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.
387
datasets available to search
ShareScore release 0.9.0
Dataset results
387 results for “National Survey”
Data from: Gynaecological cancer follow-up: national survey of current practice in the UK
Open the record for dataset details and reuse information.
National mileage fee survey
Open the record for dataset details and reuse information.
National survey-based investigation of climate risk perceptions and adaptation readiness in Greece
Open the record for dataset details and reuse information.
LBA-ECO CD-04 Biomass Survey, km 83 Tower Site, Tapajos National Forest, Brazil
This data set contains the results of a biometric tree survey of a 19.25 ha area adjacent to the eddy flux tower at the km 83 logged forest tower site in Tapajos National Forest, Para, Brazil. The survey was done in March 2000. All measurements reported here were taken before the logging began. Diameters of all trees > 35 cm DBH within the 19.25 ha survey area were recorded and trees with DBH between 10 and 35 cm DBH were recorded along three transects with a total area of 2.3 ha (Miller et al., 2004). These data were used to calculate net ecosystem productivity (NEP) and the role of this forest as a carbon source or sink. Biometric data are reported in one comma-delimited ASCII file.
Figure 9 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 9 Holotype of Pachylabra nevilliana Annandale & Prashad, 1921; NZSI M.11864/2.
Figure 8 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 8 Lectotype of Ampullaria globosa var. minor Nevill, 1877; NZSI M.2445.
Figure 4 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 4 Holotype of Ampullaria conica var. expansa Nevill, 1877; NZSI M.2426.
Figure 5 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 5 Lectotype of Ampullaria globosa var. incrassatula Nevill, 1877; NZSI M.2399.
Figure 14 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 14 Collection labels. Ampullaria globosa var. minor Nevill, 1877; NZSI M.2445.
Figure 10 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 10 Holotype of Pila robsoni Prashad, 1925; NZSI M.2414.
Figure 3 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 3 Holotype of Ampullaria erronea Nevill, 1877; NZSI M.2404.
Figure 7 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 7 Lectotype of Pachylabra turbinis var. lacustris Annandale, 1920; NZSI M.10511/2.
Figure 2 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 2 Syntype of Pachylabra angelica Nevill, 1885; NZSI M.11649/2.
Figure 6 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 6 Lectotype of Ampullaria ampullacea var. javensis Nevill, 1885; NZSI M.27736/6.
Figure 16 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 16 Collection labels. Ampullaria stoliczkana Nevill, 1885; NZSI M.2420.
Figure 11 from: Tripathy B, Sajan S, Cowie RH (2019) Illustrated catalogue of types of Ampullariidae Gray, 1824 (Mollusca, Gastropoda) in the National Zoological Collection of the Zoological Survey of India, with lectotype designations. Zoosystematics and Evolution 96(1): 1-23. https://doi.org/10.3897/zse.96.47792
Figure 11 Holotype of Ampullaria stoliczkana Nevill, 1885; NZSI M.2420.
Socio-economic survey of local populations in Akagera (Rwanda) and Odzala-Kokoua (RoC) national parks
<p>We collected data on socio-economic factors (demography, education, food consumption, NTFP and bushmeat collection, income-generating activities) to encompass livelihood strategies.</p>
Map 1 from: Liu K-K, Luo H-P, Ying Y-H, Xiao Y-X, Xu X, Xiao Y-H (2020) A survey of Phrurolithidae spiders from Jinggang Mountain National Nature Reserve, Jiangxi Province, China. ZooKeys 947: 1-37. https://doi.org/10.3897/zookeys.947.51175
Map 1 Distribution of Alboculus zhejiangensis (Song & Kim, 1991), comb. nov., in China.
Data from: Population need for primary eye care in Rwanda: a national survey
Background: Universal access to Primary Eye Care (PEC) is a key global initiative to reduce and prevent avoidable causes of visual impairment (VI). PEC can address minor eye conditions, simple forms of uncorrected refractive error (URE) and create a referral pathway for specialist eye care, thus offering a potential solution to a lack of eye health specialists in low-income countries. However, there is little information on the population need for PEC, including prevalence of URE in all ages in Sub-Saharan Africa. Methods: A national survey was conducted of people aged 7 and over in Rwanda in September-December 2016. Participants were selected through two-stage probability proportional to size sampling and compact segment sampling. VI (visual acuity<6/12) was assessed using Portable Eye Examination Kit (PEEK); URE was detected using a pinhole and presbyopia using local near vision test. We also used validated questionnaires to collect socio-demographic and minor eye symptoms information. Prevalence estimates for VI, URE and need for PEC (URE, presbyopia with good distance vision, need for referrals and minor eye conditions) were age and sex standardized to the Rwandan population. Associations between age, sex, socio-economic status and the key outcomes were examined using logistic regression. Results: 4618 participants were examined and interviewed out of 5361 enumerated (86% response rate). The adjusted population prevalence of VI was 3.7% (95%CI=3.0-4.5%), URE was 2.2% (95%CI=1.7-2.8%) and overall need for PEC was 34.0% (95%CI=31.8-36.4%). Women and older people were more likely to need PEC and require a referral. Conclusions: Nearly a third of the population in Rwanda has the potential to benefit from PEC, with greater need identified in older people and women. Universal access to PEC can address unmet eye health needs and public health planning needs to ensure equitable access to older people and women.
SARS-CoV-2 seroprevalence in Mongolia: Results from a national population survey
<p>Results of population-based age stratified seroepidemiological investigation in Mongolia</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.