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.
49
datasets available to search
ShareScore release 0.7.1
Dataset results
49 results for “global south”
Global River BankFull Discharge (GQBF) - Siberia(SI) & South Pacific/Australia(SP)
<p>The GQBF is the estimated bankfull discharge across ~2.87 million km (length) of global river reaches. The bankfull discharge here is defined as the maximum flow rate contained within a river just before inundation occurs in the surrounding floodplain. We based our river bankfull discharge estimation on a newly developed river network, Global RIver Topology (GRIT), using GRIT’s river reaches as the spatial scale to represent the variation in bankfull discharge. We included all GRIT river reaches that coincided with the Global River Width from Landsat (GRWL) river masks (with overlapping ratio >=0.5). This selects river reaches with satellite-derived width measurements >=30 m, resulting in a total length of ~2.87 million km. Here, the GQBF represents the time-averaged bankfull discharge at <1 km (river length) spatial resolution.</p> <p><strong>Regions</strong></p> <p>Added regions SI, SP Vector files.</p> <ul> <li>SI - Siberia</li> <li>SP - South Pacific/Australia</li> </ul> <p>The subcontinental catchment groups (vector, polygons) can be found at <a href="https://zenodo.org/records/11219313">GRIT domain polygon</a> (GRITv06_domain_GLOBAL.gpkg.zip). They allow for more fine-grained subsetting of data .</p> <p>Vector files are provided in geographic WGS84 coordinates (EPSG:4326).</p> <p><strong>Change log</strong></p> <ul> <li>v0.1 - 2024-09-29<br> <ul> <li>First globally complete dataset published</li> </ul> </li> <li>v0.1 - 2024-11-19 <ul> <li>Add vector files for regions SI, SP</li> </ul> </li> </ul>
Survey on policies for innovation in the Global South, 2022.
<p>In July-August 2022, the <a href="acceleratorlabs.undp.org">UNDP Accelerator Labs</a> launched a survey to get a big picture view on the work that its global network of 91 labs was doing to support innovation ecosystems. The results were surprisingly clear-cut and coherent.</p> <p>First, <strong>we learned that a solid majority of Labs had partnered with governments to deploy interventions in support of national innovation ecosystems, or was planning to do so in the near future</strong>. We were looking at a surge of government investment in innovation across the Global South. Furthermore, these Global South governments were looking beyond the usual Global North example of policies to support innovation and learning from each other.</p> <p>Second, <strong>we learned that UNDP was widely recognized as the leading organization in supporting Global South governments in this journey</strong>. And third, <strong>we learned that collaboration with governments that have invested in innovation becomes smoother and more impactful</strong>.</p> <p>This Zenodo entry contains a file aggregating all the responses to that survey. </p>
Attribution of 2022 August Heavy Precipitation Event in South Korea Using High-resolution Pseudo Global Warming Simulations: Sensitivity to Vertical Temperature Changes
<p>Post-processed CPM simulation datasets used for the paper "Attribution of 2022 August Heavy Precipitation Event in South Korea Using High-resolution Pseudo Global Warming Simulations: Sensitivity to Vertical Temperature Changes".</p>
Analysis of internet usage and bioblitz frequency in the Global South
<p>This dataset was used to analyse factors contributing to the number of bioblitzes conducting in countries in the Global South.</p> <p>This is part of a review into the effectiveness of bioblitz as a method for collecting data on biodiversity.</p> <p>We modeled population and internet usage with the number of iNaturalist Bioblitzes in a country from our sample (Groom 2021). We only just looked at those global regions where citizen science has tended to have lower prevalence in the past (Africa, Asia, and Latin America, and the Caribbean) compared to other regions. We identified a total of 254 Bioblitz projects from iNaturalist in 37 countries, in Africa (30 projects in 13 countries); Asia (71 projects in 11 countries); and Latin America and the Caribbean (153 projects in 13 countries).</p> <p>We took the total population of each country from the mean of 2015-18 values in millions from <a href="https://population.un.org/wpp/Download/Standard/Population/">https://population.un.org/wpp/Download/Standard/Population/</a> (United Nations, Department of Economic and Social Affairs, Population Division (2019). <em>World Population Prospects 2019, Online Edition. Rev. 1.</em>). Internet usage was taken as the percentage of individuals using the internet in 2017 (<a href="http://data.un.org/">http://data.un.org/</a>).</p> <p>The natural log of the number of iNaturalist projects was modelled against the log of the population in millions and the internet usage using the lm package of R.</p> <pre><code>SUMMARY_DATA <- read.delim2("summary_data.tsv", row.names=1) model <- lm(log(projects) ~log(population) + internet, data=SUMMARY_DATA) summary(model) </code></pre> <table> <tbody> <tr> <td> <p>Variable</p> </td> <td> <p>Coefficient</p> </td> <td> <p>Std. Error</p> </td> <td> <p>t-Statistic</p> </td> <td> <p>Prob.</p> </td> </tr> <tr> <td> <p>log(population) in millions</p> </td> <td> <p>0.345</p> </td> <td> <p>0.0865</p> </td> <td> <p>3.99</p> </td> <td> <p>0.0003 ***</p> </td> </tr> <tr> <td> <p>internet usage as a percentage of individuals per country</p> </td> <td> <p>0.016</p> </td> <td> <p>0.0060</p> </td> <td> <p>2.62</p> </td> <td> <p>0.0130 *</p> </td> </tr> </tbody> </table> <p>Residual standard error: 0.9167 on 34 degrees of freedom</p> <p>Multiple R-squared: 0.3911, Adjusted R-squared: 0.3553 </p> <p>F-statistic: 10.92 on 2 and 34 DF, p-value: 0.0002176</p> <p>To view properties of the model to ensure it conformed to the assumptions of the model and was a good fit. Plots are included in the attached files.</p> <pre><code>par(mfrow = c(2,2)) plot(model)</code></pre> <p>To view other correlations in the data the following code can be used. The output is included in the attached files.</p> <pre><code>correlations <- cor(SUMMARY_DATA[,c(2,3,4,6,11,13,14)],method = c("spearman")) install.packages("corrplot") library("corrplot") corrplot(correlations, method="square") </code></pre> <p> </p>
Survey data on the digitalization of informal businesses in the Global South
<p>During the spring of 2022, the UNDP Accelerator Labs created an online survey to investigate the uptake of digital tools by informal businesses in the Global South. </p> <p>We uploaded the questionnaire onto a digital surveys platform (<a href="https://www.kobotoolbox.org/">https://www.kobotoolbox.org/</a>). We then reached out through UNDP’s network of informal or small businesses in 16 countries, inviting them to complete the questionnaire and spread awareness about it. This implies that respondents are in no way a random sample of the target populations; this choice was made in the interest of speed and cost-effectiveness. We obviously claim no representativity, though we believe that some of our results are strong enough to be considered, to a first approximation, valid as a big picture. </p> <p>1,013 questionnaires from 16 countries, covering all UNDP regions, were completed. In the remaining three countries, we received fewer than 30 completed questionnaire, and decided to discard them. At the country level, the number of respondents ranges from 25 (Ecuador) to 306 (Peru). Our own analysis of the data is published here: <a href="https://doi.org/10.5281/zenodo.7896327">https://doi.org/10.5281/zenodo.7896327</a>.</p>
Conodont faunas across the Kasimovian–Gzhelian boundary (late Pennsylvanian) in South China and implications for the selection of the stratotype for the base of the global Gzhelian stage
The upper Pennsylvanian Naqing and Narao carbonate successions were deposited in intra-platform slope to basinal settings across the Kasimovian-Gzhelian boundary in Guizhou, South China. Conodont faunas comprise a mixture of the endemic taxa of the Idiognathodus luodianensis group and cosmopolitan species of the I. simulator group. The I. luodianensis group includes the new species I. fengtingensis, I. luodianensis, I. naqingensis and I. naraoensis. Platform landmark analysis demonstrates that the species of the I. luodianensis group differ in morphological features from co-occurring species of the I. simulator group. Both groups display similar increasing asymmetry in P1 element pairs across the Kasimovian-Gzhelian boundary, as recognized on the basis of the first occurrence of I. simulator. Many Kasimovian Idiognathodus species disappear and several Gzhelian species first appear with I. simulator, including two new species of Streptognathodus, S. nemyrovskae and S. zhihaoi. Just below the base of the Gzhelian, carbonate δ13C falls from 4‰ to 2‰ in both sections. The combination of an abrupt faunal turnover immediately above the prominent negative δ13C excursion might represent an oceanic event in South China, maybe recognizable on a global scale. One of these two South China sections may be the best location to place the GSSP for the base of the Gzhelian Stage.
Categorization of countries into Global South and Global North
<p>Structured data categorizing countries into two blocks: Global South and Global North. This categorization took into account factors such as HDI, colonization, and dependency. In the specific case of this categorization, countries of the Global North were understood as those with high economic income.</p>
Research Software Funders Global South
<p>The Research Software Alliance's (ReSA) mission is to bring research software communities together to collaborate on the advancement of research software. Given the ReSA mission, it is important to understand the landscape of communities involved with research software. In 2020, ReSA completed an initial exercise to scope the international research software community landscape. This work was reported by ReSA's Software Landscape Analysis task force via a <a href="https://www.researchsoft.org/blog/2020-03/">blog post</a>. The majority of the communities in the previous analysis represented the global north. To improve the extent of this landscape analysis, ReSA announced a paid opportunity for short-term contractors located in <a href="https://www.researchsoft.org/2022-mapping/">the global south</a> to collect data on communities and funders in their region in early 2022. This document describes how the work was undertaken, a summary of findings, the gaps and opportunities perceived by the data collectors and some highlights. This work identified 126 organisations and communities and 62 funder bodies that support research software in the global south. Their main activities are connecting people, training, and networking, and support through research grants.</p> <p> </p> <p>To add to this funders list please fill in the following form: <a href="https://forms.gle/CJWo24MUCjhWKh9U8">https://forms.gle/CJWo24MUCjhWKh9U8</a></p>
Research Software Communities Global South
<p>The Research Software Alliance's (ReSA) mission is to bring research software communities together to collaborate on the advancement of research software. Given the ReSA mission, it is important to understand the landscape of communities involved with research software. In 2020, ReSA completed an initial exercise to scope the international research software community landscape. This work was reported by ReSA's Software Landscape Analysis task force via a <a href="https://www.researchsoft.org/blog/2020-03/">blog post</a>. The majority of the communities in the previous analysis represented the global north. To improve the extent of this landscape analysis, ReSA announced a paid opportunity for short-term contractors located in <a href="https://www.researchsoft.org/2022-mapping/">the global south</a> to collect data on communities and funders in their region in early 2022. This document describes how the work was undertaken, a summary of findings, the gaps and opportunities perceived by the data collectors and some highlights. This work identified 126 organisations and communities and 62 funder bodies that support research software in the global south. Their main activities are connecting people, training, and networking, and support through research grants.</p> <p> </p> <p>To add to this communities list please fill in the following form <a href="https://forms.gle/KJE9vkBnM6vhh7cEA">https://forms.gle/KJE9vkBnM6vhh7cEA</a></p>
Figure 2 in Is the global decline reflects local declines? A case of the population trend of Far Eastern Curlew Numenius madagascariensis in Banyuasin Peninsula, South Sumatra, Indonesia
Figure 2. Population trend of number of the Far Eastern Curlew in Banyuasin Peninsula from 1984 to 2020.
Figure 3 in Is the global decline reflects local declines? A case of the population trend of Far Eastern Curlew Numenius madagascariensis in Banyuasin Peninsula, South Sumatra, Indonesia
Figure 3. Mix flocks of Far Eastern Curlew and Eurasian Curlew Numenius arquata in flight on 8 November 2020 in Banyuasin Peninsula, South Sumatra province, Indonesia (Photo: Cipto Dwi Handono).
Figure 4 in Is the global decline reflects local declines? A case of the population trend of Far Eastern Curlew Numenius madagascariensis in Banyuasin Peninsula, South Sumatra, Indonesia
Figure 4. Far Eastern Curlew standing at the mudflat on 8 November 2020 in the coastal zone of Banyuasin Peninsula, South Sumatra province, Indonesia (Photo: Cipto Dwi Handono).
Fig. 4 in The neglected diversity: Description and molecular characterisation of Trypanosoma haploblephari Yeld and Smit, 2006 from endemic catsharks (Scyliorhinidae) in South Africa, the first trypanosome sequence data from sharks globally
Fig. 4. Bayesian Inference (BI)/Maximum Likelihood (ML) analysis showing the phylogenetic position of Trypanosoma haploblephari (Yeld and Smit, 2006) genotypes representing morphotypes A and B inferred from partial 18S rRNA gene sequences. Comparative sequences representing known Trypanosoma species, with Trypanosoma avium (KT728402) as outgroup, were obtained from GenBank. Tree topologies for both the BI and ML trees were identical; the nodal support values (BI/ML) are represented on the BI tree. Some branches have been shortened with each //= 0.04 substitutions per site.
Fig. 3 in The neglected diversity: Description and molecular characterisation of Trypanosoma haploblephari Yeld and Smit, 2006 from endemic catsharks (Scyliorhinidae) in South Africa, the first trypanosome sequence data from sharks globally
Fig. 3. Micrographs of Trypanosoma haploblephari (Yeld and Smit, 2006) morphotype A (A–C) and T. haploblephari morphotype B (D–F) in Giemsa-stained blood films of Haploblepharus pictus and Poroderma pantherinum, respectively. Blood stage with kinetoplast (k) and undulating membrane (μm) visible (A–C); slender forms (B, E); presence of a flagellum (f) in deeply stained individuals (C, F). Scale bar: 10 μm.
Fig. 2 in The neglected diversity: Description and molecular characterisation of Trypanosoma haploblephari Yeld and Smit, 2006 from endemic catsharks (Scyliorhinidae) in South Africa, the first trypanosome sequence data from sharks globally
Fig. 2. Line drawing of Trypanosoma haploblephari (Yeld and Smit, 2006) from the host Poroderma pantherinum (Slide HE18-18) next to a drawing of a red blood cell.
FIG, 1. John William Daly (1933–2008) on the upper Río San Juan. This paper is dedicated to John Daly, our late friend and colleague, who helped collect three of the new species here described. In addition to his globally acclaimed discoveries in chemistry and pharmacology, John was an accomplished field herpetologist who contributed importantly to the systematics and natural history of dendrobatoid frogs (see Grant et al., 2006; Myers, 2009). This photograph shows John at age 37, with the upper Río San Juan behind him and branches overhead of a madroño tree (probably Garcinia magnifolia, syn. Rheedia chocoensis, Clusiaceae). When in South America, John was never far from a dendrobatid frog—this time, in the tree above his head, a tiny, undescribed semiarboreal species (also collected and later named "Dendrobates fuguritus" by our colleague Philip Silverstone). Other dendrobatids found nearby included Phyllobates aurotaenia (Boulenger, 1913), which was then being used for poisoning blowgun darts, and also the nontoxic species that we name Silverstoneia dalyi herein. (Photograph by C. W. Myers, 2 km above Playa de Oro, Chocó, February 16, 1971.) in Review of the Frog Genus Silverstoneia, with Descriptions of Five New Species from the Colombian Chocó (Dendrobatidae: Colostethinae)
FIG, 1. John William Daly (1933–2008) on the upper Río San Juan. This paper is dedicated to John Daly, our late friend and colleague, who helped collect three of the new species here described. In addition to his globally acclaimed discoveries in chemistry and pharmacology, John was an accomplished field herpetologist who contributed importantly to the systematics and natural history of dendrobatoid frogs (see Grant et al., 2006; Myers, 2009). This photograph shows John at age 37, with the upper Río San Juan behind him and branches overhead of a madroño tree (probably Garcinia magnifolia, syn. Rheedia chocoensis, Clusiaceae). When in South America, John was never far from a dendrobatid frog—this time, in the tree above his head, a tiny, undescribed semiarboreal species (also collected and later named "Dendrobates fuguritus" by our colleague Philip Silverstone). Other dendrobatids found nearby included Phyllobates aurotaenia (Boulenger, 1913), which was then being used for poisoning blowgun darts, and also the nontoxic species that we name Silverstoneia dalyi herein. (Photograph by C. W. Myers, 2 km above Playa de Oro, Chocó, February 16, 1971.)
Clinical Trials_Original dataset. Rising Pharmaceutical Innovation in the Global South.
<p>This is a supplementary document of the research reports from the "Research Collaboration on Technology, Equity, and the Right to Health", between the Global Health Centre (GHC) at the Geneva Graduate Institute in Switzerland, the James P. Grant School of Public Health at BRAC University in Bangladesh, and the Universidad de los Andes (ANDES) in Colombia, supported by the Open Society University Network (OSUN). For more information please refer to: Knowledge Portal on Innovation and Access to Medicines - https://www.knowledgeportalia.org/. </p>
Clinical trials analysis results. Rising pharmaceutical innovation in the Global South.
<p>This is a supplementary document of the research reports from the "Research Collaboration on Technology, Equity, and the Right to Health", between the Global Health Centre (GHC) at the Geneva Graduate Institute in Switzerland, the James P. Grant School of Public Health at BRAC University in Bangladesh, and the Universidad de los Andes (ANDES) in Colombia, supported by the Open Society University Network (OSUN). For more information please refer to: Knowledge Portal on Innovation and Access to Medicines - <a href="https://www.knowledgeportalia.org/">https://www.knowledgeportalia.org/</a></p>
Data from: Conodont faunas across the Kasimovian–Gzhelian boundary (Late Pennsylvanian) in South China and implications for the selection of the stratotype for the base of the global Gzhelian Stage
Open the record for dataset details and reuse information.
The Research Software Community Landscape in the Global South [Video]
<p>The Research Software Community Landscape in the Global South</p> <p><strong>Presentation and Video DOI: 10.5281/zenodo.7192692</strong></p> <p><strong>Watch the Video: <a href="https://youtu.be/pxmYroTxz-A">https://youtu.be/pxmYroTxz-A</a></strong></p> <p>Description:</p> <p>The Research Software Alliance's (ReSA) mission is to bring research software communities together to collaborate on the advancement of research software. Given the ReSA mission, it is important to understand the landscape of communities involved with research software. In 2020, ReSA completed an initial exercise to scope the international research software community landscape. This work was reported by ReSA's Software Landscape Analysis task force via a blog post. The majority of the communities in the previous analysis represented the global north. To improve the extent of this landscape analysis, ReSA announced a paid opportunity for short-term contractors located in the global south to collect data on communities and funders in their region in early 2022. This document describes how the work was undertaken, a summary of findings, the gaps and opportunities perceived by the data collectors and some highlights. This work identified 126 organisations and communities and 62 funder bodies that support research software in the global south. Their main activities are connecting people, training, and networking, and support through research grants.</p> <p>Blog post: <a href="https://www.researchsoft.org/blog/2022-10/">https://www.researchsoft.org/blog/2022-10/</a></p> <p>Please cite this work as: Martinez, Paula Andrea. (2022). The Research Software Community Landscape in the Global South. Zenodo. <a href="https://doi.org/10.5281/zenodo.7179892">https://doi.org/10.5281/zenodo.7179892</a></p> <p>Martinez, Paula Andrea. (2022). Research Software Communities Global South [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.7179807">https://doi.org/10.5281/zenodo.7179807</a></p> <p>Martinez, Paula Andrea. (2022). Research Software Funders Global South [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.7179867">https://doi.org/10.5281/zenodo.7179867</a></p> <p> </p> <p>To add to the funders list please fill in the following form: <a href="https://forms.gle/CJWo24MUCjhWKh9U8">https://forms.gle/CJWo24MUCjhWKh9U8</a></p> <p>To add to the communities list please fill in the following form <a href="https://forms.gle/KJE9vkBnM6vhh7cEA">https://forms.gle/KJE9vkBnM6vhh7cEA </a></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.