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.
11,982
datasets available to search
ShareScore release 0.7.1
Dataset results
11,982 results for “africa”
ERA5-Land selected indicators daily aggregates for Africa, 1950
<p>This deposit contains NetCDF files with daily aggregates from Copernicus Era5-Land for eight selected indicators, covering Africa 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 maximum, mean, and minimum were used for aggregation.</p>
Raw data for Infrastructure and Awareness Landscape Analysis in sub-Saharan Africa
<p>Persistent identifiers that are well-connected are essential for enhancing research, researchers, and research institutions. The comprehensive raw data shared on PIDs infrastructure and awareness landscape analysis in sub-Saharan Africa is taken from service providers and organizations, including Open DOAR, the Registry of Open Access Repositories (ROAR), the Registry of Research Data Repositories (Re3data), UNESCO, Lyrasis (Dspace), Dataverse, Open Journal System (OJS), among others. The data shared here was collected in August 2023. The data shared are secondary data, and the position is strictly based on the primary source data author. The data is restricted to what is available on the internet and does not include locally hosted offline data.</p> <p>Further analysis of the raw data suggested some salient implications for PIDs awareness in the region. Variations were observed across the various data sources, while some interesting correlations emerged from the collected data. There are countries with some PIDs infrastructure, while others are yet to establish a visible presence in PIDs infrastructure. The visibility of PIDs is somewhat related to the awareness level as well as the policy established on open access in the represented countries across the region.</p>
Field data for: Enterovirus sequence data obtained from primate samples in Central Africa suggest a high prevalence of enteroviruses with possible zoonotic potential
<p>Enteroviruses infect humans and animals, can cause disease, and some may be transmitted across species barriers. We collected different types of samples from various species of Central African wildlife, including data on sampling location and tested the samples for the presence of Enterovirus RNA using a family level PCR. Specimen collection was approved by an Institutional Animal Care and Use Committee (IACUC) of the University of California Davis, and the Governments of Cameroon and the Democratic Republic of the Congo. Enterovirus RNA was detected in samples from 17 primates and 2 rodents. Some sequences were very similar while others were dissimilar to known species, highlighting the unexplored enterovirus diversity in wildlife.</p> <p>The samples and filed data were collected by field ecologists as part of the USAID funded PREDICT project (https://ohi.vetmed.ucdavis.edu/programs-projects/predict-project) and screened for enterovirus RNA using consensus PCR. Maps were generated using basic maps from Paintmaps (http://www.paintmaps.com), a free tool for educational and academic use. The dataset contains the metadata on enterovirus screening among wildlife in Cameroon and the Democratic Republic of the Congo from 2003-2014 as part of the USAID funded PREDICT project. Please refer to the article for more information on methods and references.</p>
The immature Homo naledi ilium from the Lesedi Chamber, Rising Star Cave, South Africa
<p>To use any of these data, please cite: Cofran Z, VanSickle C, Valenzuela R, García-Martínez D, Walker CS, Hawks J, Zipfel B, Williams SA, & Berger LR. 2022. The immature <em>Homo naledi</em> ilium from the Lesedi Chamber, Rising Star Cave, South Africa. American Journal of Biological Anthropology 179:3–17. (https://onlinelibrary.wiley.com/doi/full/10.1002/ajpa.24522)</p> <p>Lesedi Ilium Landmark Dataset_R1.csv = A comma separated values (.csv) format file containing 148 3D landmarks describing shape of the right ilium, for 23 immature humans, <em>Australopithecus</em> fossils MLD 7 and MLD 25, and two reconstructions of the <em>Homo naledi</em> fossil U.W. 102a-138. The first naledi reconstruction utilizes a reference template based on MLD 7 and MLD 25, and the second reconstruction is based on the average of the human ilia. The .csv file contains columns for individual ID, landmark name, and the x-, y-, and z-coordinates of the landmark, and each row is a unique landmark coordinate.</p> <p>Lesedi_Ilium_Height_Data.csv = A comma separated values (.csv) format file containing developmental stage and iliac height (in mm) for 43 humans, U.W. 102a-138, and three <em>Australopithecus</em> fossils (MLD 7, MLD 25, and the left and right sides of Sts 14).</p> <p>A 3D mesh of the U.W. 102a-138 ilium is available on Morphosource: https://www.morphosource.org/concern/media/000383216?locale=en</p>
Data for One Health and Veterinary Systems in Africa
<p>One Health Database Africa<br> The “One Health and Veterinary Systems in Africa: Taking stock of current coverage, needs, and opportunities to meet present and changing threats and optimize collaboration” is reviewing current capacity and programmatic status, gaps, and operations in each country and by sub-regions of Africa.</p> <p>This datasets combines multiple sources to produce a single One Health database containing selected indicators. The database encompasses 54 countries across the continent of Africa (according the UN).</p>
A Lagrangian analysis of the sources of rainfall over the Horn of Africa Drylands
<p>This repository contains datasets required to reproduce the figures in the paper titled "A Lagrangian analysis of the sources of rainfall over the Horn of Africa Drylands"</p> <p>The relevant codes for generating the figures can be found in the following repository: https://github.com/akashkoppa/HAD-Moisture-Source</p>
Coronavirus disease (COVID-19) case data - South Africa
<p>COVID 19 Data for South Africa created, maintained and hosted by <a href="https://dsfsi.github.io/">DSFSI research group</a> at the University of Pretoria</p> <p><strong>Disclaimer:</strong> We have worked to keep the data as accurate as possible. We collate the COVID 19 reporting data from NICD and South Africa DoH. We only update that data once there is an official report or statement. For the other data, we work to keep the data as accurate as possible. If you find errors let us know. </p> <p>See original GitHub repo for detailed information <a href="https://github.com/dsfsi/covid19za">https://github.com/dsfsi/covid19za</a></p>
Hydrogen peroxide in the upper tropical troposphere over the Atlantic Ocean and western Africa during the CAFE-Africa aircraft campaign
<p>We provide here the supporting dataset for our study on airborne measurements of oh hydrogen peroxide in the upper tropical troposphere over the Atlantic Ocean and western Africa during the CAFE-Africa aircraft campaign in 2018.</p> <p> </p>
Geographic Scope of Randomized Clinical Trials from Africa
<p><strong>Overview</strong></p> <p>This map reports the geographic scope of randomized controlled trials (RCTs) conducted in Africa, as found in PubMed. The map highlights a discrepancy between actual trial location and how trials are reported: although reports of research from Africa are often labeled as being "African" in scope, RCTs are rarely continent-wide and many countries are not represented in even a single study. The intent of the map is to visualize actual trial locations, hopefully leading to a more accurate portrayal of RCT study sites on the African continent.</p> <p><strong>Data Source and Tools</strong></p> <p>Data for the map was extracted from PubMed and the map was created in ArcGIS Online.</p> <p><strong>Audience</strong></p> <p>The map was created for an original research poster at the 2022 International Congress on Peer Review and Scientific Publication (see "Attribution" below). Its audience is researchers, clinicians, policy makers, librarians, scholarly communications stakeholders, and editors in chief interested in improving the accuracy of the reported scope of research in Africa to better inform health care research, policy, and resource distribution.</p> <p><strong>Design</strong></p> <p>A PubMed search using Medical Subject Headings and keywords representing Africa, African, and RCTs was run to identify citations published between 1968 and February 2022. The citation titles and abstracts were screened against established inclusion/exclusion criteria, with included studies continuing through a full text review and data extraction process. Total RCT representation per country was then mapped in ArcGIS with higher RCT counts represented by darker shading. The map highlights the variance in RCT representation across the continent, with some countries represented in up to 80 RCTs and many countries represented in none.</p> <p><strong>Attribution</strong></p> <p>Folafoluwa Olutobi Odetola and Marisa L. Conte conceived the research question, crafted the PubMed search, and analyzed the citation data; Tyler Nix created the map. Special thanks to Caroline Kayko (University of Michigan) for her input in the creation of the map. </p> <p>See the original research poster at:</p> <p>Odetola, FO; Conte, ML. Geographical Scope of Randomized Clinical Trials from Africa. [Poster]. 9th International Congress on Peer Review and Scientific Publication, September 8-10, 2022, Chicago, IL. Available from: <a href="https://peerreviewcongress.org/abstract/geographical-scope-of-randomized-clinical-trials-from-africa/">https://peerreviewcongress.org/abstract/geographical-scope-of-randomized-clinical-trials-from-africa/</a></p> <p>The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p>
SI2: How circular is an extractive economy? South Africa's export orientation results in low circularity and insufficient societal stocks for service-provisioning
<p>Supporting information SI2 for the manuscript under review:</p> <p>How circular is an extractive economy? South Africa’s export orientation results in low circularity and insufficient societal stocks for service-provisioning </p> <p> </p> <p>It provides the data used and the basic mass balanced calculation for a circularity assessment.</p>
eHealth solutions in Africa
<p>Information about eHealth solutions and in African countries, mainly from the countries participating in the BETTEReHEALTH project (Ghana, Malawi, Ethiopia, Tunisia). From the BETTEReHEALTH registry: <a href="https://registry.betterehealth.eu/ehealth-solution">https://registry.betterehealth.eu/ehealth-solution</a></p>
Estimation of biomass combustion carbon emissions data for 2018 in Africa based on GABAM burned area products.
<p>Estimated biomass combustion carbon emissions data for the African region in 2018, based on the GABAM 30m burned area product.The product is geographically (latitude/longitude) projected with a resolution of 0.00025° (approximately 30 meters) using the WGS84 horizontal datum and the EGM96 vertical datum, and consists of 10° x 10° tiles covering the entire African region.</p>
Estimation of biomass combustion carbon emissions data for 2020 in Africa based on GABAM burned area products.
<p>Estimated biomass combustion carbon emissions data for the African region in 2020, based on the GABAM 30m burned area product.The product is geographically (latitude/longitude) projected with a resolution of 0.00025° (approximately 30 meters) using the WGS84 horizontal datum and the EGM96 vertical datum, and consists of 10° x 10° tiles covering the entire African region.</p>
Estimation of biomass combustion carbon emissions data for 2019 in Africa based on GABAM burned area products.
<p>Estimated biomass combustion carbon emissions data for the African region in 2019, based on the GABAM 30m burned area product.The product is geographically (latitude/longitude) projected with a resolution of 0.00025° (approximately 30 meters) using the WGS84 horizontal datum and the EGM96 vertical datum, and consists of 10° x 10° tiles covering the entire African region.</p>
Mechanisms influencing physically sequestered soil carbon in temperate restored grasslands in South Africa and North America
This dataset contains a measurement of physically protected carbon (microaggregate-within-macroaggregate C) and potential drivers of physically protected C accumulation during grassland restoration. The data were collected from three independent grassland restorations from agriculture in North America and South Africa. Northeast Kansas, USA data were collected in May 2013. Northeast Free State, RSA data were collected in September–November 2005. Southeast Nebraska, USA data were collected in October 2008–May 2008. Aggregate fractionations were performed by hierarchical wet sieving (Six et al 2000). Carbon and N quantification were done by flash combustion-gas chromatography. Microbial biomass C quantification was performed with chloroform fumigation-incubation (chloroform fumigation-extraction in the case of northeast Kansas). Phospholipid fatty acid biomass analysis was conducted using the methods of Bligh and Dyer (1959).
Tatocnemis malgassica. a. Insect, natural size. b in Descriptions of new Genera and Species of Odonata in the Collection of the British Museum, chiefly from Africa.
Tatocnemis malgassica. a. Insect, natural size. b. Extremity of abdomen, showing appendages, magnified 7 ½ times.
Dataset: Knowledge, information needs and behavior regarding HIV and sexually transmitted infections among migrants from sub-Saharan Africa living in Germany: Results of a participatory health research survey.
<p>Dataset for: Koschollek C, Kuehne A, Müllerschön J, Amoah S, Batemona-Abeke H, Dela Bursi T, Mayamba P, Thorlie A, Mputu Tshibadi C, Wangare Greiner V, Bremer V, Santos-Hövener C: Knowledge, information needs and behavior regarding HIV and sexually transmitted infections among migrants from sub-Saharan Africa living in Germany: Results of a participatory health research survey.</p> <p>This dataset has been described in a PLoS One paper and contains all data necessary to replicate the results presented within this paper (10.1371/journal.pone.0227178). Please cite both the paper as well as the DOI of this dataset if you make use of the data.</p>
Map of 15 Ecoclimatic Arid and Semi-Arid zones in Africa (6°S-39°N)
<p>Ecoclimatic Arid and Semi-Arid zones in Africa (6°S-39°N) based were derived from a multiway analysis of the WorldClim database (1950-2000). See details in the paper:<em> Leibovici DG,<strong> </strong>Quillevere G and Desconnets J-C (2007) A method to Classify Ecoclimatic Arid and Semi-Arid Zones in Circum-Saharan Africa Using Dynamics of Multiple Indicators. <strong>IEEE Transaction in Geoscience And Remote Sensing, 45(12), 4000-4007. </strong></em>doi:<a href="https://doi.org/10.1109/TGRS.2007.908878">10.1109/TGRS.2007.908878</a></p> <p>A follow up paper is part of the zip archive for multiscale consideration (Leibovici, D. G., & Jackson, M. (2011). Multi-scale integration for spatio-temporal ecoregioning delineation. <strong><em>International Journal of Image and Data Fusion</em>, <em>2</em>(2), 105-119</strong>. doi:<a href="https://doi.org/10.1080/19479832.2010.542893">10.1080/19479832.2010.542893</a>)</p>
The MedAfriCarbon radiocarbon database and web application. Archaeological dynamics in Mediterranean Africa, ca. 9600-700 BC
<p>MedAfriCarbon radiocarbon database and web app are outcomes of the <em>MedAfrica Project —Archaeological deep history and dynamics of Mediterranean Africa, ca. 9600-700 BC</em>. The dataset presented here includes a collection of <strong>1584</strong> calibrated archaeological 14C dates from <strong>1587</strong> samples collected from <strong>368</strong> sites located in Mediterranean Africa (plus some additional dates whose published information is incomplete). The majority of the dates are linked to cultural and environmental variables, notably the presence/absence of different domestic/wild species and specific material culture.</p> <ul> <li><strong>1.0.3</strong> _27 Feb 2020_– Official public JOAD release (includes JOAD DOI and volume numbers). Includes a few minor error corrections.</li> <li><strong>1.0</strong> _30 Jan 2020_— First public release of the dataset on Zenodo.</li> </ul>
Text-figure 3. Mormotomyia hirsuta Austen, d. Distal extromity of abdomen: lateral view, showing hypopygium. (:reatly riilargetl. in A Remarkable Semi-Apterous Fly (Diptera) found in a Cave in East Africa, and representing a new Family, Genus, and Species.
Text-figure 3. Mormotomyia hirsuta Austen, d. Distal extromity of abdomen: lateral view, showing hypopygium. (:reatly riilargetl.
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.