Find research datasets worth reusing

opencc-by-4.0Jul 2024View details →

Dataset for article: Potent and reversible open-channel blocker of NMDA receptor derived from dizocilpine with enhanced membrane-to-channel inhibition

<div>This version shows the correct number of n for Figure 6.</div> <div> </div>

opencc-by-4.0Aug 2024View details →

Dataset for the publication: Ruthenium-Catalyzed "Open-Loop" Recycling of Polyethylene via Tandem Isomerization-Metathesis (ISOMET)

This dataset contains the processed data collected in the research study titled "Ruthenium-Catalyzed “Open-Loop” Recycling of Polyethylene via Tandem Isomerization-Metathesis (ISOMET)" published in Green Chemistry.   <h3>Description of included data:</h3> <ul> <li>pyrolysis_product_dist_fig2.csv <ul> <li>Units: wt%</li> <li>wt% for heavy and light with respect to the total liquid fraction</li> <li>total liquid fraction = 100 - gases wt% - solids wt%</li> </ul> </li> <li>chain_length_dist_fig3.csv <ul> <li>Column compound: number of C-atoms in chain</li> <li>Columns before and after in mg</li> </ul> </li> <li>full_conv_exp_run1.csv and full_conv_exp_run2.csv <ul> <li>Column time in minutes</li> <li>Columns for propylene and butene in mmol</li> </ul> </li> <li>20mLDoE_fig4b.csv <ul> <li>Column temperature in °C</li> <li>Column pressure in bar</li> </ul> </li> <li>50mLDoE_fig4c.csv <ul> <li>Column temperature in °C</li> <li>Column pressure in bar</li> </ul> </li> <li>rep_batch_full_fig4d.csv <ul> <li>Column time in h</li> <li>Column propylene in mmol</li> <li>Column exchange: if "yes" gas phase was exchanged after measurement</li> </ul> </li> <li>tga_tipelin_610B_figS1.csv <ul> <li>Column temp in °C</li> <li>Column time in min</li> <li>Column mass in wt%</li> </ul> </li> <li>plot.py <ul> <li>Recreates all the figures in the publication. Requires the packages matplotlib, numpy, pandas, rwthcolors and scipy to be installed in the environment.</li> </ul> </li> </ul>

Phytoplankton Dataset: Supporting HAB monitoring based on cost-effective open-hardware solutions

ASTRAL Phytoplankton monitoring dataset which has supported technology validation based on images from single-specie phytoplankton sample and prototype deployment within IMTA labs

Open dataset for the research of "Assessing accuracy improvement of integrating digital footprints into gridded population mapping: spatiotemporal variations and data bias"

Result datasets for "Assessing accuracy improvement of integrating digital footprints into gridded populationmapping:spatiotemporal variations and data bias": <ol> <li> S1 is the results for gridded population mapping using different methods.</li> <li> S2 is the aggregate results of population mapping at county level.</li> <li> S3 is the results for intraday variation of population disaggregation accuracy,</li> <li> S4 is the data bias of different digital footprints.</li> </ol>

Microplastic Dataset: Supporting microplastic monitoring based on cost-effective open-hardware solutions

ASTRAL Dataset related to microplastic monitoring based on the open-hardware initiative PlanktoScope

Ilustração Frase Open Science

Título: Open Science: Just Science Done Right! Descrição: Esta ilustração está relacionada à Ciência Aberta, destacando a frase “Open Science: Just Science Done Right!”, de Jon Tennant, um defensor conhecido da ciência aberta e do acesso aberto. A arte feita à mão utiliza um lettering fluido e criativo para reforçar a mensagem sobre a importância de tornar a ciência acessível, transparente e colaborativa. Os toques de laranja vibrante trazem dinamismo à obra, simbolizando a energia e o impacto transformador da ciência aberta na sociedade global. Autor(a): Malu de Carvalho (Instagram: @mapadebiblio) Licença: Este trabalho está licenciado sob CC BY-NC-ND 4.0. Assunto: Ciência Aberta, Acesso Aberto, Comunicação Científica, Ilustração, Lettering DOI: 10.5281/zenodo.13853213

Figures code and data of "Coulomb blockade in open superconducting islands on InAs nanowires"

Electrons in closed systems can exhibit Coulomb blockade (CB) oscillations due to charge quantization. Here, we report CB oscillations in aluminum superconducting islands on InAs nanowires in the open regime. The Al island is connected to the source/drain leads through two contacts: One is fully transmitting while the other is tuned into the tunneling regime. This device configuration is typical for tunneling spectroscopy where charging energy is generally considered negligible. The oscillation periods are 2e or 1e, depending on the gate settings. A magnetic field can induce the 2e to 1e transition. Our result is reminiscent of the ``mesoscopic Coulomb blockade'' in open quantum dots caused by electron interference.

opencc-zeroOct 2024View details →

CWTS Leiden Ranking Open Edition 2024 - Results

This data set contains the indicators made available in the <a href="https://open.leidenranking.com">Open Edition of the CWTS Leiden Ranking 2024</a>. The Leiden Ranking Open Edition 2024 is based on data from OpenAlex. It provides indicators of scientific impact, collaboration, and open access publishing.

opencc-zeroOct 2024View details →

CWTS Leiden Ranking Open Edition 2024 - Data

This data set contains the data used to create the <a href="https://open.leidenranking.com">Open Edition of the CWTS Leiden Ranking 2024</a>. The data set includes (1) data about the universities included in the Leiden Ranking Open Edition 2024 and the links between these universities and their affiliated organizations, (2) data about the publications included in the Leiden Ranking Open Edition 2024 and the links between these publications and universities and main fields, (3) indicators at the level of publications, and (4) indicators at the level of universities and main fields. The Leiden Ranking Open Edition 2024 is based on the <a href="https://docs.openalex.org/download-all-data/openalex-snapshot">OpenAlex snapshot</a> released on August 30, 2024. The snapshot data is not included in this data set. The source code for creating this data set is available in <a href="https://github.com/CWTSLeiden/CWTS-Leiden-Ranking-Open-Edition">this GitHub repository</a>. See this blog post for more information about the Leiden Ranking Open Edition 2024.   This data set consists of the following tab-delimited files.   university <ul> <li>university_id</li> <li>university</li> <li>university_full_name</li> <li>ror_id</li> <li>ror_name</li> <li>country_code</li> <li>latitude</li> <li>longitude</li> <li>is_mtor_university</li> </ul>   affiliated_organization <ul> <li>ror_id</li> <li>ror_name</li> </ul>   university_affiliated_organization <ul> <li>university_ror_id</li> <li>relation_type</li> <li>affiliated_organization_ror_id</li> <li>affiliated_organization_weight</li> </ul>   main_field <ul> <li>main_field_id</li> <li>main_field</li> </ul>   pub <ul> <li>work_id</li> <li>doi</li> <li>pub_year</li> <li>micro_cluster_id</li> </ul>   pub_university <ul> <li>work_id</li> <li>university_id</li> <li>weight</li> </ul>   pub_main_field <ul> <li>work_id</li> <li>main_field_id</li> <li>weight</li> </ul>   period <ul> <li>period_begin_year</li> <li>period_end_year</li> <li>period</li> </ul>   pub_period_impact_indicators <ul> <li>work_id</li> <li>period_begin_year</li> <li>cs</li> <li>ncs</li> <li>p_top_1</li> <li>p_top_5</li> <li>p_top_10</li> <li>p_top_50</li> </ul>   pub_collab_indicators <ul> <li>work_id</li> <li>p_collab</li> <li>p_int_collab</li> <li>p_industry</li> <li>p_short_dist_collab</li> <li>p_long_dist_collab</li> </ul>   pub_oa_indicators <ul> <li>work_id</li> <li>p_oa_unknown</li> <li>p_oa</li> <li>p_gold_oa</li> <li>p_hybrid_oa</li> <li>p_bonze_oa</li> <li>p_green_oa</li> </ul>   university_main_field_period_impact_indicators <ul> <li>university_id</li> <li>main_field_id</li> <li>period_begin_year</li> <li>fractional_counting</li> <li>p</li> <li>tcs</li> <li>tncs</li> <li>p_top_1</li> <li>p_top_5</li> <li>p_top_10</li> <li>p_top_50</li> <li>mcs</li> <li>mcs_lb</li> <li>mcs_ub</li> <li>mncs</li> <li>mncs_lb</li> <li>mncs_ub</li> <li>pp_top_1</li> <li>pp_top_1_lb</li> <li>pp_top_1_ub</li> <li>pp_top_5</li> <li>pp_top_5_lb</li> <li>pp_top_5_ub</li> <li>pp_top_10</li> <li>pp_top_10_lb</li> <li>pp_top_10_ub</li> <li>pp_top_50</li> <li>pp_top_50_lb</li> <li>pp_top_50_ub</li> </ul>   university_main_field_period_collab_indicators <ul> <li>university_id</li> <li>main_field_id</li> <li>period_begin_year</li> <li>p</li> <li>p_collab</li> <li>p_int_collab</li> <li>p_industry_collab</li> <li>p_short_dist_collab</li> <li>p_long_dist_collab</li> <li>pp_collab</li> <li>pp_collab_lb</li> <li>pp_collab_ub</li> <li>pp_int_collab</li> <li>pp_int_collab_lb</li> <li>pp_int_collab_ub</li> <li>pp_industry_collab</li> <li>pp_industry_collab_lb</li> <li>pp_industry_collab_ub</li> <li>pp_short_dist_collab</li> <li>pp_short_dist_collab_lb</li> <li>pp_short_dist_collab_ub</li> <li>pp_long_dist_collab</li> <li>pp_long_dist_collab_lb</li> <li>pp_long_dist_collab_ub</li> </ul>   university_main_field_period_oa_indicators <ul> <li>university_id</li> <li>main_field_id</li> <li>period_begin_year</li> <li>p</li> <li>p_oa_unknown</li> <li>p_oa</li> <li>p_gold_oa</li> <li>p_hybrid_oa</li> <li>p_bronze_oa</li> <li>p_green_oa</li> <li>pp_oa_unknown</li> <li>pp_oa_unknown_lb</li> <li>pp_oa_unknown_ub</li> <li>pp_oa</li> <li>pp_oa_lb</li> <li>pp_oa_ub</li> <li>pp_gold_oa</li> <li>pp_gold_oa_lb</li> <li>pp_gold_oa_ub</li> <li>pp_hybrid_oa</li> <li>pp_hybrid_oa_lb</li> <li>pp_hybrid_oa_ub</li> <li>pp_bronze_oa</li> <li>pp_bronze_oa_lb</li> <li>pp_bronze_oa_ub</li> <li>pp_green_oa</li> <li>pp_green_oa_lb</li> <li>pp_green_oa_ub</li> </ul>

Raw images, video, and data file for the manuscript "Fabrication of Low-Cost, High-Resolution Open Capillary Microfluidics towards Self-Sustaining, Long-Term Hydration of Engineered Living Materials"

This dataset includes the raw images and data file in the manuscript "Fabrication of Low-Cost, High-Resolution Open Capillary Microfluidics towards Self-Sustaining, Long-Term Hydration of Engineered Living Materials", specifically: <ul> <li>Raw images for the optimized print with the PEGDA-glycerol-water resin (Figure 2 & Figure S2)</li> <li>Raw images for the optimized print with the PEGDA-glycerol-LB resin (Figure 2)</li> <li>Raw images for the optimized print with the BSA-PEGDA-water resin (Figure 3)</li> <li>Raw images and video for the spontaneous capillary flow of LB media in a PEGDA-glycerol-LB microfluidic chip (Figure 4)</li> <li>Raw data for the UV-vis spectrum of LB media (Figure S4)</li> </ul>

Flying Saucers - An Opening Salvo of the Cold War?

Open the record for dataset details and reuse information.

openmit-licenseOct 2024View details →

ACROSS WP5 Combustor Pilot Open Data

Evolution of reactive aerothermal fields in the U-THERM3D numerical simulations of FIRST combustor

Open Government Data des Bundes auf GovData

Datensatz zu Auswertung der durch Stellen des Bundes auf dem Open-Data-Portal GovData (www.govdata.de) veröffentlichten Datensätze. Auswertung in: Herfurth, Anne; Lange, Felix: Transparenz bewahren. Open Government Data im Bundesarchiv. In: Becker, Irmgard Ch. u.a. [Hrsg.]:  Born digital – neue Archivaliengattungen und ihre Bearbeitung im Archiv. Beiträge zum 28. Archivwissenschaftlichen Kolloquium der Archivschule Marburg. Veröffentlichungen der Archivschule Marburg, Nr. 72.  Hochschule für Archivwissenschaft, 2025. S. 331-355. S.a. https://www.archivschule.de/DE/forschung/archivwissenschaftliche-kolloquien/28-archivwissenschaftliches-kolloquiumganz.html

opencc-by-4.0Aug 2024View details →

MIGNEX Survey Dataset (open-access variant)

This is the anonymized variant of the MIGNEX Survey dataset. Please see MIGNEX Handbook Chapter 10 on how the anonymization process has affected the data.

Water in peripheral TM-interfaces of Orai1-channels triggers pore opening

Open the record for dataset details and reuse information.

opencc-by-4.0May 2024View details →

Helsinki Speech Challenge 2024 open audio dataset

<h1>Dataset</h1> This training dataset is originally designed for the Helsinki Speech Challenge 2024 (HSC2024). While it was created with this challenge in mind, its applications extend far beyond, making it a valuable resource for developing and testing audio algorithms across diverse uses. Our dataset features clean speech samples generated by OpenAI's text-to-speech model, paired with corresponding recorded signals. These recorded signals are purposefully distorted by real-world effects such as filtering and reverb, offering a realistic testing ground for your audio processing algorithms. To ensure ease of use, the audio samples are organized into 10 separate zip files, each dedicated to a specific task and level of complexity. Most zip files include two folders clean and recorded: one containing clean audio data and the other housing the corresponding recorded (distorted) data. However, note that folders Task_3_Level_1 and Task_3_Level_2 only include recorded data, as their clean counterparts are identical to those in Task_2_Level_2 and Task_2_Level_3, respectively. Additionally, each zip file includes a .txt file with the original text samples associated with the audio clips. Update 29th October: We have now also added the test data that was used for evaluation in the challenge with similar structure to the rest of the data, contained in the zip files starting with "Test". Additionally, there is folder Impulse_Responses, which contains a clean sine sweep signal and short and a long white noise signal with recorded counterparts.  To help you get started, we've also provided an example folder containing samples from each task and level, giving you a comprehensive overview of the dataset's scope and variety. The dataset also contains a python script evaluate.py. This can be used to evaluate the quality of audio files using the Mozilla Deepspeech speech recognition model. For more details on this script, see the more detailed description of the data challenge either on the website below or on arXiv <a href="https://arxiv.org/abs/2406.04123">https://arxiv.org/abs/2406.04123</a>. Important dates: <ul> <li>Data Challenge Launch: 10. June 2024.</li> <li>Sign-up deadline: 1. September 2024 (if you missed this deadline and wish to participate in the challenge, please send us an email).</li> <li>Submission deadline: 6. October 2024. We realize this deadline is a bit optimistic, but we humbly ask participants to try to make this deadline.</li> <li>Results are published: 4. November.</li> <li>Inverse days: 10.-13. December in Oulu, Finland.</li> </ul> Here is a link to the official webpage of the HSC2024: <a href="https://blogs.helsinki.fi/helsinki-speech-challenge/" target="_blank" rel="noopener">https://blogs.helsinki.fi/helsinki-speech-challenge/</a> Contact Email: hsc2024@helsinki.fi

Observing and controlling electrocyclic ring-opening reaction of cyclohexadiene at conical intersection

<div> <div> <div> The photoinduced cyclohexadiene/hexatriene ring-opening reaction has been modeled via explicit wave-packet propagation (Quantum dynamics-QD) on a two-dimensional (2D) ab-initio Hamiltonian (H) parametrized with multiconfigurational perturbative wavefunction theory (XMS-CASPT2). Electronic coherences and omptimal control pulses to enhance the ring-opening quantum yield have been modeled.  </div> </div> </div>

Replication Package for "Ensuring Open Source Integrity: The Intersection of Copy-Based Reuse and License Compliance"

Replication Package for "Ensuring Open Source Integrity: The Intersection of Copy-Based Reuse and License Compliance" Includes datasets, R and bash code.

Replication package for "An Exploratory Study on Default Class Openness in Java and Kotlin"

This dataset includes scripts, text files, and cached CSV/Parquet or raw TXT data files used to generate all analysis and results from the paper.  A README.md file is included in replication-pkg.zip for details on using the scripts. If you only want to inspect the figures, you do not need a data ZIP. If you want to simply re-generate the figures without changes, download data-cached.zip.  If you want to make any sort of change to the analyses, you will want to download data-csv.zip and/or data-raw.zip.  The CSV files are converted versions of the raw TXT files.

Underrepresented Groups in Open Source Software Development

This repository contains the artifacts generated when researching minority groups in open source software development, which aimed to analyze knowledge about minority groups in OSS projects. This set of artifacts consists of two main components: Research Protocol (PDF): The protocol in PDF format provides a detailed overview of the research design, methodology, and objectives of the study. It describes the scope of the research, research questions, and data collection approach. This protocol is a fundamental reference for researchers interested in understanding how the study was designed. Search Data (CSV): The CSV file contains the raw data collected during the research. The data includes results returned by each database, articles considered in each phase of the study, and the set of seed articles. The XLSX spreadsheet is a source for analyzing the data used in the research. This repository aims to promote a more transparent understanding of the process that guided this research. Researchers and the open source developer community can utilize this dataset for academic studies, replications, and informed decision-making to promote equity and representation in open source projects.