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.
1,361
datasets available to search
ShareScore release 0.7.1
Dataset results
1,361 results for “Congo”
Resilience estimates of Amazon and Congo rainforests based on mean annual precipitation and root zone storage capacity
<p>Resilience refers to the capacity of the ecosystem to absorb perturbations and remain in its native stable state. Here, we quantified forest resilience of South American and African ecosystems using mean annual precipitation and root zone storage capacity (2000-2019). We adopted Hirota et al. (2011) methodology for calculating resilience using logistic regression. This logistic regression predicts the probability of forest (tree cover > 50%) as a function of the independent variable. The predicted resilience estimates range between 0 to 1, where 1 represents the highest probability of finding forest – interpreted as highly resilient forest ecosystems.</p> <p>For more information, check: <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16115">https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.16115</a></p>
Modelled gridded population estimates for the Kasaï-Oriental Province in the Democratic Republic of Congo (2024) version 4.2
<h2><strong>Content</strong></h2> <p>This repository contains the input data and scripts used to create the modeled gridded population estimates for Kasaï-Oriental Province in the Democratic Republic of Congo. It also includes the grid-cell posterior distributions and scripts to aggregate them within user-defined geographic boundaries.</p> <p> In particular, this repository contains two compressed files (.zip):</p> <p><strong>1. <code>population_estimates.zip</code></strong></p> <ul> <li>Includes raster files (<code>.tif</code>) with summaries of population count posterior predictions at the grid-cell level, specifically the mean, median, lower credible interval, and upper credible interval.</li> <li>Includes spatial files (<code>.gpkg</code>) with summaries of population count posterior predictions at the health-area and health-zone levels, specifically the mean, median, lower credible interval, and upper credible interval.</li> </ul> <p><strong>2. <code>population_model.zip</code></strong></p> <p>This directory comprises five subdirectories with scripts, input data, and output data necessary to replicate the population model:</p> <ul> <li><code><strong>01_model_stan</strong></code>: Contains the Stan model, input data, and an R script (<code>01_model_stan.R</code>) with a function to run the model.</li> <li><code><strong>02_model_run</strong></code>: Includes an R script (<code>02_model_run.R</code>) for running the model, along with output data.</li> <li><code><strong>03_model_evaluate</strong></code>: Features a Quarto report template (<code>03_model_evaluate.qmd</code>) and model evaluation summary files(.pdf).</li> <li><code><strong>04_predict_posterior</strong></code>: Provides R scripts (<code>04_predict_posterior.R</code> and <code>04_predict_run.R</code>) for generating predictions, along with input and output data, namely the posterior predictions files (.rds).</li> <li><code><strong>05_aggregate_posterior</strong></code>: Contains R scripts (<code>05_aggregate_posterior.R</code> and <code>05_aggregate_run.R</code>) and associated input and output data, namely the population count posterior summaries as presented in the file <code>population_estimates.zip</code> .</li> </ul> <p>The work was carried out in <code>R</code> (version 4.4.0), with the packages <code>tidyverse</code> (version 2.0.0), <code>terra</code> (version 1.7-78), <code>sf</code> (version 1.0-16), <code>furrr</code> (version 0.3.1), <code>doParallel</code> (version 1.0.17), <code>foreach</code> (version 1.5.2), <code>rstudioapi</code> (version 0.16.0), and <code>rstan</code> (version 2.32.6), on macOS Sequoia (version 15.1.1). While the scripts are designed to be portable, minor adjustments may be required for compatibility with other operating systems.</p> <h2><strong>Important</strong></h2> <p>This version includes changes in the STAN model <code>10h_survey_survey_covariate_building_random_effect_hierarchy_building_covariate_density_fixed_effect_hierarchy_density.stan</code>. Consequentely, all the files generated in the previous versions are now changed.</p> <p> </p> <p>For inquiries regarding the model and the data, please contact Gianluca Boo at gianluca.boo@soton.ac.uk.</p>
data-base of CO2, CH4, N2O and ancillary data in the Congo River
<p>data-base of CO2, CH4, N2O and ancillary data in the Congo River relative to paper "Variations of dissolved greenhouse gases (CO2, CH4, N2O) in the Congo River network overwhelmingly driven by fluvial-wetland connectivity" by Borges et al. (https://doi.org/10.5194/bg-2019-68)</p>
Annual tropical forest loss during 2001-2021 in the Congo Basin
<p>The loaded dataset in Zenodo includes the following parts:</p> <p>(1) Shp file of the Congo Basin;</p> <p>(2) GeoTIFF image of the evergreen forest cover map in the Congo Basin (file name 'Congo_EvergreenForest2000_TCC70_Height5_Clip');</p> <p>(3) GeoTIFF image of the annual forest loss map produced by us (file name 'Congo_log2001_2021_L78S2_w300_cb300_theta0p2_clean120_5_new');</p> <p>(4) GeoTIFF image of the post-forest loss recovery index map produced by us (file name 'Congo_RI_Log2001_2021_L78S2_w300_cb300_400_theta0p2_clean120_5_new.tif'), and it is noted that the industrial plantation map (file name 'JRC_TMF_plantations_2022.tif') should be used to exclude any plantations in our post-forest loss recovery index map, as industrial plantations is not regarded as forest recovery.</p>
Nominal list of bats of the Congo, Rwanda and Burundi (CRB) region in The bats of the Congo and of Rwanda and Burundi revisited (Mammalia: Chiroptera)
<p><i>Nominal list of bats of the Congo, Rwanda and Burundi (CRB) region</i></p><table><thead><tr><th><b>Hayman</b> <i>et al.</i> (1966)</th><th>Present study</th></tr></thead><tbody><tr><th>MEGACHIROPTERA Pteropidae</th><td>PTEROPODIFORMI Pteropodidae Eidolinae</td></tr><tr><th><i>Eidolon helvum</i> (Kerr, 1792)</th><td><i>Eidolon helvum</i> (Kerr, 1792)</td></tr><tr><th colspan="2"><b>Rousettinae</b> <b>Epomophorini</b></th></tr><tr><th colspan="2"><i>Epomophorus anselli</i> Bergmans & Van Strien, 2004</th></tr><tr><th><i>Epomophorus crypturus</i> Peters, 1852 <i>Epomophorus gambianus</i> (Ogilby, 1835)</th><td><i>Epomophorus crypturus</i> Peters, 1852</td></tr><tr><th><i>Epomophorus anurus</i> Heuglin, 1864 <i>Epomophorus labiatus minor</i> (Dobson, 1880)</th><td><i>Epomophorus labiatus</i> (Temminck, 1837)</td></tr><tr><th colspan="2"><i>Epomophorus minimus</i> Claessen & De Vree, 1991</th></tr><tr><th><i>Epomophorus labiatus minor</i> (Dobson, 1880)</th><td><i>Epomophorus minor</i> Dobson, 1880</td></tr><tr><th><i>Epomophorus wahlbergi haldemani</i> (Halowell, 1846)</th><td><i>Epomophorus wahlbergi</i> (Sundevall, 1846)</td></tr><tr><th><i>Epomops dobsoni</i> (Bocage, 1889)</th><td><i>Epomops dobsonii</i> (Bocage, 1889)</td></tr><tr><th><i>Epomops franqueti franqueti</i> (Tomes, 1860)</th><td><i>Epomops franqueti</i> (Tomes, 1860)</td></tr><tr><th><i>Hypsignathus monstrosus</i> H. Allen, 1861</th><td><i>Hypsignathus monstrosus</i> H. Allen, 1862</td></tr><tr><th><i>Micropteropus intermedius</i> Hayman, 1963</th><td><i>Micropteropus intermedius</i> Hayman, 1963</td></tr><tr><th><i>Micropteropus pusillus</i> (Peters, 1867)</th><td><i>Micropteropus pusillus</i> (Peters, 1868)</td></tr><tr><th colspan="2"><i>Nanonycteris veldkampii</i> (Jentink, 1888)</th></tr><tr><th colspan="2"><b>Myonycterini</b></th></tr><tr><th><i>Megaloglossus woermanni</i> Pagenstecher, 1885 <i>Megaloglossus woermanni prigoginei</i> Hayman, 1966</th><td><i>Megaloglossus woermanni</i> Pagenstecher, 1885</td></tr><tr><th><i>Rousettus (Lissonycteris) angolensis</i> (Bocage, 1898)</th><td><i>Myonycteris angolensis</i> (Bocage, 1898)</td></tr><tr><th></th><td><i>Myonycteris relicta</i> Bergmans, 1980</td></tr><tr><th><i>Myonycteris wroughtoni</i> Andersen, 1908</th><td><i>Myonycteris torquata</i> (Dobson, 1878)</td></tr><tr><th></th><td><b>Plerotini</b></td></tr><tr><th><i>Plerotes anchietae</i> (Seabra, 1900)</th><td><i>Plerotes anchietae</i> (Seabra, 1900)</td></tr><tr><th></th><td><b>Rousettini</b></td></tr><tr><th><i>Rousettus aegyptiacus leachi</i> (Smith, 1823)</th><td><i>Rousettus aegyptiacus</i> (E. Geoffroy St.-Hilaire, 1810)</td></tr><tr><th></th><td><b>Scotonycterini</b></td></tr><tr><th><i>Casinycteris argynnis</i> Thomas, 1910</th><td><i>Casinycteris argynnis</i> Thomas, 1910</td></tr><tr><th><i>Scotonycteris zenkeri</i> Matschie, 1894</th><td><i>Scotonycteris bergmansi</i> Hassanin <i>et al.</i>, 2015</td></tr><tr><th></th><td><b>Stenonycterini</b></td></tr><tr><th><i>Rousettus (Stenonycteris) lanosus</i> Thomas, 1906</th><td><i>Stenonycteris lanosus</i> Thomas, 1906</td></tr><tr><th><b>MICROCHIROPTERA Hipposideridae</b></th><td><b>Hipposideridae</b></td></tr><tr><th></th><td><i>Asellia tridens</i> (E. Geoffroy St.-Hilaire, 1813)</td></tr><tr><th><i>Hipposideros cyclops</i> (Temminck, 1853)</th><td><i>Doryrhina cyclops</i> (Temminck, 1853)</td></tr></tbody></table>
Supplementary dataset to publication: Approaching the complexity of Crimean-Congo hemorrhagic fever virus serology: a study in swine
<p>For the detection of anti-CCHFV antibodies in swine, we established a swine-specific in-house ELISA, indirect immunofluorescence assay and a virus neutralization test. Uploaded data contains sample performance in each test. Samples used in this study include swine serum samples from Germany and Spain.</p>
National Checklists 2017: Republic of the Congo
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from the Republic of the Congo collected using effechecka and geonames polygons
National Checklists 2017: Democratic Republic of the Congo Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from the Democratic Republic of the Congo collected using effechecka and geonames polygons
National Checklists 2019: Republic of the Congo
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from the Republic of the Congo collected using effechecka and geonames polygons
National Checklists 2019: Democratic Republic of the Congo Species List
Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from the Democratic Republic of the Congo collected using effechecka and geonames polygons
Short-term trends in great ape density in a community-based conservation area in the eastern Democratic Republic of the Congo
<p>Provided are the following supporting data and R script for "Short-term trends in great ape density in a community-based conservation area in the eastern Democratic Republic of the Congo":</p> <ol> <li>A dataset with summarized transect-based ape sign data, <br>SupportingInformation_ApeSigns.xlsx, with coordinates made approximate.</li> <li>A randomized dataset, <br>RandomizedData_INLA.csv, derived from the original, used as INLA-modeling input. </li> <li>A reproducible R script as used to generate the INLA models: SSupporting_Information_exampleINLA_Rscript_new.doc</li> </ol>
Data for Publication - Synergies and Trade-offs between Robusta Yield, Carbon Stocks and Biodiversity across Coffee Systems in the DR Congo
<p>Data used for the publication:</p> <p>"Synergies and Trade-offs between Robusta Yield, Carbon Stocks and Biodiversity across Coffee Systems in the DR Congo" - Ieben Broeckhoven, Jonas Depecker, Trésor Kasereka Muliwambene, Olivier Honnay, Roel Merckx and Bruno Verbist</p>
Kam-Niger-Congo comparative word list
<p>This is a comparative word list containing data collected with the Leipzig-Jakarta word list, intended to compare basic vocabulary between Kam and other Niger-Congo languages. It contains reconstructions for a variety of proto-languages already available in the literature (e.g. Jukunoid, Mumuyic, Proto-Bantu, Proto-Gbe, Proto-Potou-Akanic, and Proto-Fula-Sereer), as well as the author's own quasi-reconstructions for Niger-Congo, Benue-Congo, and Delta-Cross and cognate judgements.</p>
Dataset: Health worker compliance with severe malaria treatment guidelines in the context of implementing pre-referral rectal artesunate in the Democratic Republic of the Congo, Nigeria and Uganda: an operational study
<p>Dataset underlying the publication "<strong>Health worker compliance with severe malaria treatment guidelines in the context of implementing pre-referral rectal artesunate in the Democratic Republic of the Congo, Nigeria and Uganda: an operational study</strong>" (Plos Medicine)</p> <p>Data originating from the Community Access to Rectal Artesunate for Malaria (CARAMAL) Project, 2018-2021.</p> <p>Analysis of health workers' compliance with the treatment guidelines for severe malaria in the context of rolling out pre-referral rectal artesunate (RAS) in the Democratic Republic of the Congo, Nigeria and Uganda. Details provided in the publication.</p>
Fig. 3 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)
Fig. 3. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. External view. A–B. Detail of the girdle showing a part of a girdle with ligula (arrow) and the neighbouring interrupted band. C. Detail of the valve mantle with the draped silica spines (arrow) and the silica plaques (arrow) near the edge of the mantle and the valvocopula. D. Detail of the girdle band near the pole. Scale bars = 2 µm.
Fig. 1 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)
Fig. 1. Surirella ebalensis sp. nov., from the holotype slide BR 4398, Lomami River, DR Congo, LM (DIC). A–C. Valve representing the holotype, different foci of the same valve. D–E. Different foci of the same valve. F. Girdle view. Scale bar = 10 µm.
Fig. 9 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)
Fig. 9. Surirella congolensis sp. nov., type material from sample CCA 2071, Lomami River, DR Congo, SEM. Internal view. A–B. Head pole showing the continuous raphe (arrow). C–D. Foot pole showing the interruption of the raphe and the straight slightly expanded terminal raphe endings. E–F. Detail of the alar canals. Scale bars: B–C = 2 µm; A, D = 1 µm.
Fig. 8 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)
Fig. 8. Surirella congolensis sp. nov., type material from sample CCA 2071, Lomami River, DR Congo, SEM. External view. A. Overview. B–C. Detail of foot pole showing the straight not expanded raphe endings (arrow). D. Detail of the apical pole showing the slightly curved raphe endings (arrow). E–F. Detail of the biseriate striae and the open fenestrae with the fenestral bars. Scale bars: A–B = 2 µm; C–F = 1 µm.
Fig. 2 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)
Fig. 2. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. External view. B, C, F = detail of the raphe keel with blunt spines orientated towards the valve face and which are draped over a large part of the indented mantle side. A. Overview. B–C. Detail of the valve ornamented with silica granules and blunt spines. D. Detail of the apical pole, showing the curved raphe endings. E–F. Detail of the foot pole showing the straight raphe endings. F. Short spherical shaped silica elements near the pole (arrow). Scale bars: A = 10 µm; B = 4 µm; C, F = 2 µm; D–E = 1 µm.
Fig. 4 in New and interesting Surirella taxa (Surirellaceae, Bacillariophyta) from the Congo Basin (DR Congo)
Fig. 4. Surirella ebalensis sp. nov., type material from sample CCA 2070, Lomami River, DR Congo, SEM. External view. Details of the various types of spines on the valve face and the keel. A–B. Detail of the valve surface with the biseriate striae (arrow) becoming sometimes uniseriate near the axial area. C–D. Section of the valve face showing the simple perforation of the silica wall at the areolae. Scale bars: A–B = 2 µm; C–D = 1 µm.
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.