Find research datasets worth reusing

opencc-by-4.0Oct 2021View details →

Input data and Supplementary Results for "Turnover in life-strategies recapitulates marine microbial succession colonizing model particles"

README This page contains processed input data used for downstream analysis and some Supplementary Results for the paper: Pascual-García, A., Schwartzman, J., Enke, T.N., Iffland-Stettner, A., Cordero, O.X., Bonhoeffer, S., Turnover in life-strategies recapitulates marine microbial succession colonizing model particles (2022).   Input data   <ul> <li> File “count_table.ESV.biom”: Table containing the abundance of each Exact Sequence Variant (ESV) in the different samples (biom format). </li> <li> File “count-table_metagenomes_KEGGs.L3.spf”. Table containing the abundances of genes found in the shotgun metagenomics experiments annotated in KEGG and then aggregated into classes according to the finest classification in KEGG's hierarchy (level 3). This is a tsv-formatted file that can be directly used in STAMP to perform statistical analysis (spf format). </li> <li> File “count-table_PICRUST2_KEGGs.L3.spf”. Table containing the abundances of genes predicted with PICRUSt v2. These genes were annotated in KEGG and aggregated into classes according to the finest hierarchy in KEGG (level 3). This is a tsv-formatted file that can be directly used in STAMP to perform statistical analysis (spf format). </li> <li> File “count-table_Isolates_KEGGs.L3.spf”. Table containing the abundances of genes found in the isolates genomes that were annotated in KEGG and aggregated into classes according to the finest classification in KEGG's hierarchy (level 3). This is a tsv-formatted file that can be directly used in STAMP to perform statistical analysis (spf format). </li> <li> File “samples_metadata.tsv”. Metadata table describing the samples. </li> <li> File “isolates_metadata.tsv”. Metadata table describing the isolates, it includes shallow phylogenetic levels and a categorical identifier describing the environmental preference estimated for the ESV having a 100% sequence identity with a ZINB-GLM. </li> <li> File “sequences.ESV.fasta”. File containing the Exact Sequence Variants fasta. </li> </ul> Supplementary Materials   <ul> <li> File “qiime2_visualizations.zip”. A file containing visualizations compatible with the qiime2 viewer (simply drag and drop the file in <a href="https://view.qiime2.org/">https://view.qiime2.org/</a>) for each sample or combination of samples, labelled as `$substrate.$medium.$replicate`, where `$medium = {Beads, Seawater}`  and `$replicate = {A,B,C}`. If the label is not present for one field, it means that all samples are aggregated for that field e.g.: <ul> <li> “count_table.ESV.Chitosan.Beads.A.bar-plots.qzv” Contains the replicate experiment A for communities on the synthetic beads in chitosan. </li> <li> “count_table.ESV.Chitosan.bar-plots.qzv” Contains all samples in chitosan (both seawater communities and the three replicates of communities on the beads). </li> </ul> </li> <li> File “README.odt”. This readme in libreoffice format. </li> <li> File “Genome_deposition_information.xlsx”. NCBI identifiers for the isolates’ genomes. </li> <li> File "barcodes_to_samples_MGRAST.xlsx". Contains the barcodes of each sample and its metadata as it was deposited in MG-RAST. In a second tab, there is a subset of samples with a low number of reads that MG-RAST analyzed together, generating a single entry (termed "mixed"). </li> <li> Access to raw an processed metagenomes and analysis are provided through MG-RAST following [this link](<a href="https://www.mg-rast.org/mgmain.html?mgpage=project&project=mgp85635">https://www.mg-rast.org/mgmain.html?mgpage=project&project=mgp85635</a>). <ul> <li> As of May 30th, 2022, there are two issues with the dataset in MG-RAST which are out of our scope to solve. We will report any update here. The first problem is related to the entry TCCTGAGC-GTAAGGAG-s_2_, which does not load in MG-RAST. These are very low samples and were discarded in most analyses. In addition, you will find in the metadata 17 metagenomes that do not belong to our project. </li> </ul> </li> </ul>

opencc-by-4.0May 2022View details →

Data supporting 'Controls on Greenland moulin geometry and evolution from the Moulin Shape model'

The data included here are MouSh model results generated as part of the following publication: Andrews, L. C., Poinar., K, Trunz, C. (2022). Controls on Greenland moulin geometry and evolution from the Moulin Shape model. The Cryosphere.  Nearly all meltwater from glaciers and ice sheets is routed englacially through moulins. Therefore, the geometry and evolution of moulins has the potential to influence subglacial water pressure variations, ice motion, and the runoff hydrograph delivered to the ocean. We develop the Moulin Shape (MouSh) model, a time-evolving model of moulin geometry. MouSh models ice deformation around a moulin using both viscous and elastic rheologies and melting within the moulin through heat dissipation from turbulent water flow, both above and below the water line. We force MouSh with idealized and realistic surface melt inputs. Our results show that variations in surface melt change the geometry of a moulin by approximately 10% daily and over 100% seasonally. These size variations cause observable differences in moulin water storage capacity and moulin water levels compared to a static, cylindrical moulin. Our results suggest that moulins are storage reservoirs for meltwater, with storage capacity and water levels varying over multiple timescales. Representing moulin geometry within subglacial hydrologic models may therefore improve the representation of subglacial pressures, especially over seasonal periods or in regions where overburden pressures are high. These data are also accessible at: https://ubir.buffalo.edu/xmlui/handle/10477/82587 The development of the MouSh model was funded by NASA Cryosphere grant 80NSSC19K0054 to Lauren Andrews and Kristin Poinar.

opencc-by-4.0May 2022View details →

Source data belonged to "Geometric flow control in lateral flow assays: Macroscopic single-phase modeling"

This record contains all the necessary data to obtain the results of the study "Geometric flow control in lateral flow assays: Macroscopic single-phase modeling" (<a href="https://doi.org/10.1063/5.0093316">https://doi.org/10.1063/5.0093316</a>).

Model output data and code for Zhang et al., Cross-cutting scenarios and strategies for designing decarbonization pathways in the transport sector toward carbon neutrality

Model output data and code for "Zhang et al., Cross-cutting scenarios and strategies for designing decarbonization pathways in the transport sector toward carbon neutrality" in Nature Communications.

Supplementary Data: OpenCOVID model output underlaying Figures 1 and 2 of "Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden"

Supplementary data files Figure_1.xlsx and Figure_2.xlsx contain the model simulation outcomes for Figures 1 and 2 of <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock et al</a> "Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden" (2022) <ul> <li>Figure 1: Peak daily hospital occupancy (number of beds per 100,000 population over the six-month simulation period) for three variant properties; infectivity (relative to Delta), immune evading capacity (%), and severity (relative to Delta)  </li> <li>Figure 2: Percentage of COVID-19 infections and deaths averted by third-dose vaccines for adults and vaccinating 5-11-year-olds with doses one and two.  </li> <li>Open access source-codes of the associated plotting functions are published <a href="http://zenodo.org/record/6532404#.Yqw7cezMKdb">here</a> on Zenodo.  </li> <li>Open access source-codes for the OpenCOVID model of all analyses as presented in <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock et al. (2022)</a> are publicly available at <a href="https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src">https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src</a>.  </li> <li>Detailed model descriptions and model equations of individual-based transmission model OpenCOVID are described in <a href="https://pubmed.ncbi.nlm.nih.gov/34923396/">Shattock et al. (2022)</a> and <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock et al. (2022).</a></li> </ul>

RDA Data Stewardship Organisational Models Survey 2021 Output Dataset

Data Stewardship comes in many forms and contexts, with the common goal of supporting data management. Yet that diversity can make it hard for the RDM community to further professionalise our work and services. The RDA Professionalising Data Stewardship Interest Group (PDS-IG) Models Task Group sought input from the research data community to help model different approaches to research data stewardship through an online survey in October to November 2021. An offline copy of the survey is available as a linked resource from this record. This dataset consists of a cleaned, anonymised responses from 136 respondents, though not all questions were answered by all respondents. The output are available in a CSV formatted file containing the full response set along with output from a thematic textual analysis undertaken on responses to a number of open-text questions in the survey.

Training and validation data used to produce the pre-trained model for the TomoTwin paper.

This datasets represents the training and validation data that was used to produce the pre-trained model for the TomoTwin paper. Please see 10.5281/zenodo.6637357 for the raw tomograms.

opencc-by-4.0Sep 2021View details →

Data collection for article "Quantifying Local Ecosystem Service Outcomes by Modelling Their Supply, Demand and Flow in Myanmar's Forest Frontier Landscape"

This dataset contains the nine ecosystem service models (in .neta format) underlying the publication "Quantifying Local Ecosystem Service Outcomes by Modelling Their Supply, Demand and Flow in Myanmar’s Forest Frontier Landscape". The ecosystem models were implemented using the commercial software Netica (version 6.05) for constructing and analysing Bayesian Networks.

opencc-by-4.0Mar 2022View details →

Historic data of the national electricity system transitions in Europe in 1990–2019 for retrospective evaluation of models [dataset]

This data package supports empirical analysis of national electricity system transitions and retrospective evaluation of electricity system models in 1990–2019 in 31 European countries, including the EU27, Switzerland, Iceland, Norway, and the United Kingdom. The data package covers two types of content. Firstly, we provide an annotated list of 528 original data sources and references relevant for retrospective electricity system modeling with emphasis on open-access sources. Secondly, we provide a total of 1359 processed and harmonized data files in a format that is suitable as inputs to electricity system models. Four types of data files are included for each country: (i) a country file documenting national demand and economic data, (ii) technology files describing techno-economic data for each major generation technology in the country's electricity mix, (iii) resource files describing fuel prices and CO2 emissions for each fuel, and (iv) load profiles describing 24-hour national load curves for each available year. We provide these data files as comma-separated files to enable their wider reuse for retrospective evaluation of models as well as for empirical analyses of the European electricity system transitions.

opencc-by-4.0Sep 2021View details →

Data associated with the manuscript "Simple statistical models can be sufficient for testing hypotheses with population time series data"

This is a revised version of the archive of R code and data used in the manuscript, Simple statistical models can be sufficient for testing hypotheses with population time series data. The data are in three files. etodata1.csv and etodata2.csv contain two versions of the same data for shoal-dwelling fishes in the Etowah River and associated environmental covariates. knz_dat contains data for small mammals collected in the Konza Prairie Biological Station and associated environmental covariates. The R code consists of four primary files that call nine auxiliary files. CaseStudy1-main_code and CaseStudy2-main_code are the primary files for running the two case studies. Simulations1 and Simulations2 are the files for running the two batteries of simulations. We thank the Konza Prairie Biological Station and Konza Prairie Long-Term Ecological Research Program supported by the National Science Foundation (DEB-1440484) for collecting and providing access to mammal community data. More details are in the manuscript and supporting information.

Model output and PTt marker data for van Agtmaal et al., 2022 (in review), Frontiers in Earth Science

Model output for reproduction of key figures in the manuscript van Agtmaal et al. titled "Quantifying continental collision dynamics for Alpine-style orogens" currently under revision in Frontiers in Earth Science

isoTWAS models using 48 GTEx tissues and PsychENCODE data (07.04.22)

isoTWAS models for 48 GTEx tissues, adult frontal cortex tissue from the CommonMind Consortium (subset of PsychENCODE project; Gandal et al 2018, Science), and fetal frontal cortext from Walker et al 2019, Cell. Each folder corresponds to a separate tissue and contains 1 .tsv.gz file per gene that contains the isoTWAS model. Refer to https://bhattacharya-a-bt.github.io/isotwas/ on how to use these models.

opencc-zeroJul 2022View details →

dryad40/100

Transformed crane data from: Balancing structural complexity with ecological insight in spatio-temporal species distribution models

The potential for statistical complexity in species distribution models (SDMs) has greatly increased with advances in computational power. Structurally complex models provide the flexibility to analyse intricate ecological systems and realistically messy data, but can be difficult to interpret, reducing their practical impact. Founding model complexity in ecological theory can improve insight gained from SDMs. Here, we evaluate a marked point process approach, which uses multiple Gaussian random fields to represent population dynamics of the Eurasian crane (Grus grus) in a spatio-temporal species distribution model. We discuss the role of model components and their impacts on predictions, in comparison with a simpler binomial presence/absence approach. Inference is carried out using Integrated Nested Laplace Approximation (INLA) with inlabru, an accessible and computationally efficient approach for Bayesian hierarchical modelling, which is not yet widely used in SDMs. Using the marked point process approach, crane distribution was predicted to be dependent on the density of suitable habitat patches, as well as close to observations of the existing population. This demonstrates the advantage of complex model components in accounting for spatio-temporal population dynamics (such as habitat preferences and dispersal limitations) that are not explained by environmental variables. However, including an AR1 temporal correlation structure in the models resulted in unrealistic predictions of species distribution; highlighting the need for careful consideration when determining the level of model complexity. Increasing model complexity, with careful evaluation of the effects of additional model components, can provide a more realistic representation of a system, which is of particular importance for a practical and impact-focused discipline such as ecology (though these methods extend to applications for a wide range of systems). Founding complexity in contextual theory is not only fundamental to maintaining model interpretability, but can be a useful approach to improving insight gained from model outputs.

Data accompanying "A new brittle rheology and numerical framework for large-scale sea-ice models"

Data accompanying "A new brittle rheology and numerical framework for large-scale sea-ice models" by E. Olason et al, accepted for publication in Journal of Advances in Modelling Earth Systems (2022). Files: * CS2SMOS.tar.bz2: Contains Cryosat2/SMOS data, post-precessed and used to   produce figures comparing modelled thickness to observations. * deformation_maps_demo.ipynb: An example jupyter notebook to read pairs.npz * OlasonEtAl_BBM.tar.bz2: Thickness fields from the MEB run used to produce   figure 1 (netCDF). * OlasonEtAl_MEB.tar.bz2: Thickness fields from the BBM run used to produce   figure 8 (netCDF). * OlasonEtAl_mEVP.tar.bz2: Thickness fields from the mEVP run used to produce   figure 8 (netCDF). * pairs.npz: Displacement pairs derived from the model's Lagrangian mesh used   to produce figures 3, 4, and 5 (numpy data file). * Winter2006_7_BBM.nc.bz2: Thickness, concentration, and velocity fields from   the BBM run for the winter 2006-7 widely used in the paper (netCDF). * Winter2006_7_mEVP.nc.bz2: Thickness, concentration, and velocity fields from   the mEVP run for the winter 2006-7 used for comparison in the paper   (netCDF).

A physically interpretable data-driven surrogate model for wake steering

PALM input files for the simulations performed in the study "A physically interpretable data-driven surrogate model for wake steering"  by Sengers et al. (2022).  The PALM code is available at <a href="https://palm.muk.uni-hannover.de/">https://palm.muk.uni-hannover.de</a> Additional information to the input files is given in the README file Cite this as: B.A.M. Sengers (2022). Dataset: A physically interpretable data-driven surrogate model for wake steering. https://doi.org/10.5281/zenodo.6821164

Data from: Modeling the drivers of eutrophication in Finland with a machine learning approach

The dataset contains data on characteristics of 1547 Finnish EU Water Framework Directive monitored lakes and their catchments from years 2016-2019.   Usage notes The zip-file contains catchment and lake characteristics data to support the main analysis code in Github (link) (‘Analyses and visualization’) which produces results, figures and tables presented in the study ‘Modeling the drivers of eutrophication in Finland with a machine learning approach’. Detailed information about the data can be found in the ‘README.docx’ file.

opencc-by-4.0Jun 2024View details →

Labeled data and models for COVID-19 vaccine related tweets with stance, location, and topics

The dataset contains Tweet IDs along with the location and tweet timestamp. The tweets are labeled based on motivating/demotivating status, stance towards the COVID-19 vaccine, and topic in the tweet text. To comply with Twitter guidelines, we removed the tweet texts and author information. You can use Hydrator API to hydrate the tweets. The repository also contains the machine-learning models for topic modeling, de/motivation classifier, and stance detection from the tweets.

Systematic review reveals sexually antagonistic knockouts in model organisms data and code

R Code and data for manuscript titled "Systematic review reveals sexually antagonistic knockouts in model organisms". Drosophila data is from Ruzicka, F., Hill, M.S., Pennell, T.M., Flis, I., Ingleby, F.C., Mott, R., Fowler, K., Morrow, E.H., Reuter, M., 2019. Genome-wide sexually antagonistic variants reveal long-standing constraints on sexual dimorphism in fruit flies. PLoS Biol. 17, e3000244. https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000244 Human data is from Harper, J.A., Janicke, T., Morrow, E.H., 2021. Systematic review reveals multiple sexually antagonistic polymorphisms affecting human disease and complex traits. Evolution 75, 3087–3097. https://doi.org/10.1111/evo.14394 https://onlinelibrary.wiley.com/doi/full/10.1111/evo.14394

Data used in a manuscript entitled "Large ensemble simulation for investigating predictability of precursor vortices of Typhoon Faxai in 2019 with a 14-km mesh global nonhydrostatic atmospheric model" submitted to Geophysical Research Letters

This include a dataset used in a manuscript entitled “Large ensemble simulation for investigating predictability of precursor vortices of Typhoon Faxai in 2019 with a 14-km mesh global nonhydrostatic atmospheric model” by Yamada and co-authors, which is submitted to Geophysical Research Letters. Contact: Yohei Yamada (yoheiy@jamstec.go.jp)

Data from: Improved FIFRELIN de-excitation model for neutrino applications

New FIFRELIN cascades for the isotopes 156,158Gd are distributed to the community, to be used for various applications. The new cascades feature an improved modeling of de-excitation. The main improvements are: 1) Inclusion of primary transitions from EGAF database. 2) Treatment of gamma-directional correlations 3) Improved physics for the Internal Conversion process and X ray emission. With the use of the files provided, please cite the following publication: H. Almazán et al, <a href="http://doi.org/10.1140/epja/s10050-023-00977-x">The European Physical Journal A volume 59, Article number: 75 (2023)</a>  DOI: <a href="http://doi.org/10.1140/epja/s10050-023-00977-x">https://doi.org/10.1140/epja/s10050-023-00977-x</a>