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Dataset results
90 results for “data retrieval”
Data Archive for: Hurricane Laura (2020): A Comparison of Drop Size Distribution Moments Using Ground and Radar Remote Sensing Retrieval Methods
<p>This archive corresponds to the data described in Brauer et al. (2021) to be published in <em>Journal of Geophysical Research: Atmospheres.</em> Please see the included readme.txt file for details about each data file.</p>
Data and code for the manuscript Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration
<p>Data and code for the manuscript <em>Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration</em> accepted for publication to<em> </em> <em>Earth and Space Science</em> in October 2021.</p> <p>The dataset contains 7 month of total losses (transmitted - received power levels) and retrieved water vapor density from a 4.87 km long full-duplex E-band commercial microwave link (CML) operating at 73.5 and 83.5 GHz in Prague, CZ. The CML was operated as a part of a mobile phone backhaul. Furthermore, observations of air temperature, and air relative humidity from sites close to the CML end nodes are provided. Finally, theoretical gaseous attenuation calculated from the air temperature and relative humidity is included as a part of the dataset.</p> <p>Data are stored in semicolon-delimited csv files. Time stamps are in UTC time in the format yyyy-mm-dd HH:MM:SS. All time series are regular and have 5-min temporal resolution. Metadata are stored in text files.</p> <p>The code is in a form of R Markdown files and html notebooks. Results presented in the manuscript Retrieving Water Vapor From an E-band Microwave Link With an Empirical Model Not Requiring In-situ Calibration and in its Supporting information are fully reproducible using this dataset.</p>
Gauge data used in 'An improved near-real-time precipitation retrieval for Brazil' by Pfreundschuh et al.
<p>The rain gauge measurements were compiled by the National Institute of Meteorology of Brazil 40 and consist of hourly gauge measurements covering the time range May 2000 until May 2020. They are used as reference data 'An improved near-real-time precipitation retrieval for Brazil' by Pfreundschuh et al. and published here in order to ensure reproducibility.</p>
PAReTT: a Python package for the Automated Retrieval and management of divergence time data from the TimeTree resource for downstream analyses (Dataset)
<p>Dataset for article by the same title submitted the the <em>Journal of Molecular Evolution</em>.</p>
Cross-spectra used in "Retrieval and precise phase-velocity estimation of Rayleigh waves by the spatial autocorrelation method between distributed acoustic sensing and seismometer data"
<p>Cross-spectra used in "Retrieval and precise phase-velocity estimation of Rayleigh waves by the spatial autocorrelation method between distributed acoustic sensing and seismometer data</p> <p>", by Shun Fukushima, Masanao Shinohara, Kiwamu Nishida, Akiko Takeo, Tomoaki Yamada, and Kiyoshi Yomogida </p> <p>For more information, please contact Shun Fukushima (s-fuku@eri.u-tokyo.ac.jp)</p>
data set for Design of architectural environment integration of cyber-physical systems based on image segmentation and retrieval technology
<p>This data set is used to implement the project Design of architectural environment integration of cyber-physical systems based on image segmentation and retrieval technology</p>
Spectra and retrieval data from CO and HCN observations of Jupiter with ALMA (project 2016.1.01235.S)
<p>Spectra and retrieval data from:</p> <p>Title: Evidence for auroral influence on Jupiter's nitrogen and oxygen chemistry revealed by ALMA<br> Authors: T. Cavalié, L. Rezac, R. Moreno, E. Lellouch, T. Fouchet, B. Benmahi, T. K. Greathouse,<br> J. A. Sinclair, V. Hue, P. Hartogh, M. Dobrijevic, N. Carrasco, Z. Perrin<br> Journal: Nature Astronomy<br> Year: 2023</p> <p>########################<br> # Description of files #<br> ########################</p> <p>CO_data/<br> latitudes_CO.dat: planetocentric latitudes of the 540 pointings from which the CO spectra have been extracted<br> spectrum_*.dat : CO spectra, one per pointing. Frequency in GHz and continuum-subtracted flux density in Jy/beam<br> profiles_*.dat : vertical profiles, one per pointing. Pressure in mbar, temperature in K (local average, see paper for details), and retrieved CO volume mixing ratio</p> <p>HCN_data/<br> latitudes_HCN.dat: planetocentric latitudes of the 557 pointings from which the HCN spectra have been extracted<br> spectrum_*.dat : HCN spectra, one per pointing. Frequency in GHz and continuum-subtracted flux density in Jy/beam<br> profiles_*.dat : vertical profiles, one per pointing. Pressure in mbar, temperature in K (local average, see paper for details), and retrieved HCN volume mixing ratio</p> <p> </p>
Reproduction package for "Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories"
<p>Reproduction package for "Revisiting the reproducibility of empirical software engineering studies based on data retrieved from development repositories", published in Information and Software Technology, Volume 164, December 2023. DOI: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.infsof.2023.107318" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.infsof.2023.107318</span></span></a></p>
Spectral data used in "Stratospheric-trace-gas-profile retrievals from balloon-borne limb imaging of mid-infrared emission spectra"
<p>The calibrated spectral data used in the trace gas retrievals by the Limb Imaging Fourier Transform Spectrometer Experiment (LIFE).</p>
Data from: Transmission line data of different fault instances retrieved through Phasor Measurement Unit (PMU)
<p>This study presents a dataset comprising time series data pertaining to different electrical grid scenarios, encompassing both fault-free instances and occurrences of short circuits. The dataset was meticulously created by simulating various fault scenarios using the ePMU DSA tools and Matlab Simulink. To capture these scenarios, a Phasor Measurement Unit (PMU) was deployed on a transmission line simulation model. Given the impracticality and potential risks associated with generating actual faults in a real power grid, this approach of simulating faulty scenarios through advanced tools has proven to be a reliable and effective methodology in the field of electrical grid studies. The resulting dataset offers valuable insights into power grid behavior during both normal and faulted conditions, thereby serving as a valuable resource for researchers and practitioners in the domain of power systems and fault analysis.</p>
Data from: Clathrin-independent endocytic retrieval of SV proteins mediated by the clathrin adaptor AP-2 at mammalian central synapses
Open the record for dataset details and reuse information.
Data from: L-band InSAR SWE retrievals over Northern Colorado
Open the record for dataset details and reuse information.
Data retrieval from archival renal biopsies using nonlinear microscopy
Open the record for dataset details and reuse information.
Data from: Transmission line data of different fault instances retrieved through Phasor Measurement Unit (PMU)
Open the record for dataset details and reuse information.
Data support to Characteristics of persistent heavy fog events retrieved by microwave radiometer profiler during 2010–2013 in northern China
<p>The dataset include the observation data from microwave radiometer, tethered balloon and the surface.</p>
Evaluating Elements of Web-based Data Enrichment for Pseudo-Relevance Feedback Retrieval
<p>This data archive accompanies our work, in which we analyze a pseudo-relevance retrieval method that is based on the results of web search engines. By enriching topics with text data from web search engine result pages and linked contents, we train topic-specific and cost-efficient classifiers that can be used to search test collections for relevant documents. Building up on attempts that were initially made at TREC Common Core 2018 by Grossman and Cormack, we address the questions of system performance over time considering different search engines, queries and test collections. Our experimental results show how and to which extent the considered components affect the retrieval performance. Overall, the analyzed method is robust in terms of average retrieval performance and a promising way to use web content for the data enrichment of relevance feedback methods.</p>
Data supporting the article "Replication of extinction retrieval prediction by prefrontal reactivations and non-replication of L-DOPA effects on retrieval and reactivations in males"
<p>These datasets contain sAA, sCORT, US expectancy, questionnaire and rating raw data generated in this replication study. Furthermore, the processed MRI data (vmPFC reactivations) and derived SCR data are available. The custom-made analysis script for scoring SCR can be run on Matlab 2015b.</p>
Data For: Retrieval Augmented Docking using Hierarchical Navigable Small Worlds
<p>These are the DOCK scores for the DUDE-Z "goldilocks" molecules docked to each of the 43 DUDE-Z proteins used in the paper: Retrieval Augmented Docking using Hierarchical Navigable Small Worlds.</p> <p>The data is saved as a pickle of a python dictionary. The keys are the ZINC IDs of the molecules, and the values are lists where the first entry is the corresponding SMILES string, and the second is a dictionary of DOCK scores for each DUDE-Z receptor. If a receptor does not appear in a particularly molecule's dictionary, it means that the molecule failed to dock to the receptor.</p> <p>{</p> <p>zinc_id1: [SMILES, {receptor1:score, receptor2:score,...} ],</p> <p>zinc_id2: [SMILES, {receptor1:score, receptor2:score,...} ],</p> <p>....</p> <p>}</p>
Retrieving Data Constraint Implementations Using Fine-Grained Code Patterns
<p>Business rules are an important part of the requirements of software systems that are meant to support an organization. These rules describe the operations, definitions, and constraints that apply to the organization. Within the software system, business rules are often translated into constraints on the values that are required or allowed for data, called data constraints. Business rules are subject to frequent changes, which in turn require changes to the corresponding data constraints in the software. The ability to efficiently and precisely identify where data constraints are implemented in the source code is essential for performing such necessary changes.</p> <p>In this paper, we introduce Lasso, the first technique that automatically retrieves the method and line of code where a given data constraint is enforced. Lasso is based on traceability link recovery approaches and leverages results from recent research that identified line-of-code level implementation patterns for data constraints. We implement three versions of Lasso that can retrieve data constraint implementations when they are implemented with any one of 13 frequently occurring patterns. We evaluate the three versions on a set of 299 data constraints from 15 real-world Java systems, and find that they improve method-level link recovery by 30%, 70%, and 163%, in terms of true positives within the first 10 results, compared to their text-retrieval-based baseline. More importantly, the Lasso variants correctly identify the line of code implementing the constraint inside the methods for 68% of the 299 constraints.</p>
Martian atmospheric spectral end-members retrieval from ExoMars Thermal Infrared TIRVIM data
<p>Here we investigated new thermal infrared data from the TIRVIM instrument of the ExoMars TGO with the main goal of carefully identifying Martian atmospheric dust and water ice clouds components. A methodology based on principal component and target transformation factor analysis techniques has been applied. Based on our results, this methodology can correctly recover both atmospheric dust and water ice aerosols spectral shapes and their abundances in the Martian atmosphere.</p> <p>The processed TIRVIM data and retrievals used in our work are available here. <br> <br> <strong><em>File uploaded:</em></strong></p> <p><strong>Alemanno_2022_Martian_atmospheric_spectral_end-members_retrieval_from_ExoMars_Thermal_Infrared_TIRVIM_data.zip </strong></p> <p>containing:</p> <ul> <li><strong>Data Set S1</strong> - Alemanno_2022_Martian_atmospheric_spectral_end-members_retrieval_from_ExoMars_Thermal_Infrared_TIRVIM_data</li> <li><strong>Text S1</strong> - Alemanno_2022_Martian_atmospheric_spectral_end-members_retrieval_from_ExoMars_Thermal_Infrared_TIRVIM_data.README</li> <li><strong>Data Set S2</strong> - PCA_components</li> <li><strong>Data Set S3</strong> - PCA_eigenvalues_variance</li> <li><strong>Data Set S4</strong> - TES_endmembers_orginal_target-transform</li> </ul> <p><strong>Description:</strong></p> <p><strong>Data Set S1</strong> – Martian atmospheric spectral end-members retrieved from ExoMars Thermal Infrared TIRVIM data</p> <p><strong>Text S1</strong> – description of the data contained in Dataset S1</p> <p><strong>Data Set S2</strong> – PCA_components retrieved from TIRVIM data</p> <p><strong>Data Set S3</strong> – PCA eigenvalues variance for each retrieved component of the dataset S2</p> <p><strong>Data Set S4</strong> – smoothed TES endmembers target-transformed</p> <p><strong>If you use this data set in your own work, please cite this DOI:</strong></p> <p><strong>10.5281/zenodo.7032738</strong></p> <p><strong>Please also cite this work:</strong></p> <p><strong>Alemanno G. et al. (2022), Spectral Atmospheric End-Members Retrieval from ExoMars Thermal InfraRed (TIRVIM) Data. 53rd Lunar and Planetary Science Conference, held 7-11 March, 2022 at The Woodlands, Texas. LPI Contribution No. 2678, 2022, id.1885.</strong></p> <p><strong>Alemanno G. et al. (2022), Martian atmospheric spectral end-members retrieval from ExoMars Thermal Infrared (TIRVIM) data, JGR Planets, doi: 10.1029/2022JE007429</strong></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.