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.
10
datasets available to search
ShareScore release 0.7.1
Dataset results
10 results for “code for america”
Data and code associated with "Evaluating the definition and distribution of spring ephemeral wildflowers in eastern North America"
<p>Data and code associated with a paper by Yancy et al titled "Evaluating the definition and distribution of spring ephemeral wildflowers in eastern North America". Metadata is included in files when possible.</p>
Data and code for: Adaptive evolution of freezing tolerance in oaks is key to their dominance in North America
Open the record for dataset details and reuse information.
Feasibility Study to Actively Disseminate the Latin America and the Caribbean Code Against Cancer in Primary Healthcare Centers
ClinicalTrials.gov study NCT06965608. IPD Sharing: NO. Countries: 1. Publications: 11.
Serological dataset and R code for: Patterns and processes of pathogen exposure in gray wolves across North America
<p>The presence of many pathogens varies in a predictable manner with latitude, with infections decreasing from the equator towards the poles. We investigated the geographic trends of pathogens infecting a widely distributed carnivore: the gray wolf (<i>Canis lupus</i>). We compiled a large serological dataset of nearly 2000 wolves from 17 study areas, spanning 80º longitude and 50º latitude. Generalized linear mixed models were constructed to predict the probability of seropositivity of four important viruses: canine adenovirus, herpesvirus, parvovirus, and distemper virus – and two parasites: <i>Neospora caninum </i>and <i>Toxoplasma gondii</i>.</p> <p>Canine adenovirus and herpesvirus were the most widely distributed pathogens, whereas <i>N. caninum</i> was relatively uncommon. Canine parvovirus and distemper had high annual variation, with western populations experiencing more frequent outbreaks than eastern populations. Seroprevalence of all infections increased as wolves aged, and denser wolf populations had a greater risk of exposure. Probability of exposure was positively correlated with human density, suggesting that dogs and synanthropic animals may be important pathogen reservoirs. Pathogen exposure did not appear to follow a latitudinal gradient, with the exception of <i>N. caninum</i>. Instead, clustered study areas were more similar: wolves from the Great Lakes region had lower odds of exposure to the viruses, but higher odds of exposure to <i>N. caninum</i> and <i>T. gondii</i>; the opposite was true for wolves from the central Rocky Mountains. Overall, mechanistic predictors were more informative of seroprevalence trends than latitude and longitude. Individual host characteristics as well as inherent features of ecosystems determined pathogen exposure risk on a large scale.</p> <p>Here we provide the serological dataset and the R code used in Brandell et al. 2021. See the README file for a description of the dataset and generalized linear mixed models (GLMM); see Brandell et al. 2021 main text and Supplementary Information for additional information about data collection and cleaning, research permits, and variable descriptions and rationales.</p>
Data and R code from: Fire-induced loss of the world's most biodiverse forests in Latin America
<p>Fire plays a dominant role in deforestation, particularly in the tropics, but the relative extent of transformations and influence of fire frequency on eventual forest loss remain unclear. Here we analyze the frequency of fire and its influence on post-fire forest trajectories between 2001-2018. We account for ~1.1% of Latin American forests burnt in 2002-2003 (8,465,850 ha). Although 40.1% of forests (3,393,250 ha) burned only once, by 2018~48% of the evergreen forests converted to other, primarily grass-dominated uses. While greater fire frequency yielded more transformation, our results reveal the staggering impact of even a single fire. Increasing fire frequency imposes greater risks of irreversible forest loss, transforming forests into ecosystems increasingly vulnerable to disturbance and degradation. Reversing this trend is indispensable to both mitigate and adapt to climate change globally. As climate change transforms fire regimes across the region, key actions are needed to conserve Latin American forests.</p>
Code and Data: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America
<p>Data and code used to obtain results published in Garcia-Garcia et al 2021: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America. Submited to<em> Geosci. Model Dev</em>.</p>
Data and Code for: Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America
<p>This submission contains all the code and data necessary for reproducing 1) the dataset, 2) the main results, and 3) all supplemental analyses appearing in the manuscript titled: <em>Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America</em> (Ramirez-Parada, Park, Record, Davis, Ellison, and Mazer, 2023). A preprint of this manuscript can be accessed at: https://doi.org/10.21203/rs.3.rs-3131821/v1.</p> <p> </p> <p>Extracting the compressed file will generate a folder titled "Project folder", containing sub-folders named "Data" and "R code". In order for the code to work, users need to preserve the folder structure of the code and data, as the R Markdown files in the "R code" folder have relative file paths that read and write data within the "Data" folder. Moving either would require re-writing the filepaths across Rmds for the code to run.</p> <p><br> To replicate the results, the following R Markdowns must be run in sequence (once they have been run, the Rmds for supplemental analyses can be used in any order):</p> <p><br> <em>"1. Subsetting Dataset.Rmd"</em></p> <p>This file processes a specimen dataset of ca. 2.3 million specimens that we assembled for this project (publicly available on Dryad: <a href="https://doi.org/10.25349/D9WP6S">https://doi.org/10.25349/D9WP6S</a>), filtering out duplicates, specimens out of the spatial scope of the PRISM data used for all analyses, and subsetting to only those species represented by a minimum of 300 specimens. This filtering yields a dataset of 1,038,047 specimens in flower across 1,605 species.</p> <p>For an in-depth description of the starting dataset, please refer to the "READ ME.txt" file within the "Project folder", and visit its corresponding Dryad repository (linked above).</p> <p><br> <em>"2. Main Analysis - Estimating S_space, S_time, and S_diff.Rmd"</em></p> <p>This file uses the subset dataset produced by the previous Rmd to fit the varying-intercepts, varying-slopes model that produced the estimates of apparent plasticity and apparent adaptation underlying all main analyses. This Rmd exports a dataset of species-specific estimates of S<sub>space</sub>, S<sub>time</sub>, and S<sub>space</sub> - S<sub>time</sub> that is used to recreate Figures 2, 3, and 4 of the main text in the next step. This is the most time consuming R Markdown file to run, as each MCMC chain used to fit the model in Stan must be run on a dedicated processor (limiting the usefulness of parallel computation). Fitting the model using 3 MCMC chains, 1000 iterations for warmup, and 4000 iterations for sampling, took approximately 24 hours using an Intel(R) Core(TM) i7-9750H CPU @ 2.60GHz processor. </p> <p> </p> <p><em>"3. Main Analysis - Figures 2, 3, and 4.Rmd"</em></p> <p>Finally, this Rmd uses the dataset of species-specific estimates to conduct all analyses underlying Figures 2, 3, and 4, recreating each of these figures.</p> <p><strong><em>For detailed descriptions of all materials (code and data) and instructions for using them, please refer to the "READ ME.txt" file within "Project folder". </em></strong></p> <p> </p>
Serological dataset and R code for: Patterns and processes of pathogen exposure in gray wolves across North America
Open the record for dataset details and reuse information.
Data and R code from: Fire-induced loss of the world’s most biodiverse forests in Latin America
Open the record for dataset details and reuse information.
Codes and Dataset for "Application of Low-Cost Fine Particulate Mass Monitors to Convert Satellite Aerosol Optical Depth to Surface Concentrations in North America and Africa"
<p>This file contains the codes and dataset pertaining to the manuscript "Application of Low-Cost Fine Particulate Mass Monitors to Convert Satellite Aerosol Optical Depth to Surface Concentrations in North America and Africa"</p>
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.