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.
107
datasets available to search
ShareScore release 0.9.0
Dataset results
107 results for “Materials design”
Designing a User Interface to Explore Collections of Directly-Follows Graphs for Process Mining Analysis - Supplementary Material
<p>Supplementary Material for paper: "Designing a User Interface to Explore Collections of Directly-Follows Graphs for Process Mining Analysis", submitted to BPMDS 2024</p>
Codes and results for self-learning entropic population annealing for interpretable materials design
<p>Codes that can reproduce the results in the paper entitled "self-learning entropic population annealing for interpretable materials design". Results, when the number of particles is 50, are included.</p>
Supplementary material 1 from: Murphy CA, Gerth W, Neal T, Arismendi I (2022) A low-cost, durable, submersible light trap and customisable LED design for pelagic deployment and capture of fish parasite Salmincola sp. copepodids. NeoBiota 73: 1-17. https://doi.org/10.3897/neobiota.73.76515
Supplementary material for a low-cost, durable, submersible light trap and customizable LED design for pelagic deployment and capture of fish parasite Salmincola sp. copepodids
Supplementary Materials: Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale
<p>Supplementary materials (aka data artifact or data archive) for our NAPAC22 publication: "Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale" (Paper ID: TUYE2).</p> <p>Work supported by the Exascale Computing Project (17-SC-20-SC), a joint project of the U.S. Department of Energy's Office of Science and National Nuclear Security Administration, responsible for delivering a capable exascale ecosystem, including software, applications, and hardware technology, to support the nation's exascale computing imperative. This work was supported by the Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under U.S. Department of Energy Contract No. DE-AC02-05CH11231.<br> This research used resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility located at Lawrence Berkeley National Laboratory, operated under Contract No. DE-AC02-05CH11231.</p>
Supplementary material 1 from: Behei N, Tryhubchak O, Pryymak B (2022) Development of amlodipine and enalapril combined tablets based on quality by design and artificial neural network for confirming of qualitative composition. Pharmacia 69(3): 779-789. https://doi.org/10.3897/pharmacia.69.e86876
The results of the study of pharmaco-technological parameters of intermediates and amlodipine tablets with enalapril, data of the functions of desirability
Dataset: Protocol for Designing, Optimizing and Analyzing Secondary Critical Material Supply Chains using RELOG
<p>Source code and data for "Protocol for Designing, Optimizing and Analyzing Secondary Critical Material Supply Chains using RELOG."</p>
Supplementary Material for the Paper "Design Recommendations for Self-Monitoring in the Workplace: Studies in Software Development"
<p>Contains the supplementary material for the paper "Design Recommendations for Self-Monitoring in the Workplace: Studies in Software Development" submitted to CSCW'18. All contents are explained in the file README.txt.</p> <p><strong>Abstract:</strong><br> One way to improve the productivity of knowledge workers is to increase their self-awareness about productivity at work through self-monitoring. Yet, little is known about expectations of, the experience with and the impact of self-monitoring in the workplace. To address this gap, we studied software developers, as one community of knowledge workers. We used an iterative, feedback-driven development approach (N=20) and a survey (N=413) to infer design elements for workplace self-monitoring, which we then implemented as a technology probe called WorkAnalytics. We field-tested these design elements during a three-week study with software development professionals (N=43). Based on the results of the field study, we present design recommendations for self-monitoring in the workplace, such as using experience sampling to increase the awareness about work and to create richer insights, the need for a large variety of different metrics to retrospect about work, and that actionable insights, enriched with benchmarking data from co-workers, are likely needed to foster productive behavior change at work.</p> <p><strong>Source Code:</strong></p> <p>The source code of WorkAnalytics can be found on <strong><a href="https://github.com/sealuzh/PersonalAnalytics">GitHub</a></strong> (under the original name PersonalAnalytics). WorkAnalytics was built with Microsoft's Dot.Net framework in C# and can be used on the Windows 7, 8 and 10 operating system.</p>
Supplementary material 1 from: Nakahara S, Marín MA, Ríos-Málaver C (2015) Taxonomic status and redescription of Magneuptychia nebulosa (Butler, 1867) (Lepidoptera, Nymphalidae, Satyrinae) with a lectotype designation. ZooKeys 503: 135-147. https://doi.org/10.3897/zookeys.503.9156
Records for Magneuptychia nebulosa from Quebrada Honda, El Jarillo, Miranda, Venezuela: Explanation note: Records for Magneuptychia nebulosa from Quebrada Honda, El Jarillo, Miranda, Venezuela; Altos de Pipe, Instituto venezolano de Investigaciones Científicas, Miranda, Venezuela: Cristóbal Ríos Málaver Leg: These following specimens are deposited in the reference collection of the Venezuelan Institute of Scientific Research IVIC, Altos de Pipe, Miranda, Venezuela.
Supplementary material 1 from: Al-Mahadeen MM, Jaber AM, Al-Najjar BO (2024) Design, synthesis and biological evaluation of novel 2-hydroxy-1 H-indene-1,3(2 H)-dione derivatives as FGFR1 inhibitors. Pharmacia 71: 1-9. https://doi.org/10.3897/pharmacia.71.e122127
Design, synthesis and biological evaluation of novel 2-hydroxy-1H-indene-1,3(2H)-dione derivatives as FGFR1 inhibitors
Styrene monomer as potential material for functionalization and design of chromophores for new optoelectronic and NLO polymers conception: DFT study
<p>Using Density functional theory (DFT), we have studied the intrinsic properties of styrene. We determine firstly: optimized structures, structural parameters, and thermodynamic properties to make our simulations more realistic to experimental results and check the stability. We secondly investigate optoelectronic, electronic, and global descriptors, transport properties of holes and electrons, NBO analysis, absorption, and fluorescence properties. We finally study NLO:1st and 2nd order hyperpolarizability, 2nd and 3rd order optical susceptibilities, hyper-Rayleigh scattering hyperpolarizability, EOPE, DC-KERR effects, and quadratic refractive index. The bandgap energy E<sub>g</sub> = 5.146 eV and dielectric constant show that styrene is a good insulator with an average electric field value of 4.43×10<sup>8 </sup>Vm<sup>-</sup><sup>1</sup>. Thermodynamic findings show that our molecule is thermodynamically and chemically stable. Electron and hole reorganization energies of 0.393 eV and 0.295 eV, respectively, show that styrene is more favorable to hole transport than electron transport. Styrene is transparent with linear refractive index n = 1.750 and quadratic . At the NLO, styrene has a non-zero value of which confirms the existence of first-order nonlinear optical activity. Globally the study shows that the styrene monomer is suitable for the architecture design of new polymer materials for NLO applications and optoelectronic by functionalization.</p>
Dataset 2.2 Bark bug design for realization in organic materials
<p>Dataset 2.2 of Bark bug design for realization in organic materials</p>
Supplementary Material for: 'An impedance pneumography signal quality index: design, assessment and application to respiratory rate monitoring'
<p>This supplementary material accompanies:</p> <p>Charlton P.H. <em>et al.</em>, "<a href="https://doi.org/10.1016/j.bspc.2020.102339">An impedance pneumography signal quality index for respiratory rate monitoring: design, assessment and application</a>", <em>Biomedical Signal Processing and Control</em>, 65, 102339, 2021.</p> <p>The Impedance Pneumography Signal Quality Index (SQI) dataset and accompanying scripts (in Matlab format) are provided to facilitate reproduction of the analyses using data from the MIMIC III dataset in this publication.</p> <p><strong>Summary of Publication</strong></p> <p>In this article we developed and assessed the performance of a signal quality index (SQI) for the impedance pneumography signal.<br> The SQI was developed using data from the <a href="http://peterhcharlton.github.io/RRest/listen_dataset.html">Listen dataset</a>, and assessed using data from the <a href="http://peterhcharlton.github.io/RRest/listen_dataset.html">Listen dataset</a> and MIMIC III datasets.<br> The SQI was found to accurately classify segments of impedance pneumography signal as either high or low quality. Furthermore, when it was coupled with a high performance RR algorithm, highly accurate and precise RRs were estimated from those segments deemed to be high quality. In this study performance was assessed in the critical care environment - further work is required to deteremine whether the SQI is suitable for use with wearable sensors. Both the dataset and code used to perform this study are publicly available.</p> <p><strong>Reproducing this Publication</strong></p> <p>The work relating to the MIMIC dataset in this publication can be reproduced as follows:</p> <p><strong> - Reproducing the analysis</strong><br> These steps can be used to quickly reproduce the analysis using the curated and annotated dataset.</p> <p>* Download the curated and annotated dataset from <a href="https://doi.org/10.5281/zenodo.3973770">Zenodo</a> using this <a href="https://zenodo.org/record/3973771/files/mimic_imp_sqi_data.mat?download=1">direct download link</a>.<br> * Run the analysis using the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> script.</p> <p><strong> - Full reproduction</strong><br> These steps include downloading the raw data files, extracting data from these files, collating the dataset, manually annotating the data, and performing the analysis.</p> <p>* Use the <a href="https://zenodo.org/record/3973771/files/ImP_SQI_mimic_data_importer.m?download=1"><em>ImP_SQI_mimic_data_importer.m</em></a> script to download raw MIMIC data files from PhysioNet, and collate them into a single Matlab file.<br> * Prepare the dataset for manual annotation by running the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> script.<br> * Manually annotate the signals by running the <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_mimic_imp_annotation.m</em></a> script - the annotations are stored in separate files (the original annotation files are available <a href="https://zenodo.org/record/3974113/files/2019_annotations.zip?download=1">here</a>).<br> * Import the manual annotations into the collated data file by re-running the <a href="https://zenodo.org/record/3973771/files/ImP_SQI_mimic_data_importer.m?download=1"><em>ImP_SQI_mimic_data_importer.m</em></a> script.<br> * Run <a href="https://zenodo.org/record/3973771/files/run_imp_sqi_mimic.m?download=1"><em>run_imp_sqi_mimic.m</em></a> to perform the analysis described in the publication.</p> <p><strong> - Submitted manuscript</strong></p> <p>The submitted manuscript is available <a href="https://zenodo.org/record/5211463/files/Impedance%20SQI%20manuscript%20-%20Oct%202020%20revision.docx?download=1">here</a>.</p> <p>The scripts are also stored (alongside details of how to use them) are available in the <a href="http://peterhcharlton.github.io/RRest/">RRest GitHub repository</a> at: <a href="https://github.com/peterhcharlton/RRest/tree/master/RRest_v3.0/Publication_Specific_Scripts/ImP_SQI">https://github.com/peterhcharlton/RRest/tree/master/RRest_v3.0/Publication_Specific_Scripts/ImP_SQI</a></p> <p>License: The dataset (<a href="https://zenodo.org/record/3974113/files/mimic_imp_sqi_data.mat?download=1"><em>mimic_imp_sqi_data.mat</em></a>) is distributed under the terms specified in the accompanying LICENSE file. The scripts are distributed under the GNU General Public Licence (as specified towards the start of each file).</p> <p>Version 1.0: This version includes the submitted manuscript.</p> <p> </p>
Supplementary Material for Human Factors in the Design of Chatbot Interactions: Conversational Design Practices
<p>Supplementary Material for the thesis entitled <em>Human Factors in the Design of Chatbot Interactions: Conversational Design Practices.</em></p> <p>This repository contains the following files<em>:</em></p> <ul> <li><em>systematic_literature_review_data -> </em>Dataset of the retrieved papers from the SLR, the indication of papers that were removed at each step of the protocol, the list of accepted papers, and the search strings that were used;</li> <li><em>guide_vX -> </em>Faithful prints of the guide's web pages that were shared with the validation participants. V1 was used in the survey, V2 was used in the case study, and V3 is the final version;</li> <li><em>validation_survey</em> -> <ul> <li>A copy of the Google Forms questionnaire that was used in the survey;</li> <li>Sheet with the answers to this survey;</li> </ul> </li> <li><em>validation_case_study</em> -> <ul> <li><em>conversation_samples -> </em>Conversations made by the participants in the case study stages. In each file, the conversation from the left was made without the guide, and the one from the right was created with the guide;</li> <li><em>interview_transcripts -> </em>Transcripts of the interviews conducted with each participant at the last stage of the case study;</li> <li><em>instructions_to_participants.pdf</em> -> File provided to participants containing the instructions for each step of the case study;</li> <li><em>transcripts_coding.xlsx -> </em>Sheet containing transcripts from participants' responses and the corresponding code after the thematic analysis;</li> </ul> </li> </ul>
Dataset for publication Chougan M., Ghaffar S.H., Nematollahi B., Sikora P., Dorn T., Stephan D., Albar A., Al-Kheeta M.J. Effect of natural and calcined halloysite clay minerals as low-cost additives on the performance of 3D-printed alkali-activated materials. Materials and Design (2022) 223, 111183
<p>Open dataset for publication Chougan M., Ghaffar S.H., Nematollahi B., Sikora P., Dorn T., Stephan D., Albar A., Al-Kheeta M.J. Effect of natural and calcined halloysite clay minerals as low-cost additives on the performance of 3D-printed alkali-activated materials. <strong>Materials and Design</strong> (2022) 223, 111183. <a href="https://doi.org/10.1016/j.matdes.2022.111183">https://doi.org/10.1016/j.matdes.2022.111183</a></p> <p>File 1 - FTIR - data of raw and calcined material - *.opj (Origin)</p> <p>File 2 - Mechanical performance print vs cast - *.opj (Origin)</p> <p>File 3 - Mechanical performance - *.opj (Origin)</p> <p>File 4 - TGA and XRD - data of raw and calcined material - *.opju</p>
FIGURE 4 in Type material of Chone perseyi Zenkewitsch, 1925 is not missing (Annelida: Sabellida): redescription of the species and lectotype designation
FIGURE 4. Scanning electron microscopy of Euchone perseyi, paralectotype Pol610. A–B, Posterior abdomen and pygidia, lateral views; C–G, abdominal tori; C, abdominal segment 1; D, abdominal segment 2; E, abdominal segment 5; F, abdominal segment 16; G, abdominal segment 17. Scale bars A–B: 30 μm, C–E: 10 μm, F–G: 3 μm.
FIGURE 3 in Type material of Chone perseyi Zenkewitsch, 1925 is not missing (Annelida: Sabellida): redescription of the species and lectotype designation
FIGURE 3. Scanning electron microscopy of Euchone perseyi, paralectotype Pol610. A, Body, lateral view; B, thorax, dorsal view; C, thoracic chaetigers, 1 and 2 indicates the number of chaetiger; D, thoracic chaetiger 6; E–F, thoracic uncini from chaetiger 2. Scale bars A–B: 300 μm, C: 30 μm, D: 10 μm, E–F: 1 μm. Abbreviations: inf = inferior group, sup = superior group.
FIGURE 2 in Type material of Chone perseyi Zenkewitsch, 1925 is not missing (Annelida: Sabellida): redescription of the species and lectotype designation
FIGURE 2. Bodies of Euchone perseyi stained with methylene blue. A–E, G lectotype PI–4839, F, H paralectotype Pol610. A, Collar and base of crown, dorsal view; B, same, ventral view; C, lateral view; D, thorax, lateral view; E, radiolar crown, lateral view; F, right lobe of radiolar crown (left lobe removed); G–H, posterior abdomen. Scale bars 500 μm. Abbreviations: apr = anterior peristomial ring, gr2 = glandular ridge in chaetiger 2, coll = collar or posterior peristomial ring collar, vsc = ventral shield of collar, 1–8 indicates the number of the thoracic chaetigers.
FIGURE 1 in Type material of Chone perseyi Zenkewitsch, 1925 is not missing (Annelida: Sabellida): redescription of the species and lectotype designation
FIGURE 1. Jars and original labels of Chone perseyi housed at the Zoological Museum of Moscow State University. A, Jars; B–D, original labels. Translation in B from Russian to English: [Пловучий Морск(ой) Научный Институт, Ст. 108a 11/IX 1923, БулуШЬЯ губа Зал(ив) Гавриловский 1 отделение, Глуб(ина) места 2 м лова, Грунт ил серый и чёрный, Орудие лова овалЬнаЯ драга]. English translation: [Floating Marine Science Institute, St. 108a 11/IX 1923 Bulushja bay Gavrilovskiy bay 1 branch, Depth of place 2 m fishing, Bottom gray and black, Sampler oval dredge].
Supplemental material for: Automatic Debugging of Design Faults in MapReduce applications
<p>This is the supplemental material of the paper titled as “Automatic Debugging of Design Faults in MapReduce applications” published in IEEE Transactions on Software Engineering. <a href="https://doi.org/10.1109/TSE.2024.3369766" target="_blank" rel="noopener">Link</a></p> <p> </p> <p>It contains both the test cases used in the evaluation and the statistical analysis to reproduce the experiments. The supplemental material contains the following files:</p> <ul> <li>1_testCases.zip: all test cases randomly generated for the experiments. The description of the test cases is in ./1_testCases/README.txt</li> <li>2_executionTestCases.zip: the aggregated data obtained after the execution of the test cases in the debugging techniques: fault localization technique (MRDebug-FL), input reduction technique (MRDebug-IR) and the combination of both techniques (MRDebug-IR-FL). The folder contains csv with the results the experimentation unit, and they are detailed in the ./2_executionTestCases/README.pdf file.</li> <li>3_notebook.zip: jupyter notebook that contains the analysis done in the experiments. This notebook allows the interactive execution of statistical test and plots. The instructions to install the notebook are in the file 3_notebook.zip/installation.txt.</li> </ul> <p> </p> <p>To cite this work: </p> <p>J. Morán, A. Bertolino, C. de la Riva and J. Tuya, "Automatic Debugging of Design Faults in MapReduce Applications," in <em>IEEE Transactions on Software Engineering</em>, vol. 50, no. 4, pp. 956-978, April 2024, doi: 10.1109/TSE.2024.3369766</p>
Styrene monomer as potential material for functionalization and design of chromophores for new optoelectronic and NLO polymers conception: DFT study
Open the record for dataset details and reuse information.
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.