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.
1,202
datasets available to search
ShareScore release 0.9.0
Dataset results
1,202 results for “interests”
FIGURE 22 in Orthoptera (Insecta: Tettigonioidea, Pyrgomorphoidea, Acridoidea) of Kafa Biosphere Reserve, Bale Mountains National Park and other areas of conservation interest in Ethiopia
FIGURE 22. Ovipositor and subgenital plate of females Peropyrrhicia.
FIGURE 8 in Orthoptera (Insecta: Tettigonioidea, Pyrgomorphoidea, Acridoidea) of Kafa Biosphere Reserve, Bale Mountains National Park and other areas of conservation interest in Ethiopia
FIGURE 8. Conocephalus conocephalus, Shorori Wetland (1610 m), Ethiopia. Scale bar represents 1 cm.
FIGURE 27 in Orthoptera (Insecta: Tettigonioidea, Pyrgomorphoidea, Acridoidea) of Kafa Biosphere Reserve, Bale Mountains National Park and other areas of conservation interest in Ethiopia
FIGURE 27. Habitus of male and female Peropyrrhicia keffensis n. sp. Scale bar represents 1 cm.
FIGURE 5 in Orthoptera (Insecta: Tettigonioidea, Pyrgomorphoidea, Acridoidea) of Kafa Biosphere Reserve, Bale Mountains National Park and other areas of conservation interest in Ethiopia
FIGURE 5. Pseudorhynchus lanceolatus, Dembi Forest (1260 m), Ethiopia. Scale bar represents 1 cm.
FIGURE 48. Paracinema t in Orthoptera (Insecta: Tettigonioidea, Pyrgomorphoidea, Acridoidea) of Kafa Biosphere Reserve, Bale Mountains National Park and other areas of conservation interest in Ethiopia
FIGURE 48. Paracinema t. tricolor, Shorori Wetland (1610), Ethiopia. Scale bar represents 1 cm.
Figure 2. - Number of species recorded in Jean Gutierrez collection dataset (solid bar) and in the literature (dashed bar) compiled in Spider Mites Web (http://www1.montpellier.inra.fr/CBGP/spmweb/) for the areas of particular interest. Colour scheme same as in Figure 1.
Figure 2. - Number of species recorded in Jean Gutierrez collection dataset (solid bar) and in the literature (dashed bar) compiled in Spider Mites Web (http://www1.montpellier.inra.fr/CBGP/spmweb/) for the areas of particular interest. Colour scheme same as in Figure 1.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Figure 1. - World map representing all the locations mentioned in the dataset. Areas of particular interest are represented with the same colour (⬤ Madagascar, ⬤ Western Indian Ocean, ⬤ Papuasia, ⬤ New Caledonia, ⬤ South Pacific). Grey spots gather all the other locations.
Interests, beliefs, experience, and perceptions shape tolerance towards impacts of recovering predators
<ol> <li>The modification of landscapes is increasing the interface between humans and wildlife, while conflicts concerning predator impacts on human activities persist. Some previously persecuted but now protected predator species are experiencing recovery and range expansion.</li> <li>Tolerance is considered essential for achieving coexistence between humans and wildlife; however, its conceptualisation remains unresolved. Little is known about tolerance in the context of recovering predators, particularly which drivers are relevant to all or specific species and human interests.</li> <li>Using an online questionnaire survey shared with members of organisations with interests in rural land-based activities, we collected data on interests and beliefs, and attitudes, perceptions, experience, and management preferences for six recovering vertebrate predators in the UK (n=819). We created a species tolerance score representing the management choices of the respondents in different conflict scenarios, which differed in the degree of impact on the predator population.</li> <li>Our species tolerance score was characterized by a complex combination of the interests and beliefs of the respondents about wildlife management, perceptions and experience of that species (perceived benefits, population trend, positive and negative experience, indirect negative experience) and negative experience of other recovering predators. </li> <li>We found a tolerance gradient between interest groups with notable overlap between groups with primary interests in wildlife conservation, shooting, farming, and fishing. Although higher perceived benefits consistently corresponded to higher tolerance, having a negative experience of the species dampened the effect of perceived benefits on tolerance. When both negative personal and indirect experiences were reported, tolerance was dramatically reduced. The classification of species from least to most tolerated was consistent between interest groups. </li> <li>The application of our species tolerance score as the normative dimension (i.e., acceptability) in Brenner and Metcalf's (2020) Social Tolerance of Wildlife Framework highlights that tolerance (negative attitude-high acceptability) is potentially rare and more positive attitudes must be achieved before acceptance of the impacts of species can increase. </li> <li>Our findings highlight that considering only primary interests may hinder debates concerning recovering predators. Strategies to reduce negative experiences or change how they are perceived could significantly increase tolerance in combination with increasing positive experiences.</li> </ol>
Descriptive Study on Nursing Students' Interest in Using Digital Communication and Social Media in their Field after Covid-19
<p>This paper is about Descriptive study of nursing students' interest in using Digital communication in their field after Covid 19. Digital communication and social media have massive social interaction among community users that generate an extensive amount of data. The study was conducted in the faculty of nursing at Najran University, King Dome of Saudi Arabia (KSA). A descriptive correlational research design was followed in this study Sample: 300 nursing students. The first tool: is the interview sheet. Include two parts: Part (1) student personal data. Part (2) the nursing students' interest in Digital communication and social media. The second tool: - a questionnaire to Measure nursing students' knowledge about using Digital communication and social media in their field. Results: (74.7%) of nursing students were interested in Digital communication, and more than half (55.3 %) knew about Digital communication and social media, there's a statistical association between the academic level and students' interest. Provide special education about Digital communication to improve students' knowledge in the health field for using after covid 19, In-service Training for Various Digital communication and social media platforms. dissemination of the findings of this research study to the public and private healthcare organizations</p>
DATABASE 01 ILE teachers' training interests
<p>This database was collected from april to july 2023, asking teachers for their interests in training related to Innovative Learning Environments.</p>
MOVMUS-UJI Dataset & ERGOMOVMUS: EMG and kinematics data of the hand in activities of daily living with special interest for ergonomics
<p>A dataset of <strong>human hand kinematics</strong> and <strong>forearm muscle activation</strong> collected during the performance of a wide variety of activities of daily living (ADLs) is presented, with tagged characteristics of products and tasks. A total of <strong>26 participants</strong> performed <strong>161 ADLs</strong>, selected to be representative of common elementary tasks, grasp types, product orientations and performance heights. 105 products were used, being varied regarding shape, dimensions, weight and type (common products and assistive devices).</p> <p>The data were recorded using CyberGlove instrumented gloves on both hands measuring 18 degrees of freedom on each and seven surface EMG sensors per arm recording muscle activity. The products and their arrangement were the same across subjects, and tasks were performed in a guided way. Data of <strong>more than 4100 ADLs</strong> is presented in this dataset as <strong>Matlab structures</strong> with full continuous recordings, which may be used in applications such as machine learning or to characterize healthy human hand behaviour.</p> <p>The dataset is accompanied with a <strong>custom data visualization application (ERGOMOVMUS)</strong> as a tool for ergonomics applications, allowing visualization and calculation of aggregated data from specific task, product and/or subjects’ characteristics.</p> <p> </p> <p><strong>v3.0 includes the following updates:</strong></p> <p>- Statistical summary of the recordings both in .xlsx and .ods file format (v1.1 only included it in .xlsx file format)</p> <p>- Updated experiment details in "MOVMUS-UJI DATASET GUIDE.pdf".</p>
Quantifying research interests in 7,521 mammalian species with h-index: a case study (scopus output)
<p>Dataset of bibliometric data collected from Scopus for the manuscript 'Quantifying research interests in 7,521 mammalian species with h-index: a case study'.</p>
FIGURE 7 in Two Interesting Damaeid Mites (Acari, Oribatida, Damaeidae Berlese, 1896) From The British Isles And Svalbard (Spitsbergen, Norway), With A Description Of Kunstidamaeus Arcticus N.Sp.
FIGURE 7: Epidamaeus sp. (aff. floccosus Behan-Pelletier and Norton, 1985): A – femur and genu I; B – genu, tibia and tarsus I; C – femur, genu and tibia II; D – trochanter, femur and genu III; E – trochanter, femur and genu IV; F – genu, tibia and tarsus IV (scale bar = 50 µm).
FIGURE 5 in Two Interesting Damaeid Mites (Acari, Oribatida, Damaeidae Berlese, 1896) From The British Isles And Svalbard (Spitsbergen, Norway), With A Description Of Kunstidamaeus Arcticus N.Sp.
FIGURE 5: Epidamaeus sp.(aff. floccosus Behan-Pelletier and Norton, 1985): A – lateral view of rostrum, B – lateral view on bothridial area and anterior part of notogaster, C – genital setae g1-g5, aggenital seta and adanal seta ad3; D – lateral part of prodorsum; E – parabothridial apophyses Sa and Sp; F – discidium; G – spinae adnatae (scale bars = 25 µm).
FIGURE 3 in Two Interesting Damaeid Mites (Acari, Oribatida, Damaeidae Berlese, 1896) From The British Isles And Svalbard (Spitsbergen, Norway), With A Description Of Kunstidamaeus Arcticus N.Sp.
FIGURE 3: Kunstidamaeus arcticus n.sp.: A – leg I; B – trochanter, femur and genu IV; C – tibia and tarsus IV; D – femur and genu IV, axial view; E – tibia IV, axial view; F – trochanter III; G – genu and tibia III (scale bar = 50 µm).
FIGURE 4 in Two Interesting Damaeid Mites (Acari, Oribatida, Damaeidae Berlese, 1896) From The British Isles And Svalbard (Spitsbergen, Norway), With A Description Of Kunstidamaeus Arcticus N.Sp.
FIGURE 4: Epidamaeus sp. (aff. floccosus Behan-Pelletier and Norton, 1985): A – dorsal view, legs only partly depicted; B – ventral view, legs and gnathosoma only partly depicted (scale bar = 200 µm).
Tango Spacecraft Dataset for Region of Interest Estimation and Semantic Segmentation
<p><strong>Reference Paper: </strong></p> <p><a href="https://doi.org/10.1016/j.actaastro.2023.01.012"><strong>M. Bechini, M. Lavagna, P. Lunghi, Dataset generation and validation for spacecraft pose estimation via monocular images processing, Acta Astronautica 204 (2023) 358–369</strong></a></p> <p><a href="https://www.researchgate.net/publication/361924362_Spacecraft_Pose_Estimation_via_Monocular_Image_Processing_Dataset_Generation_and_Validation">M. Bechini, P. Lunghi, M. Lavagna. "Spacecraft Pose Estimation via Monocular Image Processing: Dataset Generation and Validation". In 9th European Conference for Aeronautics and Aerospace Sciences (EUCASS)</a></p> <p><strong>General Description:</strong></p> <p>The "<em>Tango Spacecraft Dataset for Region of Interest Estimation and Semantic Segmentation</em>" dataset here published should be used for Region of Interest (ROI) and/or semantic segmentation tasks. It is split into 30002 train images and 3002 test images representing the Tango spacecraft from Prisma mission, being the largest publicly available dataset of synthetic space-borne noise-free images tailored to ROI extraction and Semantic Segmentation tasks (up to our knowledge). The label of each image gives, for the Bounding Box annotations, the filename of the image, the ROI top-left corner (minimum x, minimum y) in pixels, the ROI bottom-right corner (maximum x, maximum y) in pixels, and the center point of the ROI in pixels. The annotation are taken in image reference frame with the origin located at the top-left corner of the image, positive x rightward and positive y downward. Concerning the Semantic Segmentation, RGB masks are provided. Each RGB mask correspond to a single image in both train and test dataset. The RGB images are such that the R channel corresponds to the spacecraft, the G channel corresponds to the Earth (if present), and the B channel corresponds to the background (deep space). Per each channel the pixels have non-zero value only in correspondence of the object that they represent (Tango, Earth, Deep Space). More information on the dataset split and on the label format are reported below. </p> <p><strong>Images Information:</strong></p> <p>The dataset comprises 30002 synthetic grayscale images of Tango spacecraft from Prisma mission that serves as train set, while the test set is formed by 3002 synthetic grayscale images of Tango spacecraft from Prisma mission in PNG format. About 1/6 of the images both in the train and in the test set have a non-black background, obtained by rendering an Earth-like model in the raytracing process used to define the images reported. The images are noise-free to increase the flexibility of the dataset. The illumination direction of the spacecraft in the scene is uniformly distributed in the 3D space in agreement with the Sun position constraints.</p> <p><br> <strong>Labels Information:</strong></p> <p>Labels for the bounding box extraction are here provided in separated JSON files. The files are formatted per each image as in the following example:</p> <ul> <li> filename : tango_img_1 # name of the image to which the data are referred</li> <li> rol_tl : [x, y] # ROI top-left corner (minimum x, minimum y) in pixels</li> <li> roi_br : [x, y] # ROI bottom-right corner (maximum x, maximum y) in pixels</li> <li> roi_cc : [x, y] # center point of the ROI in pixels</li> </ul> <p>Notice that the annotation are taken in image reference frame with the origin located at the top-left corner of the image, positive x rightward and positive y downward.To make the usage of the dataset easier, both the training set and the test set are split in two folders containing the images with earth as background and without background.</p> <p>Concerning the Semantic Segmentation Labels, they are provided as RGB masks named as "filename_mask.png" where "filename" is the filename of the image of the training set or the test set to which a specific mask is referred. The RGB images are such that the R channel corresponds to the spacecraft, the G channel corresponds to the Earth (if present), and the B channel corresponds to the background (deep space). Per each channel the pixels have non-zero value only in correspondence of the object that they represent (Tango, Earth, Deep Space). </p> <p><strong>VERSION CONTROL</strong></p> <ul> <li>v1.0: This version contains the dataset (both train and test) of full scale images with ROI annotations and RGB masks for Semantic Segmentation tasks. These images have width=height=1024 pixels. The position of tango with respect to the camera is randomly selected from a uniform distribution, but it is ensured the full visibility in all the images. </li> </ul> <p>Note: this dataset contains the same images of the <em>"Tango Spacecraft Wireframe Dataset Model for Line Segments Detection"</em> v2.0 full-scale (DOI: <a href="https://doi.org/10.5281/zenodo.6372848">https://doi.org/10.5281/zenodo.6372848</a>) and also "<em>Tango Spacecraft Dataset for Monocular Pose Estimation</em>" v1.0 (DOI: <a href="https://doi.org/10.5281/zenodo.6499007">https://doi.org/10.5281/zenodo.6499007</a>) and they can be used together by combining the annotations of the relative pose and the ones of the reprojected wireframe model of Tango, with also the ones of the ROI. <strong>These three datasets give the most comprehensive dataset of space borne synthetic images ever published</strong> (up to our knowledge).</p>
Quantifying research interests in 7,521 mammalian species with h-index: a case study (model output)
<p>Model results for Quantifying research interests in 7,521 mammalian species with h-index: a case study</p>
Study of the genetic and phenotypic variation among wild and cultivated clary sages provides interesting avenues for breeding programs of a perfume, medicinal and aromatic plant
<p>A road-map of the genetic and phenotypic diversities in both crops and their wild-related species can help identifying valuable genetic resources for further crop breeding. The clary sage (<em>Salvia sclarea L.</em>), a perfume, medicinal and aromatic plant, is used for sclareol production and ornamental purposes. Despite its wide use in the field of cosmetics, the phenotypic and genetic diversity of wild and cultivated clary sage remains to be explored. We characterized the genetic and phenotypic variation of a collection of six wild <em>S. sclarea</em> populations from Croatia, sampled along an altitudinal gradient, and of populations of three <em>S. sclarea</em> cultivars. We showed low level of genetic diversity for the two <em>S. sclarea</em> traditional cultivars used for essential oil production and for ornamental purposes, respectively. In contrast, a recent cultivar resulting from new breeding methods, which involve hybridizations among several genotypes rather than traditional recurrent selection and self-crosses over time, showed high genetic diversity. We also observed a marked phenotypic differentiation for the ornamental clary sage compared with other cultivated and wild clary sages. Instead, the two cultivars used for essential oil production, a traditional and a recent, respectively, were not phenotypically differentiated from the wild Croatian populations. Our results also featured some wild populations with high sclareol content and early-flowering phenotypes as good candidates for future breeding programs. This study opens up perspectives for basic research aiming at understanding the impact of breeding methods on clary sage evolution, and highlights interesting avenues for clary breeding programs.</p>
Fig. 7 in New synonyms, and first and interesting records of certain species of the subtribe Stenolophina from the Palaearctic, Oriental and Afrotropical regions (Coleoptera, Carabidae, Harpalini, Stenolophina)
Fig. 7: Anthracus angusticollis (PÉRINGUEY, 1908). Distribution.
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.