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.
867
datasets available to search
ShareScore release 0.9.0
Dataset results
867 results for “repositories”
GitHub repositories for Enterprise Resource Planning (ERP) systems
<p>This dataset contains the main data and results of an analysis of open source ERPs (Enterprise Resource Planning) found in GitHub repositories.</p> <ul> <li><em>erp-repositories-ALL-short-filtered-v2.csv</em> is the main dataset file containing information collected for repositories using the GitHub Search API (11,500 relevant repositories after applying filtering criteria). It is also the main file that can be used for replication purposes of the reserch work.</li> <li>The remaining files contain results from the analysis on the dataset.</li> </ul> <p>The relevant paper from the 2024 International Conference on Software and Systems Reuse (ICSR) can be used for citing this work: The current status of open source ERP systems: a GitHub analysis, by Georgia M. Kapitsaki and Maria Papoutsoglou.</p>
Data to accompany the outlier-waveform-detection Github repository (internal globus pallidus, GPi)
<p>This repository contains data based on neuronal recordings from two monkeys (G and I, in the pre- and post-MPTP states) that serve as input to the code provided at <a href="https://github.com/turner-lab-pitt/outlier-waveform-detection">https://github.com/turner-lab-pitt/outlier-waveform-detection</a>. Text files located within that Github repository provide detailed instructions on how these data may be used with that code. As described in those text files, extra data are provided for Monkey G, in the pre-MPTP state.</p> <p>The data-description.txt file provides detailed information regarding the contents of each zipped tar archive. Briefly, the most important components of the files are the "snips" (individual spike waveforms) from the two monkeys and MPTP states, as extracted for each of a series of single sorted units from the internal globus pallidus (GPi). The additional G-Pre data provides examples of the high-pass filtered voltage signals from which these snips were extracted. All data are stored in the Matlab .mat format.</p> <p>All zipped files can be decompressed with 7-zip: <a href="https://www.7-zip.org/" target="_blank" rel="noopener">https://www.7-zip.org/</a></p> <p>These data and the associated Github code were used for analyses reported in an in-preparation manuscript (Kase et al., "Movement-related activity in the internal globus pallidus of the parkinsonian macaque"), and also with a preprint that is currently under review:</p> <div> <div>Detecting rhythmic spiking through the power spectra of point process model residuals</div> </div> <div>Karin M. Cox, Daisuke Kase, Taieb Znati, Robert S. Turner</div> <div>bioRxiv 2023.09.08.556120; doi: <a href="https://doi.org/10.1101/2023.09.08.556120" target="_blank" rel="noopener">https://doi.org/10.1101/2023.09.08.556120</a></div> <div> </div> <p>This research was funded in part by Aligning Science Across Parkinson's [ASAP-020519] through the Michael J. Fox Foundation for Parkinson's Research (MJFF). For the purpose of open access, the authors have applied a Creative Commons Attribution 4.0 International (CC BY) public copyright license to this dataset. </p>
Repository 2 of 2 of the Level 0 (raw FITS) images from the DMI Mauna Loa Earthshine telescope experiment (2010-2012)
<h2>Raw data upload</h2> <p>These are tar files of the raw data obtained with the earthshine refractor conceived, designed and built by Danish Meteorological Institute and Lunds Observatory and operated on Mauna Loa at the NOAA observatory during 2011-2012.</p> <p>The present doi relates to one of two - each one holds roughly 50Gb tar file. Get all for the complete dataset. The other doi is: 10.5281/zenodo.11442378</p> <p>The data are in the form of FITS files. There are data for 5 different photometric filters - Johnson B and V and then 3 red or nIR filters - IRCUT, VE1 and VE2. Some frames are without filters.</p> <p>Examples:</p> <p>2455945.1760145MOON_B_AIR.fits.gz - image of the Moon through the B filter</p> <p>2455945.0413946DARK_DARK.fits.gz - a DARK frame image taken with same exposure time as the adjacent MOON image. <br>A DARK is typically taken before and after all MOON images.</p> <p>The file-naming strategy for the file inside the archive files is simple - names start with the (fractional) Julian day of the observation, followed by target name and two indicators of the filters or other light-path devices that were used, e.g.: _VE1_AIR indicates the VE1 colour filter with just 'air' (ie nothing) in the second option. The second option may include names of knife-edge devices or neutral density filters that could be inserted.</p> <p>There are also some FLAT images taken on inside of dome or of the sky or of the Hohlraum source.</p> <p>The MOON images may well be 100-image 3D-cubes taken within a minute or two.</p> <p>Future upgrades (in new dois, but in this Community) will include dark-frame subtracted, aligned and averaged images (Level 1). A Level 2 may include actual model fits of the full lunar disks, in which terrestrial albedo is a model-parameter.</p> <p>The file called "index_justJD.csv" lists which Julian days are present in which archive file. Note that some days are spread over several tar files.</p> <p>The images were acquired with the remotely-operated telescope by Peter Thejll, Hans Gleinser, Chris Flynn, as well as Henriette Schwarz.</p> <p>Notes updated May 3 2024.</p> <p>Peter Thejll</p> <p>write pth@dmi.dk for queries</p>
FIGURE 119 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 119. Tropidolaemus subannulatus (juvenile male) (Sorsogon Prov., Luzon Id.) (KU uncat.; field no. RMB 22673). Photo © RMB.
FIGURE 109 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 109. Trimeresurus cf. flavomaculatus (hunting frogs) (Camiguin Norte Prov., Babuyan Ids.) (individual not collected). Photo © RMB.
FIGURE 66 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 66. Rhabdophis auriculatus auriculatus (Agusan del Norte Prov., Mindanao Id.) (KU 334441). Photo © RMB.
FIGURE 11 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 11. Acrochordus granulatus (blotched) (locality unknown, Philippine Ids.) (KU 327188). Photo © CDS.
FIGURE 8 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 8. Malayopython reticulatus (Sorsogon Prov., Luzon Id.) (KU uncat.; field no. RMB 23519). Photo © JBF/RMB.
FIGURE 39 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 39. Coelognathus erythrurus psephenourus (Sorsogon Prov., Luzon Id.) (KU uncat.; field no. RMB 23101). Photo © RMB.
FIGURE 53 in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
FIGURE 53. Oligodon maculatus (juvenile) (Zamboanga City Prov., Mindanao Id.) (KU 315172]). Photo © RMB.
Repository 1 of 2 of the Level 0 (raw FITS) images from the DMI Mauna Loa Earthshine telescope experiment (2010-2012)
<h2>Raw data upload</h2> <p>These are tar files of the raw data obtained with the earthshine refractor conceived, designed and built by Danish Meteorological Institute and Lunds Observatory and operated on Mauna Loa at the NOAA observatory during 2011-2012.</p> <p>The present doi relates to one of two - each one holds roughly 50Gb tar file. Get all for the complete dataset. The other doi is: 10.5281/zenodo.11500335</p> <p>The data are in the form of FITS files. There are data for 5 different photometric filters - Johnson B and V and then 3 red or nIR filters - IRCUT, VE1 and VE2. Some frames are without filters.</p> <p>Examples:</p> <p>2455945.1760145MOON_B_AIR.fits.gz - image of the Moon through the B filter</p> <p>2455945.0413946DARK_DARK.fits.gz - a DARK frame image taken with same exposure time as the adjacent MOON image. <br>A DARK is typically taken before and after all MOON images.</p> <p>The file-naming strategy for the file inside the archive files is simple - names start with the (fractional) Julian day of the observation, followed by target name and two indicators of the filters or other light-path devices that were used, e.g.: _VE1_AIR indicates the VE1 colour filter with just 'air' (ie nothing) in the second option. The second option may include names of knife-edge devices or neutral density filters that could be inserted.</p> <p>There are also some FLAT images taken on inside of dome or of the sky or of the Hohlraum source.</p> <p>The MOON images may well be 100-image 3D-cubes taken within a minute or two.</p> <p>Future upgrades (in new dois, but in this Community) will include dark-frame subtracted, aligned and averaged images (Level 1). A Level 2 may include actual model fits of the full lunar disks, in which terrestrial albedo is a model-parameter.</p> <p>The file called "index_justJD.csv" lists which Julian days are present in which archive file. Note that some days are spread over several tar files.</p> <p>The images were acquired with the remotely-operated telescope by Peter Thejll, Hans Gleinser, Chris Flynn, as well as Henriette Schwarz.</p> <p>Notes updated May 3 2024.</p> <p>Peter Thejll</p> <p>write pth@dmi.dk for queries</p>
Future-ready Nordic homes: Responding to the Changing Climate with Free-running Buildings; Digital Repository of Obtained Results
<p>The figures provided here show complete results of the parametric building performance simulation for each studied location, which was a part of the Master thesis in Energy-efficient and Environmental Building Design (Faculty of Engineering, Lund University, Sweden) by Marko Ljubas.</p> <p>The simulations were performed using software IDA ICE 4.8 by EQUA.</p> <p>The weather files were generated using software Meteonorm 8.2 by Meteotest.</p>
Data & code repository for the article "A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes"
<p>This repository contains the relevant data and code supporting the study "A network toxicology approach for mechanistic modelling of nanomaterial hazard and adverse outcomes". </p> <p>In detail the following data sources have been included:</p> <ul> <li>the relevant code and supporting data (code_to_upload.zip and supporting_data.zip);</li> <li>supplementary materials of the paper, including: <ul> <li>individual enrichment results of the 93 exposures to the 31 ENMs (enrichments_results.zip);</li> <li>comparison between the mechanism of action retrieved from differentially expressed genes and network modelling (network_comparison_results.zip);</li> <li>overrepresented network edges in categories of networks (overrepresented_structures.zip)</li> </ul> </li> </ul>
Saccostrea glomerata (Sydney Rock Oyster) - Meta Analysis Dataset Repository
<h1>Saccostrea glomerata (Sydney Rock Oyster) - Meta Analysis Dataset Repository:</h1> <h2>Dataset used to do 8 separate meta-analyses on the following topics for <em>Saccostrea glomerata</em> (Sydney Rock Oyster):</h2> <p>1. Ocean acidification and size</p> <p>2. Ocean acidification and mortality</p> <p>3. Ocean warming and size</p> <p>4. Ocean warming and mortality</p> <p>5. Transgenerational exposure to ocean acidification and size</p> <p>6. Transgenerational exposure to ocean acidification and mortality</p> <p>7. Transgenerational exposure to ocean warming effect and size</p> <p>8. Transgenerational exposure to ocean warming and mortality</p> <h3><strong>Dataset contains:</strong></h3> <ul> <li>Original code and all associated data files in order to reproduce the work within the "Code and Formatted Data" Folder.</li> <li>Datasheets containing the raw data extracted from the papers identified during the literature searches </li> </ul> <h3>Description of the data and file structure</h3> <ul> <li>R-Markdown file contains the original code required to reproduce the results outlined in this paper</li> <li>All datasheets appended with "_Formatted_For_Effect_Sizes" were used to generate the effect sizes required for the meta-analysis</li> <li>All datasheets appended with "_Extracted_Raw_Data" are the raw data extracted from the papers identified during the literature searches</li> </ul> <h3><strong>Abbreviations</strong></h3> <ul> <li>OA - Ocean Acidification</li> <li>Temp - Temperature</li> <li>Transgen - Transgenerational Exposure</li> <li>Mort - Mortality</li> </ul> <h2>Abstract</h2> <div>Global oceans are warming and acidifying because of increasing greenhouse gas emissions which are anticipated to have cascading impacts on marine ecosystems and organisms, especially those essential for biodiversity and food security. Despite this concern, there remains some scepticism about the reproducibility and reliability of research done to predict the future climate change impacts on marine organisms. Here we present meta-analyses of over two decades of research on the climate change impacts on an ecologically and economically valuable Sydney rock oyster, <em>Saccostrea glomerata</em>. We confirm with high confidence that ocean acidification has a significant impact on mortality and size of <em>S. glomerata,</em> that ocean warming has a significant impact on mortality, but not size, and transgenerational exposure has positive benefits to offspring. These meta-analyses reveal impacts of climate change on an ecologically and economically significant oyster species and recommends solutions for experimental designs to ensure sustainability of this iconic oyster. </div>
MAPS 37A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 37A–D. Geographic range maps for Philippine records of (A) Tropidonophis cf. negrosensis; (B) Tropidonophis dendrophiops; (C) Tropidonophis negrosensis; (D) Xenopeltis unicolor.
MAPS 35A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 35A–D. Geographic range maps for Philippine records of (A) Sibynophis bivittatus; (B) Sibynophis geminatus geminatus; (C) Stegonotus muelleri; (D) Trimeresurus flavomaculatus.
MAPS 36A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 36A–D. Geographic range maps for Philippine records of (A) Trimeresurus mcgregori; (B) Trimeresurus schultzei; (C) Tropidolaemus philippensis; (D) Tropidolaemus subannulatus.
MAPS 34A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 34A–D. Geographic range maps for Philippine records of (A) Rhabdophis barbouri; (B) Rhabdophis chrysargos; (C) Rhabdophis lineatus; (D) Rhabdophis spilogaster.
MAPS 33A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 33A–D. Geographic range maps for Philippine records of (A) Ramphotyphlops olivaceus; (B) Ramphotyphlops suluensis; (C) Rhabdophis auriculatus auriculatus; (D) Rhabdophis auriculatus myersi.
MAPS 25A–D in Synopsis of the Snakes of the Philippines A Synthesis of Data from Biodiversity Repositories, Field Studies, and the Literature
MAPS 25A–D. Geographic range maps for Philippine records of (A) Malayotyphlops hypogius; (B) Malayotyphlops luzonensis; (C) Malayotyphlops ruber; (D) Malayotyphlops ruficaudus.
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.