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.
8,537
datasets available to search
ShareScore release 0.9.0
Dataset results
8,537 results for “Openness”
FIGURE 1. Physalis victoriana. A. Habit. B. Flower. C. Extended corolla. D. Gynoecium. E. Flowering calyx. F. Berry and open fruiting calyx. G in Physalis victoriana (Solanaceae) a new species from Northern Argentina
FIGURE 1. Physalis victoriana. A. Habit. B. Flower. C. Extended corolla. D. Gynoecium. E. Flowering calyx. F. Berry and open fruiting calyx. G. Simple, curved, antrorse trichome. H. Glandular short trichome. I. Glandular trichome of the inner face of the fruiting calyx. Drawn from Toledo 1675 by S. Montecchiesi.
FIGURE 1. Phyllanthus myrsinites subsp. platyphyllus. A. Flowering branch. B. Pistillate flower. C. Open pistillate flower with two sepals removed showing the gynoecium. D. Staminate flower. E in A new infraspecific taxon of Phyllanthus myrsinites (Phyllanthaceae) from the Brazilian Amazon
FIGURE 1. Phyllanthus myrsinites subsp. platyphyllus. A. Flowering branch. B. Pistillate flower. C. Open pistillate flower with two sepals removed showing the gynoecium. D. Staminate flower. E. Open staminate flower showing the stamens. (A, D, E from G.T. Prance et al. 20400; B-C from J.M. Pires et al. 16689). Illustrated by Carlos Alvarez.
FIGURE 3. Friesodielsia sahyadrica. A. Branch with young and mature leaves. B. Open flower. C in Friesodielsia sahyadrica (Annonaceae), a peculiar new species from the Western Ghats, India
FIGURE 3. Friesodielsia sahyadrica. A. Branch with young and mature leaves. B. Open flower. C. Flower with two inner and one outer petal removed to show arrangement of stamens and carpels. D. Fruiting branch showing immature fruits and glaucous abaxial nature of the leaves. E. Mature fruit. Photos by Navendu Page
FIGURE 1. Andrographis stenophylla C.B. Clarke. A. Habit. B. Flower. C. Calyx. D. Opened corolla. E. Carpel. F. Fruit. G in Taxonomy, lectotypification and distribution of Andrographis stenophylla (Acanthaceae), a little known endemic species from southern India
FIGURE 1. Andrographis stenophylla C.B. Clarke. A. Habit. B. Flower. C. Calyx. D. Opened corolla. E. Carpel. F. Fruit. G. Seed (G. Gnanasekaran 126803, MH).
FIGURE 2. Bartsia lydiae. A. Flower. B. Corolla lip. C. Calyx, opened out from the ventral side. D. Bract, adaxial view. E. Anther. F in Bartsia lydiae, a new species of Bartsia sect. Laxae (Orobanchaceae) from the southern Peruvian Andes with a revised key to Bartsia sect. Laxae
FIGURE 2. Bartsia lydiae. A. Flower. B. Corolla lip. C. Calyx, opened out from the ventral side. D. Bract, adaxial view. E. Anther. F. Style. Illustration based on type specimen S.P. Sylvester 1754.
FIGURE 2. Oreocharis yunnanensis. A. Habit. B. Flower. C. Opened corolla showing stamens and staminode. D. Calyx and pistil with disc. E. Calyx. F. Bracts. G in Additional notes on Oreocharis yunnanensis, a species of Gesneriaceae from southern Yunnan, China, including morphological and molecular data
FIGURE 2. Oreocharis yunnanensis. A. Habit. B. Flower. C. Opened corolla showing stamens and staminode. D. Calyx and pistil with disc. E. Calyx. F. Bracts. G. Cross section of ovary. Illustration by Yun-Xi Zhu based on the holotype Yun-Hong Tan 6925.
FIGURE 1. Silene peloritana. A. Habit. B. Flower. C. Corolla. D. Open calyx. E in Silene peloritana (Caryophyllaceae) a new species from Sicily
FIGURE 1. Silene peloritana. A. Habit. B. Flower. C. Corolla. D. Open calyx. E. Petal (dorsal view). F. Petal (ventral view). G. Petal (lateral view). H. Coronal scale. I. Anther. J. Pistil. K. Capsule with calyx. L. Close capsule. M. Open capsule. N. Seed (lateral view). O. seed (dorsal view). Illustration by Salvatore Brullo based on type specimen (CAT).
Data related to: Open-system evolution of a crustal-scale magma column, Klamath Mountains, California
<p>Granitic magmas commonly display evidence for some level of interaction with and/or origins from crustal rocks. There is fundamental debate in the community as to the processes that control the origins of these magmas and the potential for their contamination as they pass through the crust. One approach to addressing these issues involves a combination of detailed field mapping combined with geochemical analysis of bulk-rock samples and their constituent minerals. In particular, resolution of debates about magma origin(s) and contamination processes rely on U-Pb ages of zircon combined with isotopic data gathered from bulk-rock samples and from minerals such as zircon.</p> <p>The data presented here consist of U-Pb, Hf, and oxygen isotope analyses of zircon crystals separated from a major plutonic complex in northern California: the Wooley Creek batholith and Slinkard pluton. In addition, data are presented for samples of the metamorphic rocks that host these intrusions and for xenoliths of these host rocks engulfed by the intrusions. These data are discussed in the above-mentioned manuscript. Generation of the data was supported by National Science Foundation grants EAR-0838342 to C. Barnes and A. Yoshinobu, EAR-0838546 to K. Chamberlain, and EAR-1524336 to J. Valley. The WiscSIMS isotope facility (oxygen isotope data) was supported by NSF grant EAR-1658823 and the University of Wisconsin-Madison.</p> <p>Figure 1 illustrates the locations of plutonic samples analyzed.</p> <p>Table 1 presents sample locations and rock types.</p> <p>Tables 2–5 present U-Pb ages and Hf isotope data determined by laser-ablation inductively coupled plasma mass spectrometry at the University of California-Santa Barbara.</p> <p>Tables 6A–6E present U-Pb ages determined by SHRIMP-RG (sensitive high resolution ion microprobe-reverse geometry) at Stanford University.</p> <p>Table 7 presents oxygen isotope (zircon) data determined by SIMS (secondary ion mass spectrometry at the University of Wisconsin-Madison.</p>
FIGURE 1. Primulina glandaceistriata. A. Growth habit. B. Opened corolla showing stamens and staminodes. C in Primulina glandaceistriata (Gesneriaceae), a new species from Guangxi, China
FIGURE 1. Primulina glandaceistriata. A. Growth habit. B. Opened corolla showing stamens and staminodes. C. Overhead view of pistil. D. Stigma. E. Calyx lobes.
FIGURE 3. Rafflesia mixta. A. Open male flower showing partially visible disk processes through the diaphragm aperture. B. Longitudinal section through a female flower showing ovary. C in Rafflesia mixta (Rafflesiaceae), a new species from Surigao del Norte, Mindanao, Philippines
FIGURE 3. Rafflesia mixta. A. Open male flower showing partially visible disk processes through the diaphragm aperture. B. Longitudinal section through a female flower showing ovary. C. Bud with perigone lobes removed to show the short column, blade-like processes, and ramenta. D. Disk with regularly distributed processes in two zones. E. Anthers underneath the disk. A. Barcelona 4044 with Manting, Arbolonio & Caballero. B. Arbolonio & Caballero 5. C–E. Barcelona 4043 with Manting, Arbolonio & Caballero.
FIGURE 2. Rafflesia mixta. A. Open flower. B in Rafflesia mixta (Rafflesiaceae), a new species from Surigao del Norte, Mindanao, Philippines
FIGURE 2. Rafflesia mixta. A. Open flower. B. Open flower with Ms. Mary Love P. Sanchez for scale. C. Longitudinal section through an immature male bud showing ramenta distribution. D. Rafflesia mira, open flower. E. Rafflesia mixta, thin section of a male bud showing details of ramenta (lower right: perigone tube, upper left: diaphragm). A. Arbolonio & Caballero 5 (isotype, collected 4 days after this photograph was taken). B. Barcelona 4044 with Manting, Arbolonio & Caballero. C & E. Barcelona 4043 with Manting, Arbolonio & Caballero. D. Photo courtesy of Department of Tourism, Region 11.
FIGURE 2. Hemiboea malipoensis. A–B. Habit. C. Involucre. D. Involucel and opened involucel. E. Opened corolla showing stamens and staminode. F. Stamens. G. Calyx and pistil with disc. I. Calyx. H. Stigma. J in Hemiboea malipoensis, a new species of Gesneriaceae from southeastern Yunnan, China
FIGURE 2. Hemiboea malipoensis. A–B. Habit. C. Involucre. D. Involucel and opened involucel. E. Opened corolla showing stamens and staminode. F. Stamens. G. Calyx and pistil with disc. I. Calyx. H. Stigma. J. Fruit. Illustration by Yun-Xi Zhu based on the holotype Yun-Hong Tan 6055.
Sato and Ise (submitted) Open Data
<p>______________________________________________________<br>Sato and Ise (2021) Open Data<br>Author: Hisashi SATO (JAMSTEC) hsatoscb_(at)_gmail.com<br>Date: 22 Feb 2022<br>URLs:<br>https://ebcrpa.jamstec.go.jp/~hsato/Sato_and_Ise_2020</p> <p>Corresponding publication: <br>H. Sato and T. Ise (2021) Predicting global terrestrial biomes with the LeNet convolutional neural network. Geoscientific Model Development 2022 Vol. 15 Issue 7 Pages 3121-3132. DOI: 10.5194/gmd-15-3121-2022<br>______________________________________________________<br>1. Folder "1.VCDs"<br>It contains Visualized Climate Environments (VCEs) for training and testing the Convolutional-Neural-Network (CNN) model. Names of compressed files (*.tar.gz) correspond to experiments. Each compressed file contains 4 to 16 folders.<br>Naming rule of folders:<br>The strings "CRU," "NCEP," "HadGEM," and "Miroc" stand for that the files are made from CRU_TS4.0, NCEP/NCAR reanalysis, Had2GEM-ESM, and Miroc-ESM climate datasets, respectively. The strings "AMeans" and "MMeans", respectively, stand for the annual-mean and monthly-mean climates, which are represented by VCEs in the compressed file.<br>The string "EachYear" means that the compressed files contains VCEs of each year climate from 1971 to 1980, otherwise the compressed files contains VCEs of averaged climate over 10 years. The strings "hist", "RCP26", and "RCP85" mean that the compressed files contain VCEs of climate averaged over 1971-1980, 2091-2100@RCP2.6, and 2091-2100@RCP8.5, respectively.<br>MainSimulation_training.tar.gz<br>VCEs for training the CNN model for the main simulation and dependency test of climatic datasets for training and reconstructing performances.<br>MainSimulation.tar.gz<br>VCEs for testing the CNN model for the main simulation.<br>CombinationSelection_Amean.tar.gz<br>VCEs for an experiment to find optimal combination of climatic variables (annual means) represented by the VCEs. In the VCE of the RGB color tile, up to three climate variables can be represented by RGB channels. To find the optimal combination of climatic variables, we systematically evaluated the model performance of 14 combinations of climatic variable experiments for annual means. It's result is presented in the Table S3.<br>Extracting this compressed fire results in "CRU", "NCEP", "HadGEM", and "Miroc" folders. Each folder contains 14 subfolders named with sequential numbers, which corresponds to model numbers in the Table S3.<br>CombinationSelection_Mmean.tar.gz<br>Same as the CombinationSelection_Amean.tar.gz except made with monthly mean climates, and related information is available in the Table S4.<br>ScalerSelection.tar.gz<br>VCEs for evaluating the influences of different transformations of climatic variables on the resulting accuracy. It's result is presented in the Table S5.<br>Extracting this compressed fire results in "CRU", "NCEP", "HadGEM", and "Miroc" folders. Each folder contains 4 subfolders named with sequential numbers. "Scaler1" stands for log transformed, "Scaler2" stands for no transformed (linear), "Scaler3" stands for Sigmoid(gain=5) transformed, "Scaler4" stands for Sigmoid(gain=10) transformed.<br>ColorAssignExperiment.tar.gz<br>VCEs for evaluate the influences of assignment patterns of air temperature and precipitation to RGB color channels of the VCE. It's result is presented in the Table S6. Extracting this compressed fire results in "CRU", "NCEP", "HadGEM", and "Miroc" folders. Each folder contains 6 subfolders named with sequential numbers, which indicates model number in the Table S6.<br>AverageExtentExperiment.tar.gz<br>VCEs for sensitivity test, where training and test accuracies are compared among models that are trained by monthly climate averaged over three different periods: 10 years (1971-1980; Control), 20 years (1961-1980), and 30 years (1951-1980).<br>Individual VCE shows climatic condition of each half degree grid cell. According to the ISLSCP2 data, VCEs are classified by their their potential vegetation type of the grid. Number of deepest folder names correspond vegetation code of the ISLSCP2.<br>Following is the vegetation code.<br> 01: Tropical Evergreen Forest/Woodland<br> 02: Tropical Deciduous Forest/Woodland<br> 03: Temperate Broadleaf Evergreen Forest/ Woodland<br> 04: Temperate Needleleaf Evergreen Forest/Woodland<br> 05: Temperate Deciduous Forest/Woodland<br> 06: Boreal Evergreen Forest/Woodland<br> 07: Boreal Deciduous Forest/Woodland<br> 08: Evergreen/Deciduous Mixed Forest<br> 09: Savanna<br> 10: Grassland/Steppe<br> 11: Dense Shrubland<br> 12: Open Shrubland<br> 13: Tundra<br> 14: Desert<br> 15: Polar Desert/Rock/Ice<br>The naming rule for VCEs of 10 years average climate is following:<br>Latitude number + "_" + Longitude number + ".png"<br>The naming rule for VCEs of each year's climate is following:<br>Latitude number + "_" + Longitude number + "_" + Year of climate + ".png"<br>Here, latitude number ranges from 001 to 360, starting from north-latitude-90 to southward with half degree interval. The longitude number ranges from 001 to 720, starting from west-longitude-180 to eastward with half degree interval. <br>On top of this subfolder, there is PicList.zip, which is a compressed file of PicList.txt. This text file is required to classify VCEs with the trained model.<br>_____________________________________________<br>2. Folder "2.Result"<br>It contains copies of the image classification results on the Digits screen. <br>Subfolder names correspond to experiment names. Each subfolder contains sub sub-folders "DigitsOutput," "ConfusionMatrix," and "ReconstructedBiomeMap." Naming rules for files are basically same as those of VCEs.<br>_____________________________________________<br>3. Folder "3.LearningCurves"<br>It contains screen capture of Digits output, showing learning curve of CNN models. CRU climate data. This folder contains 5 subfolders. Naming rules of these subfolders are same as those of VCEs.<br>_____________________________________________<br>4. Folder "5.FigureMaterials" <br>It contains data and codes (in R) for drawing the figures in the manuscript."<br>_____________________________________________________________</p>
Figure 2 in The behaviour of orientation of openings of burrows by Liolaemus lutzae (Squamata: Liolaemidae): is it influenced by environmental factors?
Figure 2. (Above) Direction of the openings of retreats (n = 59, in degrees) dug by Liolaemus lutzae, and (below) terrain slope direction (n = 45, in degrees) in which the retreats were dug at the restinga of the Parque Natural Municipal de Grumari, municipality of Rio de Janeiro, Brazil. The arrows represent the mean vector (µ) and the mean vector length (r) (see Table 2).
Figure 1 in The behaviour of orientation of openings of burrows by Liolaemus lutzae (Squamata: Liolaemidae): is it influenced by environmental factors?
Figure 1. (Above) Direction of the openings of retreats (n = 132, in degrees) dug by Liolaemus lutzae, and (below) terrain slope direction (n = 115, in degrees) in which the retreats were constructed at the restinga of the Reserva Ecológica Estadual de Jacarepiá, municipality of Saquarema, Brazil. The arrows represent the mean vector (µ) and the mean vector length (r) (see Table 1).
Figure 6 in Occurrences of large sharks in the open waters of the southeastern Mediterranean Sea
Figure 6. Total length frequency distribution for blue sharks (Prionace glauca) captured in the southeastern Mediterranean large pelagic fisheries during 1998–2005.
Figure 3 in Occurrences of large sharks in the open waters of the southeastern Mediterranean Sea
Figure 3. Map depicting capture locations of blue sharks (Prionace glauca) in the southeastern Mediterranean large pelagic fisheries during 1998–2005.
Figure 5 in Occurrences of large sharks in the open waters of the southeastern Mediterranean Sea
Figure 5. Map depicting capture locations of other large shark species in the southeastern Mediterranean large pelagic fisheries during 1998–2005.
Figure 2 in Occurrences of large sharks in the open waters of the southeastern Mediterranean Sea
Figure 2. (Top) Annual trend of large shark species richness as inferred from the slope of a linear regression of average number of species upon year on a series of randomly selected hauls in each year. Open circles depict number of species observed during a year. Dashed lines indicate centred 95% confidence intervals. (Bottom) Generalized additive model derived effects of the investigated parameters on the binomial probability of encountering large sharks. Dashed lines indicate two standard errors above and below the estimates.
Figure 7. A in Occurrences of large sharks in the open waters of the southeastern Mediterranean Sea
Figure 7. A rare specimen of basking shark (Cetorhinus maximus) landed in the Athens auction fish market in March 2009.
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.