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.
207
datasets available to search
ShareScore release 0.9.0
Dataset results
207 results for “Latin America”
Raw data for Infrastructure and Awareness Landscape Analysis in Latin America
<p>Persistent Identifiers (PIDs), such as Digital Object Identifiers (DOIs), are foundational to connecting and enhancing the visibility of Latin American research within a global framework. Although the region is rich in diverse and impactful research, many repositories remain only partially integrated into international registries and aggregators, limiting their discoverability and reach. The adoption of PIDs across repositories in Latin America varies widely, underscoring the need for increased awareness about the role of open PIDs in advancing research accessibility and visibility.</p> <p>This dataset offers a comprehensive overview of the current landscape of repositories, publishing systems, and Open Science policies across Latin America, shedding light on the institutional and national efforts that support an open and inclusive research infrastructure. It highlights the importance of collaboration among researchers, institutions, funders, librarians, and government agencies in fostering Open Science practices and encouraging strategic PID adoption. By expanding these open practices and strengthening PID adoption, Latin American research can achieve greater integration and impact within the global research ecosystem.</p> <p>You can read the full report titled "Infrastructure and Awareness Landscape Analysis in Latin America" at <a href="https://doi.org/10.5281/zenodo.14010858" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.14010858</a> </p>
Accompanying dataset; 'Agroforestry enhances biological activity, diversity and soil-based ecosystem functions in mountain agroecosystems of Latin America: A meta-analysis.'
<p>The database created as part of the meta-analysis is designed to facilitate the comparison of biological activity, diversity (BIAD), and ecosystem functions (EFs) between agroforestry systems (AFS) and other land-use types. It incorporates data extracted from selected studies, each record comprising a mean value, sample size, and a variance measure to compute standard deviation. The database also categorizes data according to 22 explanatory variables, including geographical coordinates, climate classification, soil type, AFS classification, and more, to characterize the sites and management systems involved. This detailed classification enables a nuanced analysis of how different factors might influence the BIAD and EFs in the context of AFS. The database supports the meta-analysis by allowing for the estimation of effect sizes using response ratios, which compare the relative difference in BIAD and EFs between AFS and other land uses. Data extraction from primary studies was meticulous, employing both direct and indirect methods such as graph digitizing software, and missing data were supplemented using reliable sources or direct communication with the original study authors. The comprehensive nature of this database ensures that the analysis can account for a wide range of variables that may affect the outcomes of interest in the meta-analysis. </p><p>For an in-depth exploration of the study's findings and methodology, refer to the comprehensive meta-analysis available in Global Change Biology (2024), entitled "<i>Agroforestry Enhances Biological Activity, Diversity, and Soil-Based Ecosystem Functions in Mountain Agroecosystems of Latin America: A Meta-Analysis</i>."</p>
Revised database of the Soil Information System of Latin America and the Caribbean, SISLAC
<p>This dataset contains the revised version of the SISLAC database in three formats: comma-separated values (.csv), microsoft access (.mdb) and PostGIS database (.backup). This database was reviewed and the inconsistencies found in the profiles and in the description of their horizons were corrected. Consists of two tables, one for the description of the profiles and the other with the description of the horizons and their properties. The key field between both tables is the profile identifier, column <strong><em>profile_id</em></strong>.</p>
Dataset for "Authorship concentration in health sciences journals from Latin America and the Caribbean"
<p>Authorship concentration indexes and other data for journals in the LILACS (Latin American and the Caribbean Literature on Health Sciences) bibliographic database, from 2015 to 2019 (FONTENELLE, 2022). These data are read and created by <a href="https://doi.org/10.5281/zenodo.6127497">analytic code in Zenodo</a>.</p> <ul> <li><em>authorship_concentration.csv</em> - dataset derived in Fontenelle (2022) from raw data exported from LILACS. This is the main file, and it's CC-BY because other researchers might have curated the raw data differently and thus derived different data. CSV file encoded with ASCII.</li> <li><em>authorship_concentration_datadictionary.csv</em> - data dictionary for the previous file. This file is actually CC0. CSV file encoded with ASCII.</li> <li><em>journals.csv</em> - dataset about the journals indexed in LILACS between 2015 and 2019. As a result of simply converting and filtering the original TITLE database, this is actually CC0 by the Pan American Health Organization (PAHO). CSV file encoded with UTF-8.</li> <li><em>journal_subjects.csv</em> - DeCS descriptors for the journals identified by the ISSN. CC0 by the Pan American Health Organization (PAHO), as above. CS file encoded with ASCII.</li> </ul>
European Investment Bank Projects in ACP, OCT, Africa, Asia, and Latin America (1957-2024)
<p>This dataset offers a comprehensive analysis of European Investment Bank (EIB) projects in Africa, the Caribbean, and the Pacific (ACP) regions, Overseas Countries and Territories (OCT), Asia, and Latin America, spanning from 1975 to 2023. The dataset includes information on 2,558 projects; each entry in the dataset includes key project details such as the project’s sector, date of signature, and financial commitments. All numbers are in 2015 euros.</p>
Revised database of the Soil Information System of Latin America and the Caribbean, SISLAC version 1.2
<p>The SISLAC_database version 1.2 contains the revised version of the SISLAC database in comma-separated values (csv) format. This database was reviewed and the inconsistencies found in the profiles and in the description of their horizons were corrected. The key field between both tables is the profile identifier, column <strong><em>profile_id</em></strong>.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1951
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1951.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1950
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1950.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximun, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1959
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1959.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1956
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1956.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1957
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1957.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1958
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1958.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1955
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1955.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1960
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1960.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1954
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1954.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1952
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1952.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1953
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1953.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1973
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1973.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1974
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1974.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</p>
ERA5-Land selected indicators daily aggregates for the Latin America region, 1972
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land eight selected indicators, covering the Latin America region, for 1972.</p><p>Each file represents one indicator aggregation for one month of the year. Inside each NetCDF file, the layers contain the daily aggregates.</p><p>For 2m dewpoint pressure, 10m u component of wind, 10m v component of wind, surface pressure, the mean function was used for aggregation. For total precipitation, the sum function was used for aggregation. For 2m temperature, the functions maximum, mean and minimum were used for aggregation.</p><p>Those files were created using the <a href="https://github.com/ErikKusch/KrigR">KrigR</a> package.</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.