Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
85
datasets available to search
ShareScore release 0.9.0
Dataset results
85 results for “Resource Modelling”
Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California
<p>This dataset contains input files for the Weather Research and Forecasting (WRF) model related to the manuscript "Evaluating mesoscale model predictions of diurnal speedup events in the Altamont Pass Wind Resource Area of California," to be submitted to the <em>Journal of Applied Meteorology and Climatology</em> by Arthur, et al. Included are:</p> <ul> <li><strong>namelist.wps</strong>: used by the WRF preprocessing system (WPS) to configure the model domain and initial/boundary conditions</li> <li><strong>Vtable.HRRR</strong>: used by WPS to process data from the High-Resolution Rapid Refresh (HRRR) model for WRF initial/boundary conditions</li> <li><strong>namelist.input.mynn</strong>: used to run the MYNN PBL simulation</li> <li><strong>namelist.input.3dpbl</strong>: used to run the 3D PBL simulation</li> <li><strong>windturbines.txt</strong>: used to define the location and type of wind turbines included in the simulations</li> <li><strong>wind-turbine-*.tbl</strong>: used to define the parameters of each turbine type (see Table 1 in Arthur et al.) <ul> <li><strong>1</strong>: NREL 1.7MW, H=80m, D=103m</li> <li><strong>2</strong>: NREL 2.3MW, H=80m, D=107m</li> <li><strong>3</strong>: NREL 2.3MW, H=80m, D=116m</li> <li><strong>4</strong>: Vestas V47 0.66MW, H=60m, D=47m</li> <li><strong>5</strong>: Bonus B54 1.0MW, H=55m, D=54m</li> </ul> </li> </ul> <p>This work was prepared by LLNL under Contract DE-AC52-07NA27344.</p>
A model of within-host interactions between host resources, macroparasite infection and immune response
Open the record for dataset details and reuse information.
Resources for: Spatio-temporal integrated Bayesian species distribution models reveal lack of broad relationships between traits and range shifts
Open the record for dataset details and reuse information.
Code: A model of wild bee populations accounting for spatial heterogeneity and climate induced temporal variability of food resources at the landscape level
Open the record for dataset details and reuse information.
Extending Grime’s CSR model to predict plant demographic responses across resource availability gradients: evidence from the Patagonian steppes
Open the record for dataset details and reuse information.
Model executable, output, drivers and parameters for modeling organism acclimation to changing availability of and requirements for substitutable and interdependent resources
Files used to generate the data for figures in: Rastetter, EB, Kwiatkowski, BL. An approach to modeling resource optimization for substitutable and interdependent resources. Ecological Modelling (2020). https://doi.org/10.1016/j.ecolmodel.2020.109033. This paper presents a hierarchical approach to modeling organism acclimation to changing availability of and requirements for substitutable and interdependent resources. Substitutable resources are resources that fill the same metabolic or stoichiometric need of the organism. Interdependent resources are resources whose acquisition or expenditure are tightly linked (e.g., light, carbon dioxide, and water in photosynthesis and associated transpiration). We illustrate the approach by simulating the development of vegetation with four substitutable sources of nitrogen that differ only in the cost of their uptake and assimilation.
Dataset accompanying paper submission for "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"
<p>This data set accompanies code archived at DOI: <a href="https://doi.org/10.5281/zenodo.3833186">10.5281/zenodo.3833186</a>, which was used in the experiments for the paper submission "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"</p>
A multi-omics systems vaccinology resource to develop and test computational models of immunity: 1st challenge dataset and submissions
<p>The goal of the CMI-PB prediction contest is to foster a collaborative research community that can collectively tackle challenges and accelerates scientific progress beyond the capabilities of individual researchers or groups. The CMI-PB consortium has curated multi-source data from multiple individuals, encompassing Ab titers (around four antibodies/features), cell frequency (approximately 20 cell types/features), gene expression (roughly 50,000 RNA transcripts/features), and plasma proteomics (around 50 proteins/features). The challenge requires integrating these diverse data sources to predict different immune responses or tasks. Specifically, you will utilize multi-source data from several individuals on day 0 (baseline) to predict specific immune responses at later time points (1, 3, 7, and 14 days post-booster vaccination).</p> <p>The first CMI-PB challenge, which is an internal challenge, was conducted using datasets from 2020 (train) and 2021 (test). In the following sections, we provide detailed information on the datasets, challenge tasks, submission format, descriptions, and access to the necessary data files for participants to develop their models and make predictions.</p> <p><br><strong>A) Multiomics CMI-PB dataset:</strong></p> <p>We propose a study design that enables a systems-level understanding of the immune responses through computational modeling. Our cohort comprises aP vs. wP infancy-primed subjects boosted with Tdap. We recruit individuals born before 1995 (wP) and after 1996 (aP), collect baseline plasma and blood samples, and then at 1, 3, 7 and 14 days post booster vaccination.</p> <p>With the obtained samples processed, we generated omics data by:</p> <ul> <li> <p>Bulk PBMCs transcriptomics,</p> </li> <li> <p>Plasma proteomics using Olink, which provides a quantitative readout of cytokines, chemokines, and other immune factors,</p> </li> <li> <p>Cell frequency in PBMCs using flow cytometry,</p> </li> <li> <p>Tdap-specific antibodies levels</p> </li> </ul> <p><strong>B) List of tasks can be accessed using the “List of tasks for challenge 1.docx” file, and submissions need to submit in provided format here: “submission template challenge 1.tsv”</strong></p> <p><strong>C) Datasets for model building and making predictions:</strong></p> <p> Data files are divided into two categories: 1) raw dataset and 2) computable matrices.</p> <ol> <li> <p><strong>Raw dataset: </strong>This raw-most dataset is divided into training and test datasets. </p> </li> <li> <p><strong>Computable matrices: </strong>There are three different types of computable matrices. a) Full: These files are generated by dividing raw files into sub-files specific to planned days specific to vaccination. b) harmonized: These are generated by preserving only overlapping features between train and test datasets. b) imputed: MICE imputation is performed to impute missing values in the dataset.</p> </li> </ol> <p><strong>D) Submission evaluation</strong></p> <p>This folder contains all submitted models with ranking files and code for evaluating these models.</p> <p><strong>To learn more about the CMI-PB prediction challenge, visit our website at www.cmi-pb.org.</strong></p>
Effects of enhanced productivity of resources shared by predators in a food-web module: Comparing results of a field experiment to predictions of mathematical models of intra-guild predation
<p>This dataset contains data from a field experiment described in the publication "Wise, D. H. & Farfan, M.A. (2021) Effects of enhanced productivity of resources shared by predators in a food-web module: Comparing results of a field experiment to predictions of mathematical models of intra-guild predation. Ecology and Evolution, 00: 1-11. <a href="https://doi.org/10.1002/ece3.8375">https://doi.org/10.1002/ece3.8375</a>".</p> <p>The field experiment compared the response to increased input of nutrients and energy (artificial detritus) to an empirical model of intra-guild predation (IGP) to the predictions of published, simple mathematical models of asymmetric IGP (a generalist IG Predator that feeds both on a specialist IG Prey and a Resource that it shares with the IG Prey). The empirical model was a food-web module created by pooling species abundances across many families in a community of soil micro-arthropods into three response variables: IG Predator (large predatory mites), IG Prey (small predatory mites) and a shared Resource (fungivorous mites and springtails). The pattern of change over time in densities of the three response variables (IG Predator, IG Prey and Resource) was compared to the predictions of mathematical models of IGP to determine if the feeding relationships in this community of soil micro-arthropods could be abstracted into a simple IGP module. Thus, we were testing the hypothesis that IGP is a dominant organizing principle in this community.</p> <p>Simple mathematical models predict that increased input of nutrients and energy to the shared Resource will increase the equilibrium density of Resource and IG Predator, but will decrease that of IG Prey. By the experiment's end, densities of fungivores (Resource) had increased ~1.5x (ratio of pooled fungivore densities in the High treatment to plots with no addition of detritus (None treatment); and IG Predator densities had increased ~4x. Contrary to the prediction of mathematical models, IG Prey had not decreased, but instead had increased ~1.5x. We discuss possible reasons for the failure of the empirical model to agree with IGP theory.</p>
Model and data for: Economical defense of resources structures territorial space use in a cooperative carnivore
<p>Manuscript Abstract: Ecologists have long sought to understand space use and mechanisms underlying patterns observed in nature. We developed an optimality landscape and mechanistic territory model to understand mechanisms driving space use and compared model predictions to empirical reality. We demonstrate our approach using gray wolves (<i>Canis lupus</i>). In the model, simulated animals selected territories to economically acquire resources by selecting patches with greatest value, accounting for benefits, costs, and tradeoffs of defending and using space on the optimality landscape. Our approach successfully predicted and explained first- and second-order space use of wolves, including the population's distribution, territories of individual packs, and influences of prey density, competitor density, human-caused mortality risk, and seasonality. It accomplished this using simple behavioral rules and limited data to inform the optimality landscape. Results contribute evidence that economical territory selection is a mechanistic bridge between space use and animal distribution on the landscape. This approach and resulting gains in knowledge enable predicting effects of a wide range of environmental conditions, contributing to both basic ecological understanding of natural systems and conservation. We expect this approach will demonstrate applicability across diverse habitats and species, and that its foundation can help continue to advance understanding of spatial behavior.</p> <p>Model & Data Abstract: In support of the above manuscript, all model files and data to re-create the analyses for the manuscript are included on Dryad. The model can be run in NetLogo (installation file included), using the associated input files to build the Montana landscape for wolves. Expertise in NetLogo is strongly recommended for using this model. Output files are likewise included along with code to create each plot in the manuscript and SI. Software files for the model and code to create each plot in the manuscript are located at Zenodo: https://doi.org/10.5281/zenodo.5802243.</p>
Case study on an integrated interoperable metadata model for geoscience information resources
<p>An integrated metadata schema was created to promote interoperability and to characterize historically collected geoscience data. The metadata standard describes the steps taken to develop a switching‐across methodology that allows geoscience metadata standards (ISO 19115, CSDGM, ANZLIC and INSPIRE) to communicate with one another. We also demonstrated a real example of one of the switching‐across that was created. A representative metadata schema was created using items from harmonization standards that might be optimally mapped. Semantic interoperability allows users to access equivalent classes across several metadata standards in a uniform and consistent rule. It also tries to provide fundamental aspects that might characterize acquisition information to enhance data reuse and current metadata standards for data preservation and distribution.</p> <p>This dataset contains 5 data and contains the content standard of each of the four metadata schema and the metadata information of integrated metadata schema.</p> <ul> <li>data_ISO19115.xlsx: Core level of metadata elements for geographic resources of ISO 19115</li> <li>data_CSDGM.xlsx: Content Standard for Digital Geospatial Metadata of CSDGM</li> <li>data_INSPIRE.xlsx: Content Standard of INSPIRE metadata modeldata_ANZLIC.xlsx: Content Standard of ANZLIC Metadata Profile</li> <li>data_integrated model.xlsx: metadata class and their elements in the integrated interoperable metadata model</li> </ul>
Human review for post-training improvement of low-resource language performance in large language models
<p>Large language models (LLMs) have significantly improved natural language processing, holding the potential to support health workers and their clients directly. Unfortunately, there is a substantial and variable drop in performance for low-resource languages. Here we present results from an exploratory case study in Malawi, aiming to enhance the performance of LLMs in Chichewa through innovative prompt engineering techniques. By focusing on practical evaluations over traditional metrics, we assess the subjective utility of LLM outputs, prioritizing end-user satisfaction. Our findings suggest that tailored prompt engineering may improve LLM utility in underserved linguistic contexts, offering a promising avenue to bridge the language inclusivity gap in digital health interventions.</p>
The global water resources and use model WaterGAP v2.2e: streamflow calibration and evaluation data basis
<p>The data collection covers the streamflow data used for calibrating and validating the global water use and availability model WaterGAP v2.2e. The collection is a result of a data selection, assessment and merge effort from three data sources (GRDC, GSIM, ADHI) for in total 1509 stations. The stations are co-registered to the DDM30 (Döll & Lehner 2002) according their best hydrological fit.</p> <p>Please see the readme.md for details. Version 1.1 contains now the shapefiles as a zip instead single files which makes downlad more convenient.</p> <p> </p>
Resource-Centric Goal Model Slicing for Detecting Feature Interactions
<p>Supplementary materials of the paper entitled:</p> <p>“Resource-Centric Goal Model Slicing for Detecting Feature Interactions”</p> <p>file01 - The features related to the concept of Decline-Mutual-Exclusion.<br> file02 - The features related to the concept of Decline-Produce-and-Use<br> file03 - The features related to the concept of Decline-State-Changing<br> file04 - The features related to the concept of Enhanced-State-Changing<br> file05 - Zoom-features-2022</p>
Model output for "A high-resolution physical-biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12)"
<p>This dataset contains the numerical model output files that were used in the analysis presented in "A high-resolution physical-biogeochemical model for marine resource applications in the Northwest Atlantic (MOM6-COBALT-NWA12)", submitted to Geoscientific Model Development.</p>
Data from: genetic resources of macroalgae: development of an efficient method using microsatellite markers in non-model organisms
<p><span>Red and brown seaweeds are species with high ecological and economic importance. Here we report the feasibility of cost-effective molecular marker development in 6 species from different clades. Microsatellites markers of two brown seaweed species <em>Alaria esculenta</em>, <em>Pylaiella littoralis</em>, and of four red seaweed species <em>Calliblepharis jubata</em>, <em>Gracilaria gracilis</em>, <em>Gracilaria dura </em>and <em>Palmaria palmata</em> were identified and characterized using genomic sequences of Double-Digest Restriction site Associated DNA (ddRAD). A total of 64,623,186 reads were generated from two runs of multiplexed Illumina Miseq sequencing for which 30,636 reads containing microsatellites and 15,443 microsatellite loci with primers pairs were found. Five hundred seventy-six primers pairs were selected for amplification trials and levels of polymorphism. From the 338 that gave a positive amplification, 142 primers pairs were polymorphic. For genetic analyses two or three populations per species from 13 different geographic locations were used. A total of 28 usable polymorphic markers for <em>A. esculenta</em>, 18 for <em>P. littoralis</em>, 11 for <em>C. jubata</em>, 14 for <em>G. gracilis</em>, 21 for <em>G. dura </em>and 13 for <em>P. palmata </em>were developed. The overall number of alleles per locus ranged from 2 to 22. These 105 new microsatellite markers will be useful for further studies of population genetics, breeding programs and conservation genetics of these species. Compared with traditional approaches, our study yielded thousands of microsatellite loci in a short tim</span><span>e with affordable costs in six different species. This study based on ddRAD-sequencing for the development of microsatellite markers provides preliminary data u</span><span>sing a few individuals from two distinct populations on the genetic structure and reproduction mode of a non-model species as shown </span>with the detection of clonality for the two red algae, <em>C. jubata </em>and <em>G. dura</em> and the detection of highly genetically divergent populations corresponding probably to different cryptic species under the name of<em> P. littoralis</em>.</p>
MIMOSA: A resource consisting of improved methylome imputation models increases power to identify CpG site-phenotype associations
<p>MIMOSA DNA methylation prediction models, set up for MWAS. To run MWAS with this resource, see the tutorial here: <a href="https://github.com/ChongWuLab/MIMOSA">https://github.com/ChongWuLab/MIMOSA</a></p>
Data from: "Transcriptome resources for two non-model freshwater crustacean species" in Genomic Resources Notes accepted 1 October 2014 to 30 November 2014
Open the record for dataset details and reuse information.
Human review for post-training improvement of low-resource language performance in large language models
Open the record for dataset details and reuse information.
Effects of enhanced productivity of resources shared by predators in a food-web module: Comparing results of a field experiment to predictions of mathematical models of intra-guild predation
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.