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.
1,453
datasets available to search
ShareScore release 0.9.0
Dataset results
1,453 results for “Outcome research”
Figure 11 from: Vyshedskiy A, Dunn R, Piryatinsky I (2017) Neurobiological mechanisms for nonverbal IQ tests: implications for instruction of nonverbal children with autism. Research Ideas and Outcomes 3: e13239. https://doi.org/10.3897/rio.3.e13239
Figure 11 - Graphical representation of neurobiological requirements for WISC-V, Visual Puzzles. The NOB score (bottom) and the PCT score (top) as a function of question number.
Figure 10 from: Vyshedskiy A, Dunn R, Piryatinsky I (2017) Neurobiological mechanisms for nonverbal IQ tests: implications for instruction of nonverbal children with autism. Research Ideas and Outcomes 3: e13239. https://doi.org/10.3897/rio.3.e13239
Figure 10 - Graphical representation of neurobiological requirements for WISC-V, Matrix Reasoning. The NOB score (bottom) and the PCT score (top) as a function of question number.
Figure 3a from: Vyshedskiy A, Dunn R, Piryatinsky I (2017) Neurobiological mechanisms for nonverbal IQ tests: implications for instruction of nonverbal children with autism. Research Ideas and Outcomes 3: e13239. https://doi.org/10.3897/rio.3.e13239
Figure 3a - Integration of color modifier. The top two rows of the matrix indicate the rule: "the object in the right column is the result of combining color indicated in the row and the object indicated in the column" (solution: the white triangle in the tird cell).
Figure 1 from: Rane S, Jolly E, Park A, Jang H, Craddock C (2017) Developing predictive imaging biomarkers using whole-brain classifiers: Application to the ABIDE I dataset. Research Ideas and Outcomes 3: e12733. https://doi.org/10.3897/rio.3.e12733
Figure 1 - Weights (β-coefficients) for voxel-wise ReHo features from a support vector machine (SVM) classifier mapped on the glass brain to separate individuals with and without Autism Spectrum Disorder
Figure 1 from: Chen J, Bagga D (2017) Noise paradoxically increases reliability metrics. Research Ideas and Outcomes 3: e12641. https://doi.org/10.3897/rio.3.e12641
Figure 1 - A: The voxel-wise ICC values of RSFC with respect to a PCC seed under different SNR levels (SNR is defined as the ratio of the amplitude of fluctuations < 0.2 Hz to > 0.2 Hz, averaged across voxels in the slice, each column) and session numbers (by partitioning each subject's scan to multiple windows, each row). B: ICC values (a), between-subject (b) and inter-subject (c) variability averaged within all voxels of the displayed slice in A ('All', numbers in the parenthesis are the window number), and voxels significantly correlated with the PCC seed at the group level ('Active', evaluated across 10 subjects using the entire scan dataset filtered < 0.2 Hz, p < 0.05, uncorrected)
Figure 3 from: Leonard J, Flournoy J, Lewis-de los Angeles CP, Whitaker K (2017) How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI. Research Ideas and Outcomes 3: e12569. https://doi.org/10.3897/rio.3.e12569
Figure 3 - Out of sample prediction accuracy of autism diagnosis using resting state data as a function of sample size and motion-based exclusion criteria (percentage of fMRI, whole-brain volumes exceeding threshold). Red line is a naive classifier that assumes that all participants share the modal diagnosis (in this case, non-ASD). The black line spans the 5th to 95th percentile accuracy across iterations using a linear SVM, with the black points at the median value. Code and output can be found on GitHub (Flournoy and Leonard 2017).
Figure 2 from: Leonard J, Flournoy J, Lewis-de los Angeles CP, Whitaker K (2017) How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI. Research Ideas and Outcomes 3: e12569. https://doi.org/10.3897/rio.3.e12569
Figure 2 - Split-half reliability results showing how sample size (N) has a large effect on R squared (median R squared from 100 permutations) while motion threshold does not. Error bars represent average 95% confidence intervals across 100 permutations. Code and output can be found on GitHub (Flournoy and Leonard 2017).
Figure 1 from: Leonard J, Flournoy J, Lewis-de los Angeles CP, Whitaker K (2017) How much motion is too much motion? Determining motion thresholds by sample size for reproducibility in developmental resting-state MRI. Research Ideas and Outcomes 3: e12569. https://doi.org/10.3897/rio.3.e12569
Figure 1 - In order to investigate the effects of age range, motion exclusion threshold and sample size on functional connectiivity reliability we split the data into two matched samples. For the reliability analysis we averaged all participants in each sample and then calculated how well aligned the two groups were in terms of each pairwise regional connectivity measure. For the out-of-sample prediction analysis we used one half of the data to train a model and then tested it on the other half.
Figure 9b from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 9b - The ant Odontomachus simillimus on AntWeb (2017) (CASENT0172667), same specimen as top row in (a).
Figure 9c from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 9c - The ant Acanthognathus ocellatus on AntWeb (2017) (USNMENT00445730); (b) and (c) were contributed by different research labs both following AntWeb's imaging protocol to facilitate comparison.
Figure 8b from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 8b - Scanning electron microscope images comparing the spinnerets of various spider species, from Ramírez et al. (2014); anterior lateral spinnerets: E, C, male, others female; A, B, Austrochilidae: Thaida pecularis; C, Tengellidae: Tengella radiata; D, Homalonychidae: Homalonychus theologius; E, F, Penestomidae: Penestomus egazini).
Figure 9a from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 9a - Head and profile views of three specimens of the ant Odotomachus simillimus, from Fisher and Smith (2008).
Figure 5b from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 5b - Sigmoilina sigmoidea, from Cushman (1917) (2a, lateral view; 2b, aperture view; 3, axial cross section). Modified from image available on the World Register of Marine Species (WoRMS Editorial Board 2017).
Figure 8a from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 8a - Mixed media representation of two fly species. Wings are photographs while other parts were illustrated with color pencils. from Rodriguez et al. (2016) (fig. 3, Cryptodacus ornatus; fig. 4, Cryptodacus trinotatus).
Figure 7b from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 7b - Illustrations of Bathyphantes gracilis from Ivie (1969) (fig. 1, male pedipalp, standard ventral view; fig. 2, male pedipalp, standard retrolateral view). Bathyphantes may be a close relative of Linyphantes.
Figure 2b from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 2b - From Roberts (1985) (top, habitus, dorsal view; bottom, male pedipalp, retrolateral view).
Figure 17a from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 17a - Scatter plot of two morphometric values for four spider species (Araneae: Dipluridae: Lathrothele), each with a distinct domain. From Coyle (1995).
Figure 6a from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 6a - Various conocephaline katydid species, from Saussure (1893) (plate 19: 1, 2, 4, 15, 23, 28, habitus of female, lateral view; 3, 13, habitus, dorsal view; 5, 6, 11, 17, 18, 21, 22, 25, 30, head region, dorsal view; 7, 8, 10, 12, 14, 31, female ovipositor, lateral view; 9, 29, 32, right forewing; 16, 19, 26, head region, frontal view; 20, 24, 27, head region, lateral view; 33, tambourine of left forewing, detail; 34, tambourine of right forewing, detail). Image available from Biodiversity Heritage Library (biodiversitylibrary.org/item/14636#page/484/mode/1up).
Figure 15 from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 15 - Composite map showing region where the beetle Bledius externus (Insecta: Coleoptera: Staphylinidae: Oxytelinae) was collected. This map incorporates elements obtained from Google Earth attributed to their source. From Castro et al. (2016).
Figure 14b from: Egloff W, Agosti D, Kishor P, Patterson D, Miller J (2017) Copyright and the Use of Images as Biodiversity Data. Research Ideas and Outcomes 3: e12502. https://doi.org/10.3897/rio.3.e12502
Figure 14b - Entire entomological collection drawer imaged using high resolution semi-automated method. Lower image is detail from upper left corner of drawer, from Holovachov et al. (2014).
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.