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.
12,393
datasets available to search
ShareScore release 0.9.0
Dataset results
12,393 results for “Materiality”
Dataset of comprehensive Full-notch creep tests (FNCT) of selected high-density polyethylene (PE-HD) materials
<p>The dataset provided in this repository comprises data obtained from a series of full-notch creep tests (FNCT) performed on selected high-density polyethylene (PE-HD) materials (for further details, see section 1 Materials in this document) in accordance with the corresponding standard ISO 16770 [1]. </p><p>The FNCT is one of the mechanical testing procedures used to characterize polymer materials with respect to their environmental stress cracking (ESC) behavior. It is widely applied for PE-HD materials, that are predominantly used for pipe and container applications. It is based on the determination of the time to failure for a test specimen under constant mechanical load in a well-defined and temperature controlled liquid environment. The test device used here also allows for continuous monitoring of applied force, specimen elongation and temperature.</p>
Dataset for the paper "A framework for robotic excavation and dry stone construction using on-site materials"
<p>Stone data from the <i>Science Robotics</i> paper "A framework for robotic excavation and dry stone construction using on-site materials" containing:</p><ul><li>Mesh files of 1,100 stones (quarried boulders, erratics, and concrete debris) that were digitized by the autonomous excavator HEAP<ul><li><a href="https://zenodo.org/api/records/10038881/draft/files/1100%20Unprocessed%20Stone%20Meshes.zip/content">1100 Unprocessed Stone Meshes.zip: </a>Raw mesh files directly from the poisson reconstruction of accumulated LiDAR points, containing some artifacts and floating geometries</li><li><a href="https://zenodo.org/api/records/10038881/draft/files/1100%20Closed%20Stone%20Meshes.zip/content">1100 Closed Stone Meshes.zip: </a>Clean, closed, downsampled meshes</li><li><a href="https://zenodo.org/api/records/10038881/draft/files/Stone_Shape_Properties.csv/content">Stone_Shape_Properties.csv: </a>Properties file with a list of the stone IDs (IDs in the 1xxx and 3xxx range typically correspond to concrete elements) and select shape properties</li></ul></li><li>A dataset of candidate placements from automatically generated stone walls. The candidate placement data zip files contain:<ul><li><a href="https://zenodo.org/api/records/10038881/draft/files/Candidate_Placement_Data-npy.zip/content">Candidate_Placement_Data-npy.zip: </a>SDF (.npy) representation of each candidate, with three channels of 32x32x32 for distances to the stone, the already-placed stones, and the target wall</li><li><a href="https://zenodo.org/api/records/10038881/draft/files/Candidate_Placement_Data-pcd.zip/content">Candidate_Placement_Data-pcd.zip: </a>Point cloud (.pcd) representations of each candidate, with separate files for the placed stone, target wall (search volume), and already-placed stones (where they exist)</li></ul></li><li><a href="https://zenodo.org/api/records/10038881/draft/files/sdf_classifier.zip/content">sdf_classifier.zip: </a>Python examples:<ul><li>Rendering the three channel SDF data to mesh geometry using marching cubes and libigl</li><li>Candidate SDF classification using the pretrained model</li></ul></li><li>Candidate attributes and labels<ul><li><a href="https://zenodo.org/api/records/10038881/draft/files/candidate_attributes_labels.csv/content">candidate_attributes_labels.csv: </a>CSV file containing a list of UUID's corresponding to each candidate placement in the dataset. For each candidate, additional information is included about the dimensions and location of the solution, together with the (subjectively) hand-labelled binary value for placement viability. </li></ul></li><li><a href="https://zenodo.org/api/records/10038881/draft/files/README.md/content">README.md: </a>An additional readme with some details on the attributes file</li></ul><p>If you use this data in your research, please cite the <a href="https://www.science.org/doi/10.1126/scirobotics.abp9758">journal article</a>.</p><p> </p>
Supplementary material Comparative Genomic Analysis of Antimicrobial-Resistant Escherichia coli from South American Camelids in Central Germany
<p>Supplementary material for publication González-Santamarina, B.; Weber, M.; Menge, C.; Berens, C. Comparative Genomic Analysis of Antimicrobial-Resistant <i>Escherichia coli</i> from South American Camelids in Central Germany. <i>Microorganisms</i> <strong>2022</strong>, <i>10</i>, 1697. https://doi.org/10.3390/microorganisms10091697 </p>
Supplementary material (part 2) for "On the effect of tributary valleys on thermally driven winds in the main valley: a case study in the Inn Valley"
<p>Part 2 of the supplementary material for the master's thesis "On the effect of tributary valleys on thermally driven winds in the main valley: a case study in the Inn Valley." (Deidda 2023, available at <a href="https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-134436">https://resolver.obvsg.at/urn:nbn:at:at-ubi:1-134436</a>). The supplementary material consists in two parts: part 1 includes scripts, datasets, model setup files and figures (available at <a href="https://zenodo.org/records/8089010">https://zenodo.org/records/8089010</a>), while part 2 includes the model output needed to create the figures (see description below).</p><p>This directory contains part of the model output used for the thesis. The model used is WRF-ARW version 4.4 (Skamarock et al. 2021). Information on the model setup is available in the thesis, Section 2.2. For storage limitations, only the files needed to create the graphs presented in the thesis are available.</p><p>The file format is <i>type_domain_date.nc </i>where <i>domain</i> is "d01" or "d02" (respectively for the outer or inner domain, see Section 2.2 in the thesis), while <i>type</i> is "wrfout", "mean_out", or "Averaged", where:</p><ul><li>"wrfout" is the instantaneous WRF output;</li><li>"mean_out" is the time-averaged WRF output, computed using the fork <a href="https://github.com/matzegoebel/WRFlux">WRFlux</a>.</li><li>"Averaged" is a combination of time-averaged and instantaneous outputs. These files were created using the the script <i>Create_intermediate_files.py, </i>available in the <a href="https://zenodo.org/records/8089010">software directory </a>(in Scripts.zip). These files were computed to have a lighter and WRF-like formatted data containing the averaged fields needed for the analysis.</li></ul>
Characterization of Functionalized Chromatographic Nanoporous Silica Materials by Coupling Water Adsorption and Intrusion with Nuclear Magnetic Resonance Relaxometry
<p>This data publication is based on the metadata and datasets underlying the manuscript "Characterization of Functionalized Chromatographic Nanoporous Silica Materials by Coupling Water Adsorption and Intrusion with Nuclear Magnetic Resonance Relaxometry" (<a href="https://doi.org/10.1021/acsanm.3c04330"><span>https://doi.org/10.1021/acsanm.3c04330</span></a>)</p> <p>Included are the datasets used, raw and processed data of Adsorption measurements (Water, Ar 87K, N2 77K), Water Intrusion measurements, NMR Relaxometry and solid state MAS NMR measurements. More information can be found in the Readme file.</p> <p> </p>
Material adicional de Ex cenobio Sancti Ysidori Lengionensis usque ad Bibliothecam Regiam Belgicam: De partidas, cronicones y sermones romances
<p>Material adicional al artículo publicado en <i>Incipit</i> 43 (2023).</p>
Supplementary Material for "Aiding the Design of Critical Software Systems by Iterative Exploration of Distinct Requirement Violation Scenarios"
<p>This dataset provides artifacts about an industrial case study of a Steer-by-Wire system. It collects models of the system modeled in the open-source Gamma Statechart Composition Framework. You can find more information about the framework here: <a href="https://github.com/ftsrg/gamma">https://github.com/ftsrg/gamma</a>.</p>
Hyperspectral photoluminescence and reflectance microscopy of 2D materials
<h2>Description of Uploaded Raw Data and Programs for Recreating Figures</h2><h3>Raw Data</h3><p>The raw data in this dataset is primarily in ".sif" binary format, which is used in the creation of Figures 2, 3, 4, and Supplementary Information (SI) Figure 2 in the paper. The ".sif" files contain spectrum data. The data for Figure 3 also includes focal data provided as .png and intensity line-cuts in .csv files.</p><p>A Python program, "load_sif.py", is included in the dataset to read and process these ".sif" files.</p><h3>Software and Programs</h3><p>The figures in the paper were generated using Python programs, which are included in the dataset. These programs are:</p><p>for Figure 2:<i> RClf_calibration.py </i></p><p>for Figure 3: <i>knife_edge_measurement.py </i>and <i>plot_intensity_profile_imageJ.py </i></p><p>for Figure 4 as well as SI Figure 1: <i>PL_linefocus_2color.py, PL_fit_image.py, PL_line_fit.py, RC_linefocus_2color.py </i>and<i> RC_line.py </i></p><p>for SI Figure 2: <i>BG_spectum_PL.py </i>and<i> Ref_spectum_RC.py </i></p><h3>Steps to Recreate Figures</h3><p>Download the zipped folder for each figure. The Python programs are using the ".sif", ".png", and ".csv" files from the downloaded folder.</p><p>Please ensure you have the appropriate software to run these Python programs and handle the provided file formats.</p>
Supplementary material for "Exploring Conceptual Data Modeling Processes: Insights from Clustering and Visualizing Modeling Sequences"
<p>This material supplements the following conference publication:</p> <p>Winkler, Rosenthal, Strecker (2024). "Exploring Conceptual Data Modeling Processes: Insights from Clustering and Visualizing Modeling Sequences". Modellierung 2024.</p>
Fig. 17. Unidentified material from Aixheim, collected from the Stubensandstein. A in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 17. Unidentified material from Aixheim, collected from the Stubensandstein. A. GPIT-PV-60390, fragment of a scapular blade in lateral view. B. GPIT-PV-60400, serrated conical tooth. C. GPIT-PV-60401, fragment of a vertebra. D. GPIT-PV-60402, indeterminate bone fragment. E. GPIT-PV-60403, rib fragment. F. GPIT-PV-60404, indeterminate bone fragment. G. GPIT-PV-60405, rib fragment. H. GPIT- PV-60406, bone fragment. I. GPIT-PV-60407, rib fragment. J. GPIT-PV-60408, zygapophysis. K. GPIT- PV-60409, rib shaft fragment. L. GPIT-PV-60410, zygapophysis. M. GPIT-PV-60411, rib fragment. N. GPIT-PV-60412, zygapophysis. O. GPIT-PV-60413, ventral margin of centrum. P. GPIT-PV-60414, fragment of a phalanx. Q. GPIT-PV-60415, fragment of a phalanx. R. GPIT-PV-60416, partial phalanx.
Supplementary Materials for SE Carter PhD Thesis
<p>Included:</p> <p>- Additional Phase I: Value and Privacy Preference Survey graphs (see Version 1)</p> <p>- VcPA Profile Design Graphs and Statistics for Phase II: Mock App Store Study (v2 includes correct cluster numbers)</p> <p>- Code List for Phase III: Semi-Structured Interviews (see Version 1)</p>
Supplementary Material on "Processes, Methods, and Tools in Model-based Engineering --- A Qualitative Multiple-Case Study"
<p>This dataset provides the supplementary material that we applied for all interviews conducted in the context of our qualitative study resulting in the JSS article mentioned in the title:</p> <ul> <li>The semi-structured interview guide,</li> <li>the codebook,</li> <li>the blank consent form that our interviewees signed,</li> <li>and the blank invitation mail that we used to ask our interviewees to participate in our study.</li> </ul>
Analyzing the Human Recommendation Community 'ifyoulikeblank' on Reddit — Auxiliary materials
<p>This repository contains auxiliary materials for the iConference 2024 paper "“If I like BLANK, what else will I like?”: Analyzing<br>a Human Recommendation Community on Reddit" by Thi Binh Minh Cao and Toine Bogers (= corresponding author)</p> <p>Published in: <em>Proceedings of the 2024 iConference</em>, April 15--26, 2024, Changchun, China.</p> <p>The paper presents the results of an analysis of /r/ifyoulikeblank, a Reddit community dedicated to requesting and providing for recommendations. This repository contains the following auxiliary materials:</p> <ul> <li>The annotated sample of threads from the /r/ifyoulikeblank subreddit (<strong>annotated-dataset.xlsx</strong>). The second sheet in the Excel file explains the contents of the file.</li> <li>The R code for performing the analysis described in the paper (<strong>annotation-analysis.R</strong>)</li> <li>CSV file containing the genres attributed to the artists as crawled from the Spotify API (<strong>artist-spotify-genres.csv</strong>)</li> <li>CSV file containing the popularity scores crawled from the Spotify API for the seed items and Spotify recommendations (<strong>recommendation-popularity.reddit-vs-spotify.csv</strong>)</li> <li>CSV file containing the popularity scores crawled from the Spotify API for the Reddit (<strong>recommendation-popularity.reddit.csv</strong>)</li> <li>The stopwords file used in the textual analysis (<strong>stopwords.csv</strong>)</li> <li>Excel file containing the activity data for the /r/ifyoulikeblank subreddit (<strong>subreddit-stats.xlsx</strong>)</li> </ul>
PROCRAFT Final Meeting - Material study on the aircraft of the Deutsches Museum by Marisa Pamplona – Deutsches - Museum
Open the record for dataset details and reuse information.
arxiv_supplementary_material_User_study_dataset
<div> <div>**Supplemental Material Description for "Expanding Horizons in HCI Research Through LLM-Driven Qualitative Analysis"**</div> <br> <div>The Excel workbook titled `arxiv_supplymentary_material_User_study_dataset.xlsx` provided as supplementary material holds the dataset necessary for understanding the evaluation methods used in the study. The contents are organized into several sheets, described as follows:</div> <br> <div>1. **Paper**: In this sheet, the research paper selection is listed, including an identifier (ID), the title of the paper, its publication year, the venue where it was presented, the DOI, and information regarding the availability of raw data. This dataset only includes papers that offer open access to raw participant data for qualitative analysis, foundational to the research process.</div> <br> <div>2. **GPT_paper_summary**: This sheet contains summaries of the selected papers, created using GPT-4. Included for each paper are the ID, the title, and the GPT-4-generated summary, which were required by the system for initializing the analysis.</div> <br> <div>3. **G1, G2, … , G5**: Recorded in these tabs are the results from multiple rounds of applying the evaluation system. Each 'Gx' tab corresponds to one trial, and contains both the paper ID as well as the qualitative comments crafted by the LLM, mirroring the deductive reasoning typically manifest in human analysis.</div> <br> <div>It is important to note that the data shared excludes any material that is not cleared for public release, including full-text articles and the raw responses of the study participants. The dataset, therefore, aligns with copyright and privacy policies while providing an adequate basis for verification and exploration by other researchers.</div> <br> <div>The LLM-generated discussions are compared with the original papers' discussions to assess the capabilities of LLMs in reconstructing meaningful narrative in the absence of the source material. This dataset supports the credibility of the study's outcomes and presents an opportunity for others in the field to undertake similar research endeavors.</div> </div>
CatVolc: A new database of geochemical and geochronological data of volcanic-related materials from the Catalan Volcanic Zone (Spain)
<p>The Catalan Volcanic Zone (CVZ) (NE Spain) consists of an intraplate alkaline volcanic zone associated with the opening of the Western Mediterranean and the development of the European Rift System. Volcanic activity in the CVZ started in the L’Empordà area (ca. > 12 - 8 Ma), extended to La Selva (7.9 - 1.7 Ma), and finally migrated to the Garrotxa Volcanic Field (< 0.7 - 0.01Ma). Despite the scientific interest in the CVZ since the early 19th century, certain aspects remain poorly constrained. These include a full understanding of the spatial and temporal evolution of the magma plumbing system and ascent mechanisms, as well as the chronology of volcanism across the CVZ. Addressing these unresolved questions requires geochemical, petrological, and geochronological data, which, in the case of the CVZ, are scattered and have never been integrated or analyzed within a unified framework. Here, we present the CatVolc (Catalan Volcanism) database, which compiles available geochemical and geochronological data of volcanic-related materials of the CVZ. For each sample, the CatVolc database lists general information about the sampling site, sample lithology, whole-rock analyses (including major and trace elements), isotopic ratios, mineral chemistry, and radiometric/thermoluminescence dating information, if available. A preliminary analysis of the information contained in the CatVolc database highlights the critical limitations of the current state of knowledge and allows suggesting potential future directions for volcanic-driven investigations in the CVZ. Additionally, the results obtained validate the CatVolc database as a key tool for comprehending the spatial and temporal evolution of the magmatic system(s) and volcanic activity in the CVZ, particularly in the Garrotxa Volcanic Field. This aspect is critical for advancing in the assessment of the volcanic hazards in the region and for gaining a comprehensive understanding of future volcanic activity.</p> <p>The current database version consists of three MS Excel files dedicated to primary magmatic rocks (<em>CatVolc_magmatic_rocks.xlsx</em>), xenoliths (<em>CatVolc_xenoliths.xlsx</em>) and radiometric/thermoluminescence dating information (<em>CatVolc_dating.xlsx</em>). Each MS Excel file is structured around a main table (<em>Samples_general_info</em>) containing general information (e.g., location, age, sampling site) of the listed samples, and a certain number of secondary tables. Secondary tables included in the MS Excel files for magmatic rocks and xenoliths report: (i) whole-rock geochemistry (<em>Major_elements</em> and <em>Trace_elements</em>); (ii) isotopic relations data (<em>Isotopic_relations</em>); and (iii) mineral and volcanic glass chemistry (<em>Amphibole</em><strong>, </strong><em>Feldspar</em><strong>, </strong><em>Felspathoid</em><strong>, </strong><em>Glass</em><strong>, </strong><em>Mica</em><strong>, </strong><em>Olivine</em><strong>, </strong><em>Pyroxene</em><strong>, </strong><em>Oxides</em><strong>, </strong><em>Serpentines</em><strong> </strong>and<strong> </strong><em>Sulphides</em><em>)</em>. In addition to the <em>Samples_general_info </em>table, the <em>CatVolc_dating.xlsx </em>also includes radiometric/thermoluminescence dating information (<em>Dating</em>). Finally, in all three Excel files, we have incorporated a table with consulted references (<em>References</em><em>) </em>and a glossary of the acronyms used for the parameters included in the main and secondary tables (<em>Codes</em>). </p> <p> </p>
Supplementary material for "Mutual predictiveness of sound correspondences for reconstruction and language subgrouping: The case of Gyalrongic preinitials"
<p>This is the supplementary material of the paper "Mutual predictiveness of sound correspondences for reconstruction and language subgrouping: The case of Gyalrongic preinitials", to be published in Diachronica. It includes the datasets, codes and images involved in the research. Publication is still several months away, and I am trying to collect and identify more cognates as well as correct mistakes. </p> <p>Version 2 has included a few more cognates. I have added a file explaning my cognate judgements and annotations, and removed some doubtful forms after verification with native speakers. </p> <div> <div> <div> <div> <p>Comments, corrections and suggestions about cognate judgement, annotation and bibliographical references are welcome. I will correct and update the data from time to time.</p> </div> </div> </div> </div> <p> </p>
Fig. 1 in Examination of nontraditional materials for microvertebrate screenwashing
Fig. 1. Photograph showing how the screenwashing setup can be arranged in a small space. Each bucket contains the nested nylon bags holding the matrix and cinched shut with a nylon rope. The rope is then looped around a wooden brace to prevent the bags from sitting on the bottom of the bucket. The braces are also useful for pulling the bags in and out of the water for agitation before drying. The set up for screenwashing with paint sieves (not pictured) is the same, including the use of the braces.
Supporting material for von Fromm et al (2024) Global synthesis of SOC abundance and persistence profile data
<p>This file contains the supporting material for von Fromm et al (2024) Controls and relationships of soil organic carbon abundance and persistence vary across pedo-climatic regions published in Global Change Biology (https://doi.org/10.1111/gcb.17320). </p> <p>The data comes originally from the International Soil Radiocarbon Database (ISRaD; <a href="https://soilradiocarbon.org/">https://soilradiocarbon.org/</a>). We filtered the data and applied a mass-preserving spline function. For more details see the corresponding manuscript and the github repository (https://github.com/SophievF/Global_SOC_Abundance_Persistence).</p>
Supplementary material from: Prediction of the Cold Flow Properties of Biodiesel using the FAME Distribution and Machine Learning Techniques
<p><span>The dataset is divided into three sections within the worksheet.</span></p> <p><span> </span><span>The first section contains the definition of the data's feedstock and its source reference. The reference includes the year, DOI (if available, as some are collected from books), publication journal, article title, and authors.</span></p> <p><span> </span><span>The second section describes the FAME distribution, starting from C4:0 up to C24:0, including a column of unidentified FAMEs.</span></p> <p><span><span>The third and final section describes the measured properties Cloud Point (CP), Cold Filter Plugging Point (CFPP) and Pour Point (PP).</span></span></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.