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.
8,038
datasets available to search
ShareScore release 0.7.1
Dataset results
8,038 results for “validation”
Data for article of validation of a two-stage process for polyhydroxyalkanoates production
<p>The information contained in this data section corresponds to the article titled "Microrespirometric validation of a two-stage process for polyhydroxyalkanoates production from peanut oil and propionate with Cupriavidus necator," published in The Open Chemical Engineering Journal. Three Excel files are attached as data, providing information on the figures related to the growth kinetics and the results of the respirometric experiments.</p>
M1-data-format-only compositions and two-rater judgments of composition validity
<p>The set of graph compositions produced by the implementation of M1 data-format-matching algorithm and the validity judgements of two of the authors MMW and WRH.</p>
Figs 1–4 in Validation of Eclipta dendensis Nascimento & Santos-Silva, 2017 (nomen nudum) (Coleoptera, Cerambycidae, Cerambycinae, Rhinotragini)
Figs 1–4. Eclipta dendensis sp. nov., holotype ♀, images copied from NASCIMENTO & SANTOS-SILVA (2017): 1, dorsal habitus; 2, ventral habitus; 3. lateral habitus; 4, head, frontal view. Total length: 8,55 mm.
IGN Train and Validation Data for ICDAR'24 MapText Competition
<p>Data set of 2Kx2K image tiles cropped from Napoleonic Cadastre maps of the <a href="https://archives.valdemarne.fr/recherches/archives-en-ligne/cadastre-napoleonien">Val de Marne Archive</a> for the <a href="https://rrc.cvc.uab.es/?ch=28">ICDAR'24 Competition on Historical Map Text Detection, Recognition, and Linking</a>.</p> <p>Annotations and images follow the format described at the competition website and can be evaluated using the official <a href="https://github.com/icdar-maptext/evaluation">evaluation repository</a> script.</p> <table> <tbody> <tr> <td> </td> <td><strong>Train</strong></td> <td><strong>Validation</strong></td> </tr> <tr> <td>Annotations</td> <td><code>ign_train.json</code></td> <td><code>ign_val.json</code></td> </tr> <tr> <td>Images</td> <td><code>train.zip</code></td> <td><code>val.zip</code></td> </tr> <tr> <td>Files</td> <td><code>ign/train/*.jpg</code></td> <td><code>ign/val/*.jpg</code></td> </tr> <tr> <td>Tiles</td> <td>80</td> <td>15</td> </tr> <tr> <td>Map Sheets</td> <td>37</td> <td>9</td> </tr> <tr> <td>Words</td> <td>8,096</td> <td>1,801</td> </tr> <tr> <td>Label Groups</td> <td>7,449</td> <td>1,661</td> </tr> <tr> <td>Illegible Words</td> <td>563</td> <td>217</td> </tr> <tr> <td>Truncated Words</td> <td>371</td> <td>91</td> </tr> <tr> <td>Valid Words</td> <td>7,533</td> <td>1,584</td> </tr> </tbody> </table> <p><em>Original images available at <a href="https://archives.valdemarne.fr/recherches/archives-en-ligne/cadastre-napoleonien" target="_blank" rel="noopener">https://archives.valdemarne.fr/recherches/archives-en-ligne/cadastre-napoleonien</a> as of 1 Feb. 2024.</em></p>
Post-fire flood hazard model (PF2HazMo) version 1.0.0: Model scripts and parameterization and validation data
<p>Human development at the foot of the mountains faces sediment-laden flood hazards characterized by high-velocity, erosive flows carrying mud and debris, and when flood control infrastructure that protects communities fills with sediment, it loses capacity. The estimation and management of sediment-laden floods have proven challenging because cycles of wildfire, precipitation, and infrastructure sedimentation are still poorly understood. Efforts to model compound hazards such as post-fire floods are relatively new, and existing models do not consider the role of flood control infrastructure, such as debris retention basins and flood channels, in the development of post-fire floods. Here we present data sources and calibration methods to estimate sediment-laden flood hazards downstream of infrastructure on a catchment-by-catchment basis using the Post-Fire Flood Hazard Model (PF2HazMo), a stochastic modeling approach that utilizes continuous simulation to resolve the effects of antecedent conditions and system memory. Data sources provide parameter ranges needed for stochastic modeling, and several performance measures are considered for model calibration. With application to three catchments in Southern California, we show that PF2HazMo predicts the median of the simulated distribution of peak bulked flows within the 95% confidence interval of observed flows, with an order of magnitude range in bulked flow estimates depending on the performance measure used for calibration. Using infrastructure overtopping data from a post-fire wet season, we show that PF2HazMo accurately predicts the number of flood channel exceedances. Model applications to individual watersheds reveal whether existing infrastructure is undersized to contain present-day and future overtopping hazards based on current design standards.</p>
Data for the Article: Cross-validation of a semantic segmentation network for natural history collection specimens
<p>This deposit contains six datasets which were used for testing and validating a semantic segmentation network. The purpose was to evaluate the suitability of the segmentation network for use in the processing of images from Natural History Collections.</p>
AIoTes DS Validation Profile
<p>This dataset contains the demographic information of the AIoTes validation interviews participants</p>
Code to generate figures 3 and 4 of: "A comprehensive LFQ benchmark dataset to validate data analysis pipelines on modern day acquisition strategies in proteomics."
<p>Code to generate figures 3 and 4 of the manuscript titled "A comprehensive LFQ benchmark dataset to validate data analysis pipelines on modern day acquisition strategies in proteomics."</p> <p> </p>
Fig. 5 in Validity of Epigonus megalops (Perciformes: Epigonidae), Redescription of E. atherinoides, and First Record of E. draco from the Central South Pacific
Fig. 5. Position of uppermost margin of pectoral-fin base in two similar species. A: E. megalops, USNM 147374, paratype, 116.0 mm SL; B: E. ctenolepis, FUMT-P 1567, holotype, 98.0 mm SL.
Fig. 1 in Validity of Epigonus megalops (Perciformes: Epigonidae), Redescription of E. atherinoides, and First Record of E. draco from the Central South Pacific
Fig. 1. Epigonus megalops (A–B) and E. atherinoides (C–E). A: E. megalops, USNM 70255, holotype, 125.3 mm SL, Philippines; B: E. megalops, USNM 147374, paratype, 116.0 mm SL, Philippines; C: E. atherinoides, USNM 51601, holotype, 93.9 mm SL, Hawaiian Islands; D: E. atherinoides, CSIRO H 2603-01, 122.2 mm SL, Western Australia; E: E. atherinoides, MNHN 2014-0854, 101.0 mm SL, Society Islands.
Fig. 3 in Validity of Epigonus megalops (Perciformes: Epigonidae), Redescription of E. atherinoides, and First Record of E. draco from the Central South Pacific
Fig. 3. Distributional records of Epigonus megalops (open stars), E. atherinoides (open circles = previous studies; solid circles = present study), and E. draco (open triangles = previous studies; solid triangles = present study).
Fig. 2 in Validity of Epigonus megalops (Perciformes: Epigonidae), Redescription of E. atherinoides, and First Record of E. draco from the Central South Pacific
Fig. 2. Dorsal view of snout of Epigonus megalops, USNM 70255, holotype, 125.3 mm SL (arrows point to maxillary mustache-like processes).
Fig. 6 in The Validity of Helcogramma ishigakiensis (Aoyagi, 1954) and a Synopsis of Species of Helcogramma from the Ryukyu Islands, Southern Japan (Perciformes: Tripterygiidae)
Fig. 6. Mandibular sensory pore system of species of Helcogramma in the Ryukyu Islands. A, Helcogramma aquila (HMNH-P 9148, male, 34.4 mm SL); B, H. fuscipectoris (KAUM–I. 24444, male, 28.7 mm SL); C, H. inclinata (KAUM–I. 6522, male, 50.9 mm SL); D. H. ishigakiensis (KAUM–I. 17519, male, 50.0 mm SL); E, H. rhinoceros (KAUM–I. 32332, male, 26.9 mm SL); F, H. striata (KAUM–I. 30110, male, 37.1 mm SL). Scale bars 2 mm.
Fig. 3 in The Validity of Helcogramma ishigakiensis (Aoyagi, 1954) and a Synopsis of Species of Helcogramma from the Ryukyu Islands, Southern Japan (Perciformes: Tripterygiidae)
Fig. 3. Underwater photographs of Helcogramma ishigakiensis. A, male; B, female; C, female (left) and male (right); D, female (front) and male (back), north of Ho-Syuu, Onna, Okinawa-jima island, Ryukyu Islands, 3–7 m, 13 (A), 19 (C–D) May 2013. Photos by T. Katano.
Fig. 2 in The Validity of Helcogramma ishigakiensis (Aoyagi, 1954) and a Synopsis of Species of Helcogramma from the Ryukyu Islands, Southern Japan (Perciformes: Tripterygiidae)
Fig. 2. Color photographs of fresh and preserved specimens of Helcogramma ishigakiensis. A–B, KAUM–I. 40381, male, 43.3 mm SL, Yoron-jima island; C–D, KAUM–I. 17519, male, 50.0 mm SL, Amami-oshima island; E–F, KAUM–I. 17520, female, 51.9 mm SL, Amamioshima island; G, preserved specimen, same as A–B; H, preserved specimen, same as E–F.
Fig. 5 in The Validity of Helcogramma ishigakiensis (Aoyagi, 1954) and a Synopsis of Species of Helcogramma from the Ryukyu Islands, Southern Japan (Perciformes: Tripterygiidae)
Fig. 5. Color photographs of fresh (A, C–J) and preserved (B) specimens of Helcogramma in the Ryukyu Islands. Helcogramma aquila, A, HMNH-P 9144, male, 35.0 mm SL, B, HMNH-P 4409, female, 32.5 mm SL; H. fuscipectoris, C, KAUM–I. 63398, male, 22.6 mm SL, D, KAUM–I. 63399, female, 24.2 mm SL; H. inclinata, E, KAUM–I. 29669, male, 42.5 mm SL, F, KAUM–I. 30625, female, 49.2 mm SL; H. rhinoceros, G, KAUM–I. 51381, male, 27.2 mm SL; H, KAUM–I. 63467, female, 29.4 mm SL; H. striata, I, KAUM–I. 37748, male, 38.5 mm SL, J, KAUM–I. 29515, female, 33.5 mm SL.
Fig. 6 in The Australian Sinistral Flounder Arnoglossus aspilos praeteritus (Actinopterygii: Pleuronectiformes: Bothidae) Reassigned as a Valid Species of Engyprosopon
Fig. 6. Radiographs of caudal skeletons of Engyprosopon praeteritus (A, holotype, AMS IA. 4142, male, 57 mm SL; B, CSIRO A 1336, 69.0 mm SL) and Arnoglossus aspilos (C, HUMZ 185346, 96.5 mm SL). The hypural bones are split in A and B, and fused in C.
Fig. 5 in The Australian Sinistral Flounder Arnoglossus aspilos praeteritus (Actinopterygii: Pleuronectiformes: Bothidae) Reassigned as a Valid Species of Engyprosopon
Fig. 5. Lateral line scale on ocular side (A), CSIRO A 1334,73.2 mm SL and first gill arch (B), CSIRO A 1332, 73.1 mm SL of Engyprosopon praeteritus.
Fig. 4 in The Australian Sinistral Flounder Arnoglossus aspilos praeteritus (Actinopterygii: Pleuronectiformes: Bothidae) Reassigned as a Valid Species of Engyprosopon
Fig. 4. Relationships between body depth in SL and SL (A) and between interorbital width in head length and SL (B). Engyprosopon praeteritus: holotype (△), paratypes(▲) and present specimens (■); Arnoglossus aspilos (●).
Fig. 1 in The Australian Sinistral Flounder Arnoglossus aspilos praeteritus (Actinopterygii: Pleuronectiformes: Bothidae) Reassigned as a Valid Species of Engyprosopon
Fig. 1. Collection localities of type series and present specimens of Engyprosopon praeteritus. H, holotype; P, paratypes. Numerals refers to number of specimens.
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.