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.
625
datasets available to search
ShareScore release 0.9.0
Dataset results
625 results for “Anomaly”
Core Origin of Seismic Velocity Anomalies at the Earth's Core-Mantle Boundary
<p>Datasets supporting the findings in the article "Core Origin of Seismic Velocity Anomalies at the Earth's Core-Mantle Boundary"</p>
Arctic water vapor anomalies based on monthly CESM experiment
<p>This dataset shows the internal anomalies of Arctic water vapor and other related variables by using the monthly data from historical/RCP8.5 experiments based on the Community Earth System Model (CESM), which has 40-member runs during 1920-2005/2006-2050. To characterize internal variability, we remove the ensemble mean (radiative forced component) and focus on the residual (internal) variability. Then we use a 10-year low-pass Lanczos filter to extract decadal variability, and the difference between the internal variability and its decadal component is treated as interannual compoent.</p>
Data and code for: "Sea level rise from West Antarctic mass loss significantly modified by large snowfall anomalies"
<p>Data and code required to reproduce results in paper: "Sea level rise from West Antarctic mass loss significantly modified by large snowfall anomalies"</p>
A dataset of Korean weather with anomaly score from 2010 to 2020
<p>This dataset describes the weather data of 64 cities in Korea for each day and the weather anomaly scores for each day from 2010 to 2020. The dataset includes city name, dates, temperature, humidity, vapor pressure, dew point temperature, sea level pressure, ground pressure, ground temperature, LOF anomaly score, IF anomaly score, COPOD anomaly score, ABOD anomaly score, HBOS anomaly score, SOD anomaly score and ROD anomaly score. In the dataset, the weather data and the weather anomaly score of each day for 64 Korean cities from 2010 to 2020 are stroed into 64 csv files. Each csv file in the dataset represents each city. The 64 cities include Seoul, the capital of Korea, and the 6 metropolitan cities of Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. In addition, the weather data and weather anomaly scores for 19 coastal cities and 4 islands in Korea are included in the dataset.</p>
Gravity Anomalies and Implications for Shallow Mantle Processes of the Western Cocos-Nazca Spreading Center
<p>This folder contains six grid files and one Matlab code from Zheng et al. (2022). </p> <p><br> (1)105W95W1S5N_mba.grd -- mantle Bougour anomaly calculated in this study (displayed in Fig. 1c).</p> <p>(2)105W95W1S5N_mba_ship_topo_global_FAA.grd -- Calculated mantle Bougour anomaly using mutltibeam bathymetry and global free air anomaly data (displayed in Fig. S1b).</p> <p>(3)105W95W1S5N_mba_global_topo_global_FAA.grd -- Calculated mantle Bougour anomaly using global bathymetry and global free air anomaly data (displayed in Fig. S1c).</p> <p>(4)105W95W1S5N_thermal_1k.grd -- thermal effect caused by plate cooling (displayed in Fig. S2b).</p> <p>(5)105W95W1S5N_rmba_1k.grd -- residual mantle Bougour anomaly (displayed in Fig. 2a).</p> <p>(6)105W95W1S5N_crust_1k.grd -- relative crustal thickness (displayed in Fig. 2b).</p> <p>(7)fig4_filtered_model.m -- Matlab code for producing filtered model in Fig. 4 </p>
Replication package for PHP code smells in web apps: evolution, survival and anomalies
<p>Replication package (dataset and programs/scripts) and extra documents for article:</p> <p><strong>PHP code smells in web apps: evolution, survival and anomalies</strong></p> <p>Folder zips RQ1-5 - Extra graphics for all applications studied. In the article, due to lack of space, we only present graphics for two applications.</p> <p>Data folder zip - data used in the study and suitable for replication. The folder is divided in subfolders and there is an "explanation.txt".</p> <p>scripts.zip - PHP scripts used to pre-process data</p> <p>R scripts.zip - R scripts used to analyze and graphics</p>
A dataset of Korean weather with anomaly score from 2010 to 2020
<p>This dataset describes the weather data of 64 cities in Korea for each day and the weather anomaly scores for each day from 2010 to 2020. The dataset includes city name, dates, temperature, humidity, vapor pressure, dew point temperature, sea level pressure, ground pressure, ground temperature, LOF anomaly score, IF anomaly score, COPOD anomaly score, ABOD anomaly score, HBOS anomaly score, SOD anomaly score and ROD anomaly score. In the dataset, the weather data and the weather anomaly score of each day for 64 Korean cities from 2010 to 2020 are stored into 64 csv files. Each csv file in the dataset represents each city. The 64 cities include Seoul, the capital of Korea, and the 6 metropolitan cities of Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. In addition, the weather data and weather anomaly scores for 19 coastal cities and 4 islands in Korea are included in the dataset.</p>
Data for "Ultra-low-velocity anomaly inside the Pacific Slab near the 410-km discontinuity"
<p>This folder contains the P- and S-wave displacement records after removing the instrument responses.</p> <p>./20091010_RR_Pwave : P-wave data for the reference region of event 20091010.<br> ./20091010_SS1_Pwave : P-wave data for the SS1 region of event 20091010.<br> ./20091010_SS2_Pwave : P-wave data for the SS2 region of event 20091010.<br> ./20090407_Pwave : P-wave data of event 20090407.<br> ./20110804_Pwave : P-wave data of event 20110804.<br> ./20091010_Swave : S-wave data of event 20091010.</p>
Synthetic Aperture Anomaly Imaging
<p><strong>Abstract: </strong>Previous research has shown that in the presence of foliage occlusion, anomaly detection performs significantly better in integral images resulting from synthetic aperture imaging compared to applying it to conventional aerial images. In this article, we hypothesize and demonstrate that integrating detected anomalies is even more effective than detecting anomalies in integrals. This results in enhanced occlusion removal, outlier suppression, and higher chances of visually as well as computationally detecting targets that are otherwise occluded. Our hypothesis was validated through both: simulations and field experiments. We also present a real-time application that makes our findings practically available for blue-light organizations and others using commercial drone platforms. It is designed to address use-cases that suffer from strong occlusion caused by vegetation, such as search and rescue, wildlife observation, early wildfire detection, and surveillance.</p>
Mantle xenoliths used in "High P-T sound velocities of amphiboles: Implications for low-velocity anomalies in metasomatized upper mantle"
<p>Mineral proportions in hydrous-mineral-bearing mantle xenoliths collected worldwide and their calculated sound velocities in this study. </p>
20th Century Antarctic sea ice extent anomaly reconstruction by sector
<p>Monthly Antarctic sea ice extent anomaly reconstruction in total and by sector ("Total", "King Haakon VII", "Ross Sea", "East Antarctica", "Weddell Sea", "Bellingshausen Amundsen Sea") for the 20th Century. We provide an ensemble of 2500 reconstructions. </p> <p>For each sector we provide one CSV file. The rows in these data sets correspond the reconstructed month, e.g. reconstructions for January 1950 are found in row "t1950_1" and the columns correspond to the 2500 reconstructions. The numbers of the reconstructions correspond to one another across sectors, such that the 1st "Total" reconstruction is the sum of the 1st reconstruction in all sectors.</p>
Artifacts for "FLAG: Finding Line Anomalies (in code) with Generative AI"
<p>Artifacts for our work used to detect defects in code using LLM consistency checking. Please read README.md file in repository to start.</p>
Theoretical synthesis datasets of submarine cable magnetic anomalies.
<p>Theoretical synthesis datasets of submarine cable magnetic anomalies, including training, validation and testing, for end-to-end deep learning. A total of 140000 samples and its coresponding labels.</p>
Horizontal Magnetic Anomaly Accompanying with the Co-seismic EQL of M7.3 Fukushima Earthquake of 16 March 2022: Phenomenon and Mechanism
<p>The file named 'EQL video & camera scene on google earth.rar' contains the video of the EQL (16 March 2022 & 7 April 2011) and the picture of the moment of the EQLs and the corresponding Google Earth scenes. The file named 'geological data.rar' contains the geological map of Sendai city and surrounding zone. The file named 'original geomagnetic data(2011).rar' contains the original geomagnetic data of three stations (i.e., KAK, KNY and MMB) on 7 April 2011. The file named 'original geomagnetic data(2022).rar' contains the original geomagnetic data of three stations (i.e., KAK, KNY and MMB) on 16 March 2022. The file named 'The processed data and the corresponding matlab program.rar' contains the processed geomagnetic data of the three stations and the matlab program for visualization.</p>
Global reconstructions of the GRACE-like terrestrial water storage anomalies
<p>These datasets provide global (excluding Antarctica) reconstructions of the GRACE-like terrestrial water storage anomalies (TWSA) from April 2002 to July 2021 with a spatial resolution of 1 degree.</p> <p>These reconstructed TWSAs were generated by a two-step linear model. The driving data include the ERA5-Land model-extracted precipitation and air temperature data, as well as the Noah model-simulated TWSA. The training period is from April 2002 to April 2013, and the testing period is from May 2013 to July 2021.</p> <p>‘REC-JPL-M’ means the reconstructed TWSA based on the JPL mascon solution; ‘REC-JPL-SH’ means the reconstructed TWSA based on the JPL spherical harmonic solution.</p>
Light calcium isotope anomaly observed in continental basaltic lavas: a mixed signal of recycled carbonate and fractionation during melting
<p>Table 1 and Supplementary Tables S1 to S7 which support for the manuscript 'Light calcium isotope anomaly observed in continental basaltic lavas: a mixed signal of recycled carbonate and fractionation during melting'.</p>
Analysis of Anomaly Detection for Artificial Intelligence of Things: A Systematic Literature Mapping
<p>This data set contains the characteristics extracted from each of the works selected from the literary review carried out following the PRISMA methodology.</p>
Anomaly Detection dataset for the fuselage of an aircraft
<p>If you use the dataset, please cite:</p> <p><em>Siddhant Shete, Dennis Mronga</em></p> <p><strong>"Adaptive Online Anomaly Detection using Transfer Learning"</strong></p> <p>About the dataset: The dataset is basically used for anomaly detection in the fuselage of an aircraft manufacturing company. We captured the data on the mockup of the fuselage with several iterations at different distances away from the mockup. The dataset is basically the scans of mockup from top to bottom with and without anomalies. The dataset has been segregated into two panels.</p> <p>Contents of <em><strong> AircraftFuselageMockupDataset.zip </strong></em></p> <ol> <li>Nomal_panel1 </li> <li>Nomal_panel2</li> <li>Anomaly_panel1</li> <li>Anomaly_panel2</li> </ol> <p>Every folder has data at 3 distances 15cm, 25cm, 35cm.</p> <p> </p> <p><em>This dataset is provided by the Robotics Innivation Center, DFKI GmbH.</em></p> <p><em>The grant was provided by Federal Ministry for Economic Affairs and Climate Action </em></p> <p><em>Grant number: 20W1922F</em></p>
Anomaly Detection dataset for the ISS Panel mockup
<p>If you use the dataset, please cite:</p> <p><em>Siddhant Shete, Dennis Mronga</em></p> <p><strong>"Adaptive Online Anomaly Detection using Transfer Learning"</strong></p> <p>About the dataset: The dataset is basically used for anomaly detection in the ISS(International Space Station) panel. This dataset was captured from the mockup used for experiments at the institute. The panel replicates the curcuit and control boards at ISS. The dataset is segregated in two parts Normal data and Anomalous data.</p> <p>Contents of <em><strong> ISSPanelDataset.zip </strong></em></p> <ol> <li>Nomal</li> <li>Anomaly</li> </ol> <p>The Anomaly folder has data with different scenarios where the led lights are on, the fan panel cover is missing or some parts are missaligned.</p> <p> </p> <p><em>This dataset is provided by the Robotics Innivation Center, DFKI GmbH.</em></p> <p><em>The grant was provided by Federal Ministry for Economic Affairs and Climate Action </em></p> <p><em>Grant number: 20W1922F</em></p>
Artifacts for "FLAG: Finding Line Anomalies (in code) with Generative AI"
<p>Artifacts for our work used to detect defects in code using Large Language Models. Please read README.md file in repository to start.</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.