 10.5281/zenodo.3633267
title: Supplementary data for Design of hidden thermodynamic driving for non-equilibrium systems via mismatch elimination during DNA strand displacement

description: Data and processing scripts accompanying the publication.
DOI: 10.5281/zenodo.3633268
title: Supplementary data for Rational design of hidden thermodynamic driving for non-equilibrium systems via mismatch elimination during DNA strand displacement

description: Data and processing scripts accompanying the publication.
DOI: 10.5281/zenodo.3633287
title: IODP Expedition 361 Gas safety report

description: This composite report returns data from two different gas chromatograph configurations (GC3 and NGA). Each row combines data from several measurements made on the same sample at the same time for a particular headspace or vacutainer sample. If data do not exist for a particular expedition, the column does not appear. Gas samples were measured by gas chromatography and either flame ionization detection (GC-FID) or thermal conductivity detection (GC-TCD). Reported analytes may include methane, ethane, ethene, propane, propene, n-butane, i-butane, n-pentane, i-pentane, n-hexane, i-hexane, n-heptane, i-heptane, nitrogen, oxygen, carbon monoxide, carbon dioxide, and hydrogen sulfide. When data are available, methane to (ethane + ethene) ratio (C1/C2 ratio) is reported. To identify individual samples and tests, see each separate analysis (GC3, NGAFID, and/or NGATCD).
DOI: 10.5281/zenodo.3633288
title: IODP Expedition 361 Gas safety report

description: This composite report returns data from two different gas chromatograph configurations (GC3 and NGA). Each row combines data from several measurements made on the same sample at the same time for a particular headspace or vacutainer sample. If data do not exist for a particular expedition, the column does not appear. Gas samples were measured by gas chromatography and either flame ionization detection (GC-FID) or thermal conductivity detection (GC-TCD). Reported analytes may include methane, ethane, ethene, propane, propene, n-butane, i-butane, n-pentane, i-pentane, n-hexane, i-hexane, n-heptane, i-heptane, nitrogen, oxygen, carbon monoxide, carbon dioxide, and hydrogen sulfide. When data are available, methane to (ethane + ethene) ratio (C1/C2 ratio) is reported. To identify individual samples and tests, see each separate analysis (GC3, NGAFID, and/or NGATCD).
DOI: 10.25612/837.7bd3eqj8gody
title: 2018 Jefferson County Building Footprints
DOI: 10.5281/zenodo.3633064
title: Bio‐derived Carbon Nanofibres from Lignin as High‐Performance Li‐Ion Anode Materials

description: Development of cost‐effective and increasingly efficient sustainable materials for energy‐storage devices, such Li‐ion batteries, is of crucial future importance. Herein, the preparation of carbon nanofibres from biopolymer blends of lignin (byproduct from the paper and pulp industry) and polylactic acid (PLA) or a thermoplastic elastomeric polyurethane (TPU) is described. SEM analysis shows the evolving microstructural morphology after each processing step (electrospinning, stabilisation and carbonisation). Importantly, it is possible to tailor the nanofibre porosity by utilising miscibility/immiscibility rules between lignin and the polymer additive (PLA/TPU). PLA blends (immiscible) generate porous structures whereas miscible lignin/TPU blends are solid when carbonised. Electrodes produced from 50 % PLA blends have capacity values of 611 mAh g<sup>−1</sup> after 500 charge/discharge cycles, the highest reported to date for sustainable electrodes for Li‐ion batteries. Thus, this work will promote the development of lignocellulose waste materials as high‐performance energy‐storage materials.
DOI: 10.5281/zenodo.3633065
title: Bio‐derived Carbon Nanofibres from Lignin as High‐Performance Li‐Ion Anode Materials

description: Development of cost‐effective and increasingly efficient sustainable materials for energy‐storage devices, such Li‐ion batteries, is of crucial future importance. Herein, the preparation of carbon nanofibres from biopolymer blends of lignin (byproduct from the paper and pulp industry) and polylactic acid (PLA) or a thermoplastic elastomeric polyurethane (TPU) is described. SEM analysis shows the evolving microstructural morphology after each processing step (electrospinning, stabilisation and carbonisation). Importantly, it is possible to tailor the nanofibre porosity by utilising miscibility/immiscibility rules between lignin and the polymer additive (PLA/TPU). PLA blends (immiscible) generate porous structures whereas miscible lignin/TPU blends are solid when carbonised. Electrodes produced from 50 % PLA blends have capacity values of 611 mAh g<sup>−1</sup> after 500 charge/discharge cycles, the highest reported to date for sustainable electrodes for Li‐ion batteries. Thus, this work will promote the development of lignocellulose waste materials as high‐performance energy‐storage materials.
DOI: 10.7910/dvn/0khzmi/a4ffit
title: Debt Traps - Dataverse Files.zip

description: This folder contains all of the files necessary to replicate the results in the publication.
DOI: 10.5255/ukda-sn-854051
title: McStrike: Trade unions, collective action and social media, twitter data 2017
DOI: 10.5281/zenodo.3628733
title: Titulares y Catedráticos de Comunicación en Universidades Españoles

description: En este dataset se registran los titulares y catedráticos que obtuvieron plaza en una universidad pública española en el periodo 2000-2019. Los datos proceden del Boletín Oficial del Estado y se han extraído de forma automáticca (Elías Said) y manual (Rafael Repiso).
DOI: 10.5281/zenodo.3628734
title: Titulares y Catedráticos de Comunicación en Universidades Españoles

description: En este dataset se registran los titulares y catedráticos que obtuvieron plaza en una universidad pública española en el periodo 2000-2019. Los datos proceden del Boletín Oficial del Estado y se han extraído de forma automáticca (Elías Said) y manual (Rafael Repiso).
DOI: 10.5281/zenodo.3633301
title: IODP Expedition 361 Bulk density (GRA)

description: Gamma ray attenuation (GRA) data were acquired using a Cs-137 collimated source and a sodium iodide (thallium), or NaI(Tl), scintillation detector. The signal was calibrated using water and aluminum standards to provide a proxy for bulk density. This measurement was performed by a sensor mounted on either the Whole-Round Multisensor Logger (WRMSL) or the Special Task Multisensor Logger (STMSL); which track was used for a given data set is indicated in the data.
DOI: 10.5281/zenodo.3633302
title: IODP Expedition 361 Bulk density (GRA)

description: Gamma ray attenuation (GRA) data were acquired using a Cs-137 collimated source and a sodium iodide (thallium), or NaI(Tl), scintillation detector. The signal was calibrated using water and aluminum standards to provide a proxy for bulk density. This measurement was performed by a sensor mounted on either the Whole-Round Multisensor Logger (WRMSL) or the Special Task Multisensor Logger (STMSL); which track was used for a given data set is indicated in the data.
DOI: 10.5281/zenodo.3633303
title: IODP Expedition 361 Hole drilling summary

description: Report includes detailed drilling data: BHA length, bit parameters, and primary depth measurements.
DOI: 10.5281/zenodo.3633304
title: IODP Expedition 361 Hole drilling summary

description: Report includes detailed drilling data: BHA length, bit parameters, and primary depth measurements.
DOI: 10.5281/zenodo.3633306
title: IODP Expedition 361 Hole summary

description: Report lists hole data: location, water depth, drilling, coring system, and core recovery.
DOI: 10.3886/e112634v1-22089
title: Replication data for: Genetic Diversity and the Origins of Cultural Fragmentation

description: The origin of the uneven distribution of ethnic and cultural fragmentation across countries has been underexplored, despite the importance attributed to the effects of diversity on the stability and prosperity of nations. Building on the role of deeply-rooted biogeographical forces in comparative development, this research empirically demonstrates that genetic diversity, predominantly determined during the prehistoric "out of Africa" migration of humans, is an underlying cause of various existing manifestations of ethnolinguistic heterogeneity. Further research may revolutionize our understanding of how economic development and the composition of human capital across the globe are affected by these deeply-rooted factors.
DOI: 10.5281/zenodo.3633305
title: IODP Expedition 361 Hole summary

description: Report lists hole data: location, water depth, drilling, coring system, and core recovery.
DOI: 10.5281/zenodo.3633312
title: IODP Expedition 361 Ion chromatography

description: Cation and anion concentration in interstitial water samples was measured by ion chromatography using a conductivity detector. Cation analytes include calcium, magnesium, potassium, and sodium. Anion analytes include chloride, sulfate, and bromide.
DOI: 10.6084/m9.figshare.11775318.v5
title: Simulated significant wave height (3-hourly, 2015.01-2100.12) from FIO-ESM v2.0 ssp585 experiment r1i1p1f1

description: Simulated significant wave height (3-hourly, 2015.01-2100.12) from FIO-ESM v2.0 ssp585 experiment (one of future scenarios) r1i1p1f1. The grid, named gx1v6, is the displaced pole (the North Pole displaced to the Greenland) grid with 1.1 degree in longitude and 0.27-0.54 degree in latitude.
DOI: 10.5255/ukda-sn-853822
title: HomeSense UK household data 2017-2018
DOI: 10.5281/zenodo.3633311
title: IODP Expedition 361 Ion chromatography

description: Cation and anion concentration in interstitial water samples was measured by ion chromatography using a conductivity detector. Cation analytes include calcium, magnesium, potassium, and sodium. Anion analytes include chloride, sulfate, and bromide.
DOI: 10.5281/zenodo.3633314
title: IODP Expedition 361 Interstitial water composite report

description: This composite report includes data from numerous interstitial water (IW) analyses (e.g., ICP-LIQUIDS and IONCHROM) in a variable set of columns. Each row combines the data from several tests (groups of measurements made on the same sample at the same time) for a particular IW sample. If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate analysis (ALKALINITY, ICP-LIQUIDS, IONCHROM, SALINITY, SPECTRO, TITRATOR, and potentially others). Major and minor elements were determined by inductively coupled plasma-atomic emission spectrocsopy (ICP-LIQUIDS). Cations and anions were measured by ion chromatography (IONCHROM). Complex ions were measured by colorimetric measurements using a UV-VIS spectrometer (SPECTRO). Alkalinity and chloride was measured by titration (ALKALINITY and TITRATOR). Dissolved carbon (DC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) were measured by combustion in a total organic carbon (TOC) analyzer. Salinity was measured by refractometer (SALINITY). pH was measured by ion-selective electrode as part of the alkalinity procedure and is reported in the ALKALINITY analysis.
DOI: 10.5281/zenodo.3633315
title: IODP Expedition 361 Interstitial water composite report

description: This composite report includes data from numerous interstitial water (IW) analyses (e.g., ICP-LIQUIDS and IONCHROM) in a variable set of columns. Each row combines the data from several tests (groups of measurements made on the same sample at the same time) for a particular IW sample. If data do not exist for a particular expedition, the column does not appear. To identify individual samples and tests, see each separate analysis (ALKALINITY, ICP-LIQUIDS, IONCHROM, SALINITY, SPECTRO, TITRATOR, and potentially others). Major and minor elements were determined by inductively coupled plasma-atomic emission spectrocsopy (ICP-LIQUIDS). Cations and anions were measured by ion chromatography (IONCHROM). Complex ions were measured by colorimetric measurements using a UV-VIS spectrometer (SPECTRO). Alkalinity and chloride was measured by titration (ALKALINITY and TITRATOR). Dissolved carbon (DC), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC) were measured by combustion in a total organic carbon (TOC) analyzer. Salinity was measured by refractometer (SALINITY). pH was measured by ion-selective electrode as part of the alkalinity procedure and is reported in the ALKALINITY analysis.
DOI: 10.5281/zenodo.3633317
title: IODP Expedition 361 Bulk and grain density (MAD)

description: Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances. Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D). Dry volume (C or D) is measured by helium pycnometry. Submethods A and B are not recommended by IODP. Submethod C is suitable for saturated materials such as fine-grained sediments. Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.
DOI: 10.5281/zenodo.3633316
title: IODP Expedition 361 Bulk and grain density (MAD)

description: Moisture and density (MAD) data were acquired on ~10 mL sediment or rock samples by measuring three out of four material parameters: wet (saturated) mass, wet volume, dry mass, and/or dry volume after 24 h drying in a convection oven at 105 degrees C. From the moisture and volume measurements, the following phase relationships are calculated: wet and dry water content, wet bulk density, dry bulk density, grain density, porosity, and void ratio. The combination of measurements is defined by the submethod chosen: A, B, C, or D. Wet (A, B, or C) and dry (A, B, C, or D) mass is determined using motion-compensated balances. Wet volume is determined either by helium pycnometry (A) or by the sample's geometric dimensions using calipers (A or D). Dry volume (C or D) is measured by helium pycnometry. Submethods A and B are not recommended by IODP. Submethod C is suitable for saturated materials such as fine-grained sediments. Submethod D is suitable for unsaturated porous material such as certain limestones and basalts.