Find research datasets worth reusing

Data output from Projecting future climate change impacts on the distribution of pelagic squid in the Southern Ocean

<p>Data output from Projecting future climate change impacts on the distribution of pelagic squid in the Southern Ocean:<br>Rasters, R models and scripts</p>

Dataset and Model for Data Science Projects

<p>This zenodo is for the data science projects hosted in this GitHub repository: https://github.com/oathaha/data-science-portfolio/tree/main</p>

opengpl-3.0-or-laterSep 2024View details →

Codes and data upload for Mesocircuit Model project

<h3>Information</h3> <p>This resource contains source codes and data required to produce the figures from:<br>Senk, J., Hagen, E., van Albada, S. J., & Diesmann, M. (2024). Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space. <em>arXiv preprint arXiv:1805.10235v3<br><br></em>For only source codes, see:</p> <p>Senk, J., & Hagen, E. (2024). Mesocircuit Model (v1.0.0). Zenodo. <a href="https://doi.org/10.5281/zenodo.13798936" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13798936</a></p> <div> <h3>Instructions</h3> To use this resource, download the mesocircuit-model-1.0.0.tar.gz file. Then, extract the contents of the archive and run the following command in the extracted directory:<br> <div> </div> <div>$ # unzip the archive</div> <div>$ tar -xzf mesocircuit-model-1.0.0.tar.gz</div> <br> <div>$ # create and activate the conda environment</div> <div>$ cd mesocircuit-model</div> <div>$ conda env create -f environment.yml</div> <div>$ conda activate mesocircuit</div> <br> <div>$ # run the figure-generation scripts</div> <div>$ cd scripts</div> <div>$ python ms_figures_simulations.py</div> <div>$ python run_mesocircuit_lfps.py</div> <div> </div> <div>$ # deactivate environment</div> <div>$ conda deactivate </div> </div> <div> </div> <div>Installers for conda may be obtained e.g., from https://github.com/conda-forge/miniforge. <br> <div>The figures produced by ms_figures_simulations.py will be saved in the `ms_figures` directory.</div> <div>The figures produced by run_mesocircuit_lfps.py will be saved in mesocircuit_data/mesocircuit_MAMV1/dd1dcbd4034fbd4f689fbdd2ff7abb3b/lfp/figures.</div> </div>

THEIA-XR: the project

<p>Introducing you the THEIA-XR project - all to make the invisible visible for operators of off-highway heavy duty machines.</p>

Augmented Spaces and Maps, research project 2015–2019

<div> <p>"Augmented Space” (2015-2019) is a research project initiated by Dr. Christine Schranz which brings together both theoretical and and practical parts as a basic introduction to the field of digital cartographies. Complementary to the book publication “Augmented Spaces and Maps. Das Design von kartenbasierten Interfaces”, the AR application offers a historical perspective on the Campus of the Arts (formerly the site of the Basel bonded warehouse) and combines this view with a contemporary critique of the practice of art-related bonded warehouses. The project was carried at the FHNW Academy of Arts and Design in Basel, with the support from the Swiss National Science Foundation (SNSF).</p> <p>Principal Investigator, Book Editor: Dr. Christine Schranz</p> <p>Video Production: Maria Smigielska</p> </div>

Collembola morphospecies in sub project 7 in KiLi project

<p>List of morphospecies of Collembola, identified by Dr. Jörg Salamon.</p> <p>Assemblages of springtails were sampled with pitfall traps. Ten pitfall traps were evenly spaced along two 50 m transects, with a distance of 10 m between individual traps and 20 m between transects. Pitfall traps were filled with 100-200 ml solution of equal parts of ethylenglycol and water with a drop of liquid soap to break the surface tension. The traps were placed on the sampling sites in June 2012 and collected after seven days. As the number of individuals collected in ten traps was very high and all individuals could not be analyzed in time, for the present analysis, we processed only three traps from each study site. Ground-dwelling beetles were sorted to morphospecies level, and where possible, to species.</p> <p>The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.</p>

EGP Mitochondrial Genome Analysis on Human Genome Diversity Project Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the HGDP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Simons Genome Diversity Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>2b388c1fa446ecec70e33ea0471e06f8</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>50b80ed32b1ae542c8967cc31986dd19</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>995f30b74c4bb094a674b1a994853246</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome Copy Number</td> <td>e79e61efab4c491fa2825b7d1853df58</td> </tr> </tbody> </table> </div> <div>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</div>

EGP Mitochondrial Genome Analysis on Simons Genome Diversity Project Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the SGDP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Simons Genome Diversity Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <table> <tbody> <tr> <th>Public Dataset</th> <th>EGP Result File Type</th> <th>MD5</th> </tr> </tbody> <tbody> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>86b09553f80926c1c29c57000ec1a88f</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>010026d77bee81e7b8daf5836bd12da3</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>f1ea3edf4a82b42f2028467fb3544dc4</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Copy Number</td> <td>4872eeb792c214ad49662e98e4b14620</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p>

opencc-by-4.0Aug 2024View details →

A Systematic Mapping Study on Student Reflection in Software Engineering Project-Based Learning (supplementary material)

<p>This repository contains supplementary material for the manuscript "A Systematic Mapping Study on Student Reflection in Software Engineering Project-Based Learning". The CSV file is structured as follows:</p> <ul> <li>Column A represents the paper citation key generated by Zotero that we used as a unique identifier for all papers in this study.</li> <li>Columns B-I include the results of our data extraction as per the data extraction form.</li> <li>Columns J-AB include metadata about each paper.</li> </ul>

EGP Mitochondrial Genome Analysis on 1000 Genomes Project 2504 Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the 1000 Genomes Project 2504 Dataset. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on 1000 Genomes Project 2504 Dataset</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/1000G_2504_high_coverage.sequence.index</code>. Please note that the index files are there as well. You just have to append a <code>.crai</code>. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>dbf39d6ff0e4389b900f9d985f2e6c64</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>4d53ef60ec16f3e4b566c45fdf0fb977</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Variant Tables</td> <td>16925b546051d37cce27df8ec57ccc5e</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Copy Number</td> <td>365c1b360ea327795d981356064658a6</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div>

EGP Mitochondrial Genome Analysis on 1000 Genomes Project 698 Related Whole-Genome Sequencing Data

<div> <p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the 1000 Genomes Project 698 Related Dataset. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on 1000 Genomes Project 698 Related Dataset</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://ftp-trace.ncbi.nlm.nih.gov/1000genomes/ftp/1000G_2504_high_coverage/additional_698_related/1000G_698_related_high_coverage.sequence.index</code>. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>322038d61b4da2e937b32410613c3532</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>36c782c12245100478903f7fa191a402</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Variant Tables</td> <td>68b2a51361ffae4e7ad9d420b8becd38</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Copy Number</td> <td>1e83c8ae132b0a7ef33b090757b29063</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div> <p> </p> </div> <h2> </h2>

EGP Mitochondrial Genome Analysis on Gambian Genome Variation Project Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the GGVP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Gambian Genome Variation Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>d21e1e91e8b4c00627171fae79a1f54d</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>b359d1068d4f84f7746d1ebde82df29a</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>ee2b93aa93d2177d92ec0f8f308b43ed</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Copy Number</td> <td>fda509ba1d2bf33fd2d6b77b92e76c03</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div>

NANCY SNS JU Project - VR Video Streaming & iPerf3 on O-RAN 5G Testbed Dataset

<p>This dataset was developed in the context of the NANCY project and it is the output of the experiments involving streaming a virtual reality (VR) video in a 5G coverage expansion scenario. Additionally, iPerf3 experiments in both TCP and UDP modes were carried out. The coverage expansion scenario involves a main operator and a micro-operator which extends the main operator’s coverage and can also provide additional services.</p> <p>The dataset includes network traffic, which was captured and stored in a .pcap files, as well as various performance metrics that were collected by an xApp running in the near-real-time Radio Access Network Intelligent Controller.</p> <p>The NANCY project has received funding from the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union's Horizon Europe research and innovation programme under Grant Agreement No 101096456.</p>

opencc-by-4.0May 2024View details →

Projections of Precipitation and Temperatures in Greenland and the Impact of Spatially Uniform Anomalies on the Evolution of the Ice Sheet

<p>Supplementary data used in the article <em>Projections of Precipitation and Temperatures in Greenland and the Impact of Spatially Uniform Anomalies on the Evolution of the Ice Sheet</em> submitted to The Cryosphere.</p> <p>Please cite the corresponding paper if you use this data. </p> <p>We supply</p> <ol> <li>the regridded CMIP6 precipitation (pr) and temperature (tas) model output for Greenland.</li> <li>local precipitation-near surface temperature sensitivities for each model in the folder <em>local_slopes_precipitation</em></li> <li>The monthly anomalies for near-surface temperature and precipitation as well as the local change in precipitation (compare to the climatology, in %) with respect to the climatology (year 1980-200) in the folder <em>2100_anomalies</em></li> <li>The CMIP6 monthly climatology from the years 1980-2000 (precipitation & near-surface temperature) </li> <li>The monthly precipitation and near-surface temperature anomalies from 2015-2100 in the folder <em>2100_85years</em></li> </ol> <p> </p> <p>License of CMIP6 model output: </p> <p>CMIP6 model data produced is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0; https://creativecommons.org/licenses/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</p>

opencc-by-4.0Jul 2024View details →

Extract of the project data from the LIFE KPI webtool. Deliverable 2.5 of the LIFE NatuReef project: Nature-based reef solution for coastal protection and marine biodiversity enhancement. LIFE22-NAT-IT-LIFE-NatuReef/101113742

<p>Key performance indicator, a quantifiable measure of performance over time for a specific objective.</p>

All Figures of IAMM Project

<p>Figures produced during IAMM Project.</p> <p>AllYears directory contains figures of the evolution during the 30 years (2021-2050) along RCP 2.6 or RCP 8.5 (1by1rcp directory) and in comparing the 2 RCP (2rcp directory)</p> <p>Year_by_Year contains figures of the evolution of each year among the 30 years (directory with the name of the year from 2021 to 2050) along RCP 2.6 or RCP 8.5 (1by1rcp directory) and in comparing the 2 RCP (2rcp directory)</p> <p>_________________________________</p> <p>File name explanation :</p> <p>rcp26 : RCP 2.6     rcp85 : RCP 8.5   2rcp : RCP 2.6 (top) and RCP 8.5 (bottom)</p> <p>Year : yearly mean/statistics/evolution; Month : monthly mean/statistics/evolution</p> <p>2D : horizontal mean of the 2D variable          </p> <p>'FCO2' : CO2 sea-air flux, 'FCO2a' : Summed CO2 sea-air flux,'rain' : precipitation,'flsolar' : short waves solar flux ,'fltherm' : long waves IR flux,'WIND' : wind stress,'WSPD' : wind spead</p> <p>3D : 3D mean of the 3D variable (mean of the whole domain including water column)</p> <p>'TEMP' : temperature,'SAL' : salinity,'KZ' : eddy diffusivity,'phy_dia_Chl': nanoplankton chlorophyll,'phy_pico_Chl': picoplankton chlorophyll,'Chl': total chlorophyll,'mid_nh4_nh4': ammonium,'mid_no3_no3': nitrate,'mid_po4_po4': phosphate,'mid_O2_O2' : dissolved oxygen in mmol.m-3,'O2': dissolved oxygen in ml.L-1,'mid_dic_dic': dissolved inorganic carbon,'mid_pco2_pco2': CO2 oceanic partial pressure,'mid_pH_pH': pH,'mid_at_at': total alcalinity,'mid_aco3_aco3': CaCO3 (aragonit) saturation state </p> <p>Level : mean in 3 levels : surface (blue), mid-depth (green), bottom (orange) in addition of 3D mean (black)</p> <p>SOLEMIO : mean at the SOLEMIO (SOMLIT) station</p> <p>SURF : surface mean</p> <p>Depth : water column distribution</p> <p> </p> <p>  </p>

SmartAqua4FuturE (SAFE) Horizone Europe project_WP2_T2.3.1_Keywater Fisheries_Vermiculture Dataset

Open the record for dataset details and reuse information.

Data and models for Project 2 funded by FERSC in year 2023

<p>Data for FY23~24 FERSC Project 2: <span>Intermodal solutions for freight flows in Southwest U.S </span></p>

Meteorological Data from Kardamyla, Chios: March 2024 Baseline Measurements for the MUSICA Project

<p>The present meteorological data is collected from the weather station in <strong>Kardamyla</strong>, a village in northern Chios, and is published on the <strong>Zenodo</strong> platform for open access. The Kardamyla area was selected due to its proximity to the location where the <strong>MUSICA</strong> project platform will be installed. The data includes measurements of temperature, rainfall, wind speed, and wind direction, and covers the period from March 1st to March 31st, 2024.</p> <h3>Purpose</h3> <p>These measurements are conducted as part of the <strong>MUSICA</strong> project, with the goal of monitoring climate changes in the Kardamyla area and the broader region of Chios, particularly following the installation of the project's platform. The data presented here covers the period from March 2024, and new measurements will be regularly added as part of ongoing monitoring efforts to track changes in weather and climate conditions.</p> <h3>Content</h3> <p>The files include:</p> <ul> <li><strong>Date and time of recording</strong>: For accurate time tracking of the data.</li> <li><strong>Temperature</strong>: Daily average, maximum, and minimum temperatures in degrees Celsius (°C).</li> <li><strong>Rainfall</strong>: Daily rainfall in millimeters (mm).</li> <li><strong>Wind speed</strong>: Average and maximum daily wind speed in kilometers per hour (km/h).</li> <li><strong>Wind direction</strong>: The prevailing wind direction of the day.</li> </ul> <h3>Data Highlights for March 2024</h3> <ul> <li><strong>Highest temperature</strong>: 25.1°C, recorded on March 31st, 2024, at 15:10.</li> <li><strong>Lowest temperature</strong>: 3.3°C, recorded on March 24th, 2024, at 05:50.</li> <li><strong>Highest daily rainfall</strong>: 28.2 mm, recorded on March 5th, 2024.</li> <li><strong>Highest wind speed</strong>: 77.2 km/h, recorded on March 12th, 2024, at 00:10.</li> </ul> <h3>Data Usage</h3> <p>The data is free to use. Users are welcome to download, analyze, and utilize the data for personal, educational, or research purposes, as well as for developing applications and tools that contribute to understanding and addressing weather and climate phenomena.</p>

Meteorological Data from Kardamyla, Chios: February 2024 Baseline Measurements for the MUSICA Project

<p>The present meteorological data is collected from the weather station in <strong>Kardamyla</strong>, a village in northern Chios, and is published on the <strong>Zenodo</strong> platform for open access. The Kardamyla area was selected due to its proximity to the location where the <strong>MUSICA</strong> project platform will be installed. The data includes measurements of temperature, rainfall, wind speed, and wind direction, and covers the period from February 1st to February 29th, 2024.</p> <h3>Purpose</h3> <p>These measurements are conducted as part of the <strong>MUSICA</strong> project, with the goal of monitoring climate changes in the Kardamyla area and the broader region of Chios, particularly following the installation of the project's platform. The data presented here covers the period from February 2024, and new measurements will be regularly added as part of ongoing monitoring efforts to track changes in weather and climate conditions.</p> <h3>Content</h3> <p>The files include:</p> <ul> <li><strong>Date and time of recording</strong>: For accurate time tracking of the data.</li> <li><strong>Temperature</strong>: Daily average, maximum, and minimum temperatures in degrees Celsius (°C).</li> <li><strong>Rainfall</strong>: Daily rainfall in millimeters (mm).</li> <li><strong>Wind speed</strong>: Average and maximum daily wind speed in kilometers per hour (km/h).</li> <li><strong>Wind direction</strong>: The prevailing wind direction of the day.</li> </ul> <h3>Data Highlights for February 2024</h3> <ul> <li><strong>Highest temperature</strong>: 21.9°C, recorded on February 29th, 2024, at 13:40.</li> <li><strong>Lowest temperature</strong>: 3.0°C, recorded on February 4th, 2024, at 07:30.</li> <li><strong>Highest daily rainfall</strong>: 49.4 mm, recorded on February 12th, 2024.</li> <li><strong>Highest wind speed</strong>: 82.1 km/h, recorded on February 11th, 2024, at 21:30.</li> </ul> <h3>Data Usage</h3> <p>The data is free to use. Users are welcome to download, analyze, and utilize the data for personal, educational, or research purposes, as well as for developing applications and tools that contribute to understanding and addressing weather and climate phenomena.</p>