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.
2,235
datasets available to search
ShareScore release 0.9.0
Dataset results
2,235 results for “engineering”
Sebastian+Simmons-High-frequency quantitative ultrasound to assess the acoustic properties of engineered tissues in vitro
<p>This dataset includes raw acquired ultrasound data, processing scripts, and statistical data for acoustic property characterization of cell-free and cell-seeded fibrin hydrogels.</p>
Supplementary Material for Disruptive Solutions on Requirement Engineering for Agile Software Development: A tertiary study
<p>This repository delivers the supplementary material for the paper: <em>Disruptive Solutions on Requirement Engineering for Agile Software Development: A tertiary study.</em></p> <p>In the following, we present the abstract of the study:</p> <p><strong>Context:</strong> Agile Software Development (ASD) is a disruptive process compared to traditional software development. Therefore, traditional Requirements Engineering (RE) forms may not be the best way to do RE for ASD (RE-ASD). <strong>Objective:</strong> Working with ASD using traditional RE ways could limit ASD's potential. Thus, it is necessary to investigate what academia and industry have done in RE to take full advantage of all of the capabilities of ASD beyond traditional RE. <strong>Method: </strong>We conducted a Tertiary Study looking for solutions for RE-ASD using the Systematic Literature Review (SLR) protocol described by Kitchenham and Charters. We then categorized the solutions into families using Targeted Coding and Constant Comparison, tools from Socio-Technical Grounded Theory (STGT). Afterward, we classified the solutions as disruptive using our model based on the Hype Level Curve concept, assessing their hype (popularity) in the software engineering community using Google Trends and Google Colab tools. <strong>Results:</strong> After executing the SLR protocol, we accepted 37 studies and encountered 136 solutions used by academia and industry for RE-ASD. We categorized these solutions into 21 solution families, six of which we classified as disruptive. Design Thinking (DT) and Artificial Intelligence (AI) were the two families of solutions that stood out the most. We also identified the type of solution (e.g., process, method, technique, tool, model, framework) and domain (academia or industry). Furthermore, we cataloged the challenges presented by the solutions. <strong>Conclusion:</strong> We concluded that only a few solutions that have been used for RE-ASD have the power to successfully challenge the mainstream Agile Software Development process by using innovation (26 out of 106). There is a gap between academia and industry regarding these disruptive solutions, and some challenges still need to be addressed in using these solutions.</p> <p>The repository contains the following:</p> <ul> <li>Dataset from the Tertiary Study: <ul> <li>Data of the retrieved studies. It presents the classifications of the documents as 'Accepted,' 'Rejected' (with the indication of the step of the protocol the authors rejected the study), or 'Duplicated.'</li> <li>Data of all solutions retrieved from the accepted studies</li> </ul> </li> <li>Socio-Technical Grounded Theory (STGT) tools <ul> <li>Result of the use of Targeted Coding and Constant Comparison</li> </ul> </li> <li>The Google Colab Notebook <ul> <li>Code in python</li> <li>Results</li> </ul> </li> </ul> <p> </p>
Supplementary data for "ENGINEERED ADAPTATION MECHANISMS BETWEEN MARINE AND FRESHWATER ENVIRONMENTS IN FISH AFTER THE FLOOD" for the ICC 2023 in Cedarville, Ohio
<p>Supplementary data for "ENGINEERED ADAPTATION MECHANISMS BETWEEN MARINE AND FRESHWATER ENVIRONMENTS IN FISH AFTER THE FLOOD" for the ICC 2023 in Cedarville, Ohio.</p> <p>These include FishBase annotation, mtDNA sequence similarity matrixes, clustering, and statistics for nine fish orders:</p> <p>1. Acipenseriformes</p> <p>2. Angulliformes</p> <p>3. Beloniformes</p> <p>4. Characiformes</p> <p>5. Clupeiformes</p> <p>6. Cyprinodontiformes</p> <p>7. Elasmobranchii</p> <p>8. Pleuronectiformes</p> <p>9. Salmoniformes</p>
Dataset for "Applicability of Control Materials To Support Gene Promoter Characterization and Expression in Engineered Cells Using Digital PCR"
<p>This dataset constitutes the pre-processed data contained in the publication 'Applicability of Control Materials To Support Gene Promoter Characterization and Expression in Engineered Cells Using Digital PCR' Analytical Chemistry (2022) 94(14):5566-5574 (DOI: 10.1021/acs.analchem.1c05134).</p>
Consensus of Game Engine Architectures: an Overview of Coupling and Subsystems in Game Engines
<p>The video game industry is one of the most innovative, competitive, and rapidly growing industries. The industry's successes along with the increasing gamers’ expectations result in always larger and more complex games. These games thus must be developed with game engines, which have become correspondingly more sophisticated. Today, game engine developers find game engine development challenging. To support the process of creating and maintaining game engines, we propose applying an approach based on a consensus algorithm to a set of game engine architectures. Our approach generates a model that suggests the most commonly used subsystems in game engine architectures, ranked by their degree of coupling. The model can be used by developers as a starting point when deciding what subsystems to include when building a game engine and points out the most coupled subsystems, which can play an important role towards higher subsystems maintainability and reusability. We evaluate our approach by comparing the results of our approach against a predefined ground truth data. The result of our approach matches the subsystems defined in the ground truth data and it shows that the most coupled subsystems are core, low-level rendering, third-party SDKs and world editor. Additionally, when comparing game engine architectures, we observe that most architectures are composed of nearly the same set of subsystems. </p>
Figure 2: The intput and output forms of the transformation engine
<p>The goal of the project was to develop a translation system between two<br> knowledge representation forms. One of the representation forms is a new<br> kind of abstract predicate oriented conceptual graphs called ECG. The second<br> representation form is a set of sentences of a given language. While the ECG<br> is a general, language independent tool, the sentences belong to a language<br> and a speci¯c grammar.</p>
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 5. Differences in Validation Criteria between Classical Engineering Sciences and the Field of Brain- Like Artificial Intelligence for Automation
<p>A usual validation procedure in classical fields of engineering and computer sciences as well as in Applied AI, which is currently the dominant AI research domain, is to analyze and implement different potential methods to solve a given problem and to then compare their performance. What is thus usually desired are comparable, quantifiable results. In comparison, the starting situation is<br> different in the field of Brain-Like AI (see Figure 5).</p>
Ecosystem engineers spill-over of biodiversity: beavers affect breeding bird assemblage on wetland, but also on adjacent terrestrial habitats
<p>Abundance of breeding bird species recorded on Eurasian beaver and reference sites in Poland (central Europe).</p>
Engineering dynamic gates in binding pocket of penicillin G acylase to selectively degrade bacterial signaling molecules
<p>(01-mutants_design.tar.gz) Mutants design:</p> <ol> <li>Input structures of ecPGA from the PDB database (PDB IDs: 1GK9, 1GM7, and 1GM9), processed to resemble wild-type state, repaired by RepairPDB module of FoldX 4</li> <li>Double-point mutants preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA double-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA double-point mutants</li> </ol> </li> <li>Triple-point mutant preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA triple-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA triple-point mutants</li> </ol> </li> </ol> <p>(02-docking.tar.gz) Preparation of protein-ligand complexes using molecular docking for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules:</p> <ol> <li>PDB files of ligand, PDBQT files of the receptor and PDB files of the complexes selected from docking experiment:</li> </ol> <p>Full names of presented protein variants:<br>ecPGA_wt, wild-type Escherichia coli penicillin G acylase<br>LAF, Phe138αLeu & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_22<br>LSF, Phe138αLeu & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_98<br>MAF, Phe138αMet & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_23<br>MSF, Phe138αMet & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_99<br>VAF, Phe138αVal & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_30<br>YAF, Phe138αTyr & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_33<br>Full names of presented AHLs:<br>C06, N-hexanoyl-L-homoserine lactone;<br>C06-3O, N-3-oxo-hexanoyl-L-homoserine lactone;<br>C08, N-octanoyl-L-homoserine lactone;<br>C08-3O, N-3-oxo-octanoyl-L-homoserine lactone;<br>C10, N-decanoyl-L-homoserine lactone;<br>C12-3O, N-3-oxo-dodecanoyl-L-homoserine lactone</p> <p>(03-protein_ligand_MDs.tar.gz) Ligand-enzyme complexes molecular dynamics for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules:</p> <ol> <li>Force field parameters in Amber format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Output files generated during post-processing of production runs trajectories in a form of text files generated by cpptraj</li> </ol> <p>(04-free_enzymes_MDs.tar.gz) Free enzymes molecular dynamics of 3 best triple-point ecPGA (VAF, YAF and MSF) mutants prioritized based on protein-ligand molecular dynamics simulations and experimental assays:</p> <ol> <li>Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber format</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Post-processing analysis of generated trajectories: <ol> <li>Text files with distances, CSV files containing result of PCA and clustering, PNG files with clustered PCA results</li> <li>Inputs and outputs of MDpocket analysis and visualization of the pocket frequency grid as an isomesh</li> <li>CAVER input configuration files in text format, CAVER output data including parsed CSV and text files for visualization of entrance opening time evolution and cavity profiles inspection</li> <li>cpptraj generated text files including RMSD, distances and chi1 angles measurements</li> </ol> </li> </ol> <p>All plots were generated using matplotlib or seaborn Python libraries. Figures containing structural representations were generated using PyMOL 2.0.1.</p> <p>(05-ecPGA_VAF_YAF_MSF_penG_MDs.tar.gz) PenG-enzyme complexes molecular dynamics for wild-type ecPGA and 3 best designed triple-point mutants (VAF, YAF, MSF):</p> <ol> <li>PenG force field parameters in Amber (GAFF) format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format and analysis output files generated during post-processing of production runs trajectories in a form of text files</li> <li>Reactive Stabilization Score [RSS] statistics summarized in CSV files</li> </ol>
Strain gauge platforms: Time-lapse microscopy dataset of engineered cardiac microbundles
<p>This dataset is a "part I" extension of the "<a href="https://doi.org/10.5061/dryad.5x69p8d8g">Engineered cardiac microbundle time-lapse microscopy image dataset</a>" and contains 732 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using microbundle strain gauge platforms [1] ("Type1"). In the "part II" extension, we included 808 experimental time-lapse image sequences of beating hiPSC-based cardiac microbundles using FibroTUG platforms [2] ("Type2"). </p> <p>References:</p> <p>[1] Zhang, K., Cloonan, P. E., Sundaram, S., Liu, F., Das, S. L., Ewoldt, J. K., ... & Chen, C. S. (2021). Plakophilin-2 truncating variants impair cardiac contractility by disrupting sarcomere stability and organization. <em>Science Advances</em>, <em>7</em>(42), eabh3995.</p> <p>[2] DePalma, S. J., Davidson, C. D., Stis, A. E., Helms, A. S., & Baker, B. M. (2021). Microenvironmental determinants of organized iPSC-cardiomyocyte tissues on synthetic fibrous matrices. <em>Biomaterials science</em>, <em>9</em>(1), 93-107.</p>
Dataset and Replication Package for the View-Based Retriever Approach To Reverse Engineering Software Architecture Models
<div> <div><span>Dataset and replication package for the view-based Retriever approach to reverse engineering software architecture models. Each Dataset project is structured as follows:</span></div> <ul> <li><span>The .ruleengine.yml file contains the configuration for running the Retriever approach.</span> <ul> <li><span>The repository value is the ID of a GitHub repository.</span></li> <li><span>The current_version value is the latest version of the retriever approach used to build the architectural models.</span></li> <li><span>The rules values are the rules used to build the architectural models.</span></li> </ul> </li> <li><span>The model_re folder contains the architectural model of the system automatically generated by the Retriever approach.</span> <ul> <li><span>The pcm folder contains the Palladio Component Model (PCM) of the system.</span></li> <li><span>The uml folder contains the PlantUML model.</span></li> </ul> </li> <li><span>The model_gs folder contains our manual gold standards for the system.</span></li> </ul> <div><span>The easiest way to use our approach is to use the CLI application with the given parameters: ./eclipse -i /path/to/input/directory -o /path/to/output/directory -r supported_rules</span></div> </div>
Aero-engine NOx emissions in case of electrochemical suppression technique application (experimental results)
<p><span>Results of the mini engine exhaust tests with various excitation discharge type and energy application</span></p>
Multi-domain evaluation of a latest generation combustion engine: focusing on sound quality perception
<p>Dataset for conference paper "Multi-domain evaluation of a latest generation combustion engine: focusing on sound quality perception"</p>
Data - Teaching and Learning of Introduction to Software Engineering Experimentation to Distance-Learning Students: a Quasi-Experiment
<p>Data from a quasi-experiment on "Teaching and Learning of Introduction to Software Engineering Experimentation to Distance-Learning Students: a Quasi-Experiment"</p> <p> </p> <p>Funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) 311503/2022-5</p>
Supplemental Material: Research Artifacts for Human-Oriented Experiments in Software Engineering: An ACM Badges–driven Structure Proposal
<p>This Research Artifact contains supplemental material from the study: "Supplemental Material: Research Artifacts for Human-Oriented Experiments in Software Engineering: An ACM Badges–driven Structure Proposal". The supplementary material contains:</p> <ol> <li>The list of the 106 primary studies classified by journals.</li> <li>The list of the 12 research artifacts classified by conferences.</li> <li>The .xlsx file of the dataset used to analyze the RQs.</li> <li>The .xlsx file of the dataset used to analyze the research artifacts problems (Table 3). </li> <li>The list of the figures published in the scientific article.</li> </ol>
3D Laser Scanning Data: Public Square in Murcia and Engineering Laboratory at the University of Alicante
<p>This dataset includes 3D terrestrial laser scans obtained using the Leica C10 ScanStation. The data covers two distinct scenarios:</p> <ol> <li> <p><strong>Public Square in Murcia Capital</strong>: This dataset includes two scan positions within a public square located in Murcia. Three HDTarget markers were placed, and their center or vertex coordinates are provided in the accompanying _vertices.txt file. The scans were conducted with the laser scanner leveled, but they are not registered.</p> </li> <li> <p><strong>Engineering Laboratory at the University of Alicante</strong>: This dataset consists of two scans of the Ground Engineering Laboratory at the University of Alicante. The scans were conducted with the same leveled laser scanner, and no targets were used. Between the two scans, some elements in the laboratory were slightly moved, which can be identified by comparing the point clouds.</p> </li> </ol>
Dataset for "Engineering defect clustering in diamond-based materials for technological applications via quantum mechanical descriptors"
<p>The unique set of extreme physical properties makes diamond an ideal candidate for applications in the energy industry such as in high-power and high-frequency electronics as well as in electrochemistry and photovoltaics. Furthermore, dopant-vacancy complexes in diamond can be exploited for further development of quantum computers, single-photon emitters, high-precision magnetic field sensing and nanophotonic devices. While certain dopant-vacancy complexes are well-studied, studies of other dopant/vacancy clusters are focused mostly on defect detection while investigations on how to tune their electronic and optical properties for specific applications is mostly omitted. To this aim, we attempted to reveal coupled structural-electronic features and their effect on the band gap of such defects through first principle calculations. We investigated four different defect types: a) dopant-vacancy complexes (X-V), b) two dopants as nearest neighbours (X-X), c) two dopants separated by one carbon atom (X-C-X) and d) two dopants separated by a vacancy (X-V-X). For each of these configurations, we considered Al, B, N, P and Si as dopant atoms. This dataset contains input files needed to reproduce every ground state geometry used in our study.</p>
Dataset: Pacer BlueStar Engineering the Future ETF (BULD) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data for the paper: The Role of Glycerol in Manufacturing Freeze-Dried Chitosan and Cellulose Foams for Mechanically Stable Scaffolds in Skin Tissue Engineering
<p>The Dataset contains all the data, described in the article "<strong>The Role of Glycerol in Manufacturing Freeze-Dried Chitosan </strong><br><strong>and Cellulose Foams for Mechanically Stable Scaffolds in Skin Tissue Engineering</strong>."</p> <p><strong><em>Abstract</em></strong><br>Various strategies have extensively explored enhancing the physical and biological properties of chitosan and cellulose scaffolds for skin tissue engineering. This study presents a straightforward method involving the addition of glycerol into highly porous structures of two polysaccharide complexes: chitosan/carboxymethyl cellulose (Chit/CMC) and chitosan/oxidized cellulose (Chit/OC); during a one-step freeze-drying process. Adding glycerol, especially to Chit/CMC, significantly increased stability, prevented degradation, and improved mechanical strength by nearly 50%. Importantly, after 21 days of incubation in enzymatic medium Chit/CMC scaffold has almost completely decomposed, while foams reinforced with glycerol exhibited only 40% mass loss. It is possible due to differences in multivalent cations and polymer chain contraction, resulting in varied hydrogen bonding <br>and, consequently, distinct physicochemical outcomes. Additionally, the scaffolds with glycerol improved the cellular activities resulting in over 40% higher proliferation of fibroblast after 21 days of incubation. It was achieved by imparting water resistance to the highly absorbent material and aiding in achieving a balance between hydrophilic and hydrophobic properties. This study clearly indicates the possible elimination of additional crosslinkers and multiple fabrication steps that can reduce the cost of scaffold production for skin tissue engineering applications while tailoring mechanical strength and degradation.</p> <p><strong>Figure 2.</strong> Morphology. SEM micrographs of the internal structure of the freeze-dried scaffolds. Results of porosity analysis. The methodology and data are described in the README file in the folder.</p> <p><strong>Figure 3.</strong> Mechanical test results. Representative stress-strain curves from the tensile test of all freeze-dried scaffolds, where (A)<br>– measurement performed in dry conditions, (B) – measurement performed in wet conditions. All are described in the README file in the folder.</p> <p><strong>Figure 4. </strong>Swelling behavior of all scaffolds. B – Two representative vials with a visual demonstration of swelling, samples marked with circles: Chit/CMC sample submerged in the PBS (blue circle) and Chit/CMC/Glyc sample floating on the surface (green circle). The arrows lead to photos of scaffolds taken from vials directly after swelling. C – Gel fraction analysis in aqueous solution after 24 <br>6 h. D – Time after which the water droplet is absorbed into the scaffold. E – Photographs of water droplet shape changes on Chit/CMC and Chit/CMC/Glyc scaffolds over time. All are described in the README file in the folder.</p> <p><strong>Figure 5</strong>. Fourier Transform Infrared Spectroscopy (ATR-FTIR) analysis results. Details are in the README file in the folder.</p> <p><strong>Figure 6.</strong> The FTIR spectra of eluates from degraded scaffolds collected on a microscopic glass slide. Details are in the README file in the folder.</p> <p><strong>Figure 7.</strong> The degradation studies of all scaffolds over 21 days of experiments in A – enzymatic medium. B – cell culture medium. Details are in the README file in the folder.</p> <p><strong>Figure 9. </strong>Cell experiments and toxicity analysis. Cytotoxicity of eluates taken from degraded scaffolds. B – Direct fibroblast seeding on scaffolds during 14 days of culture period. C – Direct fibroblast seeding on scaffolds during 14 days of culture period without control to better see the effect of glycerol. Details are in the README file in the folder.</p>
Datasets for Crowd-based Requirements Engineering and aspect-based detection of learning-centered emotion from the text in Serbian language
<h1>Datasets for the paper "Enhancing Software and Learning with Serbian Student Feedback Corpora"</h1> <p>These datasets include student feedback on an Intelligent Tutoring System written in Serbian, annotated with categories for Crowd-based Requirements Engineering (CrowdRE) and aspect-based detection of learning-centered emotions. Four annotators manually annotated each sentence. </p> <p>The CrowdRE dataset includes two JSON files:</p> <ul> <li><strong>crowdre_english.json</strong> - annotated text with columns and classes written in English. Columns are: <ul> <li><em>Comment</em> - the entire student feedback</li> <li><em>Sentence</em> - sentence extracted from the feedback that was annotated</li> <li><em>Intention </em>- class representing the intention of the sentence</li> <li><em>Topic </em>- class representing the topic of the sentence</li> </ul> </li> <li><strong>crowdre_srpski.json</strong> - annotated text with columns and classes written in Serbian. Columns are:<br> <ul> <li><em>Komentar</em> - the entire student feedback</li> <li><em>Recenica </em>- sentence extracted from the entire feedback that was annotated</li> <li><em>Namera </em>- class representing the intention of the sentence</li> <li><em>Tema </em>- class representing the topic of the sentence.</li> </ul> </li> </ul> <p>The dataset for the aspect-based detection of learning-centered emotions includes two JSON files:</p> <ul> <li><strong>emotions_english.json </strong>- annotated text with columns and classes written in English. Columns are: <ul> <li><em>Comment </em>- the entire student feedback</li> <li><em>Sentence </em>- sentence extracted from the feedback that was annotated</li> <li><em>Aspect </em>- class representing the aspect of the sentence</li> <li><em>Emotion </em>- class representing the learning-centered emotion of the sentence</li> </ul> </li> <li><strong>emocije_srpski.json </strong>- annotated text with columns and classes written in Serbian. Columns are: <ul> <li><em>Komentar </em>- the entire student feedback</li> <li><em>Recenica</em> - sentence extracted from the entire feedback that was annotated</li> <li><em>Aspekt</em> - class representing the aspect of the sentence</li> <li><em>Emotion </em>- class representing the learning-centered emotion of the sentence.</li> </ul> </li> </ul> <p>Annotators annotated the dataset based on the annotation procedure and guidelines available <a href="https://github.com/Clean-CaDET/student-feedback-mining">here</a>. </p> <h2>Citation</h2> <p>If you use this in your research, please cite:</p> <blockquote> <p>Vidaković, D., Luburić, N., Kovačević, A., & Slivka, J. Enhancing software and learning with Serbian student feedback corpora. Language Resources & Evaluation (2025). https://doi.org/10.1007/s10579-025-09855-y</p> </blockquote> <p> </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.