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”
Database and model code for "Material efficiency and climate change mitigation of passenger vehicles"
<p>This record provides all data points and model code necessary to compute the results presented in P. Wolfram, Q. Tu, N. Heeren, S. Pauliuk, E. Hertwich (2020) "Material efficiency and climate change mitigation of passenger vehicles", published in Journal of Industrial Ecology. All data is described in section 2 of the manuscript. The code can be run in MATLAB. </p>
Polish is quantitatively different on quartzite flakes used on different worked materials [R analysis]
<p>This upload includes the following files related to the R analysis:</p> <p>- Raw data as a CSV table (processing-quartzite-final.csv), i.e. results from the ConfoMap analysis (see <a href="https://doi.org/10.5281/zenodo.3979116">https://doi.org/10.5281/zenodo.3979116</a>)</p> <p>- RStudio project (Quantification quartzite final.Rproj)</p> <p>- R scripts as R Markdown files (*.Rmd)</p> <p>- R scripts knitted to HTML files (*.html)</p> <p>- An R script (RStudioVersion.R) to write the used version of RStudio to a text file (RStudioVersion.txt)</p> <p>- Output from script #1: processing-quartzite-final.Rbin and processing-quartzite-final.xlsx</p> <p>- Output from script #2: processing-quartzite-final_summary-stats.xlsx</p> <p>- Output from script #3: all plots as PDF files.</p> <p>Note that for running the scripts, the raw data files (processing-quartzite-final.csv, .Rbin and .xlsx) should be stored in a "Data" folder within the working directory.<br> Output (processing-quartzite-final_summary-stats.xlsx and PDF plots) were saved into "Summary-stats" and "Plots" folders, respectively.</p> <p>Zenodo does not allow sub-folders, so this folder structure had to be removed.</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p>
Polish is quantitatively different on quartzite flakes used on different worked materials [ConfoMap analysis]
<p>Each surface has been processed with two templates:</p> <p>1) Extract two 50x50 µm sub-areas and extract topography layer from each sub-area. Export sub-areas as SUR files. File names start with "A35" or "VSH4".</p> <p>2) Process all extracted sub-areas for quantitative analysis. File names start with "processing-quartzite-final".</p> <p>All ConfoMap templates are saved in MNT format (including all original and processed surfaces, as well as results). Each template has also been exported to a PDF file.</p> <p>Instructions to download all files at once are given here: <a href="https://doi.org/10.5281/zenodo.4011952">https://doi.org/10.5281/zenodo.4011952</a></p> <p>Additionally, the results of the second template are collated into "processing-quartzite-final.csv".</p>
Emotion and Diversity in Online Publics - Supporting Materials
<p>Supporting materials for the article "Counterpublic, Deliberative Sphere, Incubator, Battleground: Emotion and Diversity in Online Publics".</p> <p>"</p>
Phylogenetic signal in phonotactics: Supplementary materials
<p>Data, code and results for the paper <em>Phylogenetic signal in phonotactics </em>(<a href="https://doi.org/10.1075/dia.20004.mac">Macklin-Cordes, Bowern & Round, 2021</a>).</p> <p>Information and usage instructions are found in the <em>readme.txt </em>file and Section S3 of the paper's Supplementary Information.</p>
Supplementary Material - Maritime Cargo Prioritisation during a prolonged pandemic lockdown using an integrated TOPSIS-Knapsack technique
<p>Supplementary Material - Maritime Cargo Prioritisation during a prolonged pandemic lockdown using an integrated TOPSIS-Knapsack technique: A Case Study on Small Island Developing States – the Rodrigues Island</p> <p>Results and Sensitivity analysis</p>
Supporting material for Shintergy sinchronized brain and gravitational influence over laser, weight scale and chronometers
<p>Supporting material for Shintergy sinchronized brain and gravitational influence over laser, weight scale and chronometers</p> <p> </p> <p>ResearchGate paper and project:</p> <p>https://www.researchgate.net/publication/343671561_Effects_of_a_Shintergy-sinchronized_brain_over_a_laser_beam_chronometers_and_a_scale_weight_a_Possible_Fractal_Structure_of_Consciousness</p>
Supplementary material for the paper "Geologically old but freshly exposed rock fragments encountered by Yutu-2 rover"
<p>The derived data presented in figures 6 and 8, and the image IDs for producing figures 1, 2, 3/4, 5, and 7 in the paper "Geologically old but freshly exposed rock fragments encountered by Yutu-2 rover" are available in this data repository.</p>
Supplementary material (buffet data set): Egeler, G.-A., von Rickenbach, F., & Baur, P. (2020). Menüwahl in der Hochschulmensa: Design & Durchführung Feldexperiment (NOVANIMAL Kurzbericht). ZHAW. https://doi.org/10.21256/zhaw-1408
<p>During the fieldexperiment in the NOVANIMAL Project several informations about the offer of the buffet were collected. The report of the fieldexperiment see:</p> <p><a href="https://zenodo.org/deposit/4115429">Egeler, G.-A. & Baur, P. (2020). Menüwahl in der Hochschulmensa: Fleisch oder Vegi? Ergebnisse eines 12-wöchigen Feldexperiments (NOVANIMAL Working Paper No. 5). ZHAW. https://doi.org/10.21256/zhaw-1405</a></p>
Spectral Library of Impervious Urban Materials
<p>The radiative response of impervious urban materials is a highly influential surface property, due to its impacts on the radiation balance of incoming and outgoing long- and short-wave fluxes. Information about the material composition can be determined with data resolved to the wavelength level. Spectral reflectance in the visible- to short-wave infrared (VIS-SWIR) region is widely used in remote sensing-based land cover classification and spectral long-wave infrared (LWIR) emissivity is required for the observation of surface temperatures. The Spectral Library of impervious Urban Materials (SLUM) available from the London Urban Micromet data Archive (LUMA) includes LWIR emissivity spectra of 74 samples of impervious surfaces derived using measurements made by a portable Fourier Transform InfraRed (FTIR) spectrometer and matching short-wave reflectance spectra observed for each urban sample.</p> <p>The documentation (<a href="http://www.met.reading.ac.uk/micromet/documents/LUMA_SLUM.pdf">pdf</a>) contains photos, meta information for all 74 samples and plots of the short-wave reflactance (300-2500 nm) and long-wave (8-14 um) emissivity spectra.</p> <p>Data are provided in csv format for short-wave reflectance (LUMA_SLUM_SW.csv) and long-wave emissivity (LUMA_SLUM_LW.csv).</p> <p>Further details (including integrated broadband values of emissivity and albedo), methods and data analysis are presented in</p> <p>Kotthaus, S, TEL Smith, MJ Wooster, and CSB Grimmond 2014: Derivation of an urban materials spectral library through emittance and reflectance spectroscopy, <em>ISPRS Journal of Photogrammetry and Remote Sensing</em>, 94, 194–212. doi:10.1016/j.isprsjprs.2014.05.005</p> <p><strong>Please cite both this site and the paper above if you use this data</strong></p>
Supplementary Material for "Route Efficiency Assessment and Review of the Synthesis of β-Nucleosides via N-Glycosylation of Nucleobases"
<p>This is the external Supplementary Material for our publication "Route Efficiency Assessment and Review of the Synthesis of β-Nucleosides via <em>N</em>-Glycosylation of Nucleobases", which has been released as a preprint on <em>ChemRxiv </em>(https://doi.org/10.26434/chemrxiv.12753413.v1). The files in this record are additionally available from <em>ChemRxiv</em>.</p>
Ethical Perspectives in AI: A Two-folded Exploratory Study From Literature and Active Development Projects - Supplementary Material
<p>This is the Supplementary Material provided for the work accepted on HICSS 2021.</p> <p>Title of work: Ethical Perspectives in AI: A Two-folded Exploratory Study From Literature and Active Development Projects.</p> <p> </p> <p> </p> <p>This dataset depicts 589 GitHub README files explored in our article. We devised each repository into 4 categories. AI Applications (78), reference lists (486), Explainable AI tool (6), Ethical AI tool (15). Moreoveer, 4 repositories could not be found, and 181 of them had a Programming Language. In addition, we classified them according to our judgement of Interesting (82) or Great (33), regarding the objectives of our work. 75 repositories were not related to AI Ethics, and 7 of them mentioned COVID-19 in their repositories in some manner. Highlighted repositories in red pertain to categories 3 and 4, that is, tools for implementing AI Ethics, while those in yellow are marked as “Great”.</p> <p>Explainable AI tool and Ethical AI tool were added to 21 occurrences of tools for implementing AI ethics publicly available in repositories. Furthermore, it is seen that many papers open-sourced their codes on GitHub (as in https://github.com/lopusz/awesome-interpretable-machine-learning), meaning that the academic field has also made good progress in implementing ethics in AI, hence, the combined energy of both sources fosters an enhanced debate and stimulates progress towards AI ethics in practice.</p>
VR-Together Pilot 3: Geometry of living room, bedroom. Materials, textures and illumination
<p>VR-Together Pilot 3 geometry of living room and bedroom, materials, textures and illumination.</p> <p>This dataset contains de material created for the <a href="https://vrtogether.eu/about-vr-together/pilots/pilot3/">Pilot 3 of the VR-Together project</a>. In particular, it contains the following material:</p> <ul> <li>Geometry of the living room</li> <li>Geometry of the bedroom</li> <li>Objects</li> <li>Textures</li> <li>Illumination scheme</li> </ul> <p>All the previous material has been created in Unity.</p> <p>VR-Together has been funded by the European Commission as part of the H2020 program, under the grant agreement 762111.</p>
Datasets and Supporting Materials for the MALIN-ANR 2019 Competition (French national research agency)
<p>This "ZENODO deposit" provides a multiple sensor dataset collected by the CyborgLOC team during the intermediate competition of the Challenge MALIN (<em>MA</em><em>îtrise</em><em> de la </em><em>L</em><em>ocalisation </em><em>IN</em><em>door</em>), which is a competition for indoor/outdoor real-time positioning. The sensors, including a GNSS receiver Ublox NEO-M8N, a Realsense D435i stereo camera, three Xsens MTi-300 and one PERSY (<strong>PE</strong>destrian <strong>R</strong>eference <strong>SY</strong>stem), are mounted on different parts of the subject’s body. The PERSY is a foot-mounted positioning device with a tri-axial accelerometer, a tri-axial gyroscope, a tri-axial magnetometer as well as a GNSS receiver Ublox M8T. The two scenarios are designed in a training center of firefighters CFIS (Fire and Rescue Training Center) in Blois, France to simulate the situation of firefighters during interventions. With total distances around 2 km for each scenario, the travelled trajectories passed through challenging environments including indoor, outdoor, urban canyon. The indoor part contains different stair levels, from the underground up to the 6th floor. The travel modes are vehicles and pedestrians. Several classical activities of firefighters are realized such as walking, running, stair-climbing, side-walking, crawling, passing above/below obstacles, carrying a stretcher, ladder climbing, etc. High accurate ground truth of stationary points and enclosing volumes are provided by the organizers of the competition, i.e., the French Ministry of Defense (DGA: Direction Générale de l’Armement). Provided with raw data, they allow the evaluation of the positioning performances.</p> <p>To facilitate the use of our dataset under Rosbag format, a toolkit of python scripts named <em>MALIN Data Processing Tools</em> is provided on GitHub (<a href="https://github.com/4g-group/malin_data_processing_tools">https://github.com/4g-group/malin_data_processing_tools</a>). It allows merging Rosbags, converting Rosbag files to CSV files as well as republishing camera’s topics as decompressed data. Details about these processing tools could be found in the Readme file on the Github page. </p>
AlienRemover: data and materials
<p><em>AlienRemover</em> (<a href="https://gitlab.pasteur.fr/GIPhy/AlienRemover">https://gitlab.pasteur.fr/GIPhy/AlienRemover</a>) is a program to quickly discard alien reads (e.g. exogenous reads, host, cloning vectors) from FASTQ-formatted files. Alien bases are searched using a fast alien <em>k</em>-mer identification algorithm, and the removal criterion is determined by detecting (based on <em>k</em>-mers) a sufficient proportion of successive alien bases within high-throughtput sequencing (HTS) reads. To determine accurate default values for both <em>k</em>-mer length and sucessive alien base proportion, different datasets were build and stored in this repository.</p> <p> </p> <p><strong>► Athal_PhiX (<em>Arabidopsis thaliana</em> + PhiX reads)</strong></p> <p>This dataset was inferred from the 2x300 Illumina MiSeq reads associated to the SRA accession <a href="https://www.ncbi.nlm.nih.gov/sra/SRR726611">SRR726611</a>. These HTS reads correspond to the whole genome sequencing of <em>A. thaliana</em>, but also of <em>Escherichia</em> virus PhiX (used for control).</p> <p>Technical adapter and primer oligonucleotides were detected using <a href="https://www.ebi.ac.uk/research/enright/software/kraken/">Minion</a> (see documentation <a href="http://wwwdev.ebi.ac.uk/enright-dev/kraken/reaper/src/reaper-latest/doc/minion.html">here</a>), leading to the following ones:</p> <pre><code>>R1_TruSeq_Adapter_Index_22 AGATCGGAAGAGCACACGTCTGAACTCCAGTCACcgtacgTAATCTCGTATGCCGTCTTCTGCTTG >R2_TruSeq_Universal_Adapter_rc AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGTAGATCTCGGTGGTCGCCGTATCATT >poly-A AAAAAAAAAAAAAAA >poly-C CCCCCCCCCCCCCCC</code></pre> <p>Read pairs were clipped and trimmed using <a href="https://research.pasteur.fr/en/software/alientrimmer">AlienTrimmer v2.0</a>. Only read pairs made up by reads of length at least 220 bps were retained.</p> <p>To properly assign each remaining read pair to its taxon, they were aligned using <a href="https://github.com/lh3/minimap2">minimap2</a> against genome assemblies of <em>A. thaliana </em>(<a href="https://www.ncbi.nlm.nih.gov/assembly/GCF_000001735.4">GCF_000001735.4</a>) and PhiX174 (<a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_002588795.1">GCA_002588795.1</a>). Read pairs that do not align against these two genome assemblies were discarded. This procedure led to 6,378,237 read pairs: 6,343,954 (99.46%) and 34,283 (0.54%) are associated to <em>A. thaliana</em> and PhiX174, respectively.</p> <p>This read dataset corresponds to the two gzipped FASTQ files <code>Athal_PhiX.1.fastq.gz</code> and <code>Athal_PhiX.2.fastq.gz</code>. Each FASTQ block (i.e. 4-line block) associated to <em>A. thaliana</em> and PhiX has its first line starting with <code>@Arabidopsis_thaliana</code> and <code>@PhiX</code>, respectively.</p> <p> </p> <p><strong>► hCoV19_Hsap (SARS-CoV-2 + <em>Homo sapiens</em> reads)</strong></p> <p>This dataset was inferred from the 300 bps Illumina iSeq single-end reads associated to the SRA accession <a href="https://www.ncbi.nlm.nih.gov/sra/SRR12782936">SRR12782936</a>. These HTS reads correspond to the whole genome sequencing of a SARS-CoV-2 virus isolate, but contains alien reads from its human host.</p> <p>These reads were processed following a similar procedure as previously described (see above). Trimming and clipping were carried out with the following oligonucleotides:</p> <pre><code>>TruSeq_DNA AGATCGGAAGAGCACACGTCTGAACTCCAGTCACcctatggtATCTCGTATGCCGTCTTCTGCTTG >poly-A AAAAAAAAAAAAAAA >poly-C CCCCCCCCCCCCCCC</code></pre> <p>Taxonomic assignation was performed by aligning reads against genome assemblies of <em>H. sapiens</em> (<a href="https://www.ncbi.nlm.nih.gov/assembly/GCF_000001405.28">GCF_000001405.28</a>) and SARS-CoV-2 (<a href="https://www.ncbi.nlm.nih.gov/assembly/GCA_009858895.3">GCA_009858895.3</a>), leading to a total set of 392,404<br> single-end reads, made up by 222,945 (56.81%) SARS-CoV-2 and 169,459 (43.19%) and <em>H. sapiens</em> ones.</p> <p>This read dataset corresponds to the gzipped FASTQ file <code>hCoV19_Hsap.fastq.gz</code>. Each FASTQ block associated to SARS-CoV-2 and <em>H. sapiens</em> has its first line starting with <code>@SARS-CoV-2</code> and <code>@Homo_sapiens</code>, respectively.</p> <p> </p> <p><strong>► Homo.sapiens.*.kmr (<em>Homo sapiens k</em>-mers)</strong></p> <p><em>AlienRemover</em> is able to save into a file the different distinct <em>k</em>-mers associated to alien genomes. To quickly detect and remove alien reads within FASTQ files, these saved alien <em>k</em>-mers can next be directly read by <em>AlienRemover</em>, which is useful when dealing with large alien genomes. When analysing the dataset hCoV19_Hsap, the <em>H. sapiens</em> <em>k</em>-mers were therefore computed by <em>AlienRemover</em> and saved.</p> <p>The <em>H. sapiens k</em>-mer sets correspond to the 11 files <code>Homo.sapiens.k$k.kmr</code>, where <code>$k</code> is odd and varies between 11 and 31.</p>
Supplementary materials for "Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments"
<p>Supplementary materials for "Relative Information Gain: Shannon entropy-based measure of the relative structural conservation in RNA alignments". These include precalculated RNA Blocks, MBRs (Matrix of Bear encoded RNA), sPSSMs (structural Position Specific Scoring Matrix), RIG (Relative Information Gain) scores, and plots calculated for 3016 Rfam 14.1 families. In particular:</p> <ul> <li><strong>alignments.zip:</strong> zipped file containing the structural alignments for each Rfam family.</li> <li><strong>RNA_Blocks.zip</strong>: zipped file containing the RNA blocks used to derive different substitution matrices.</li> <li><strong>MBRs.zip</strong>: zipped file containing the substitution matrices.</li> <li><strong>sPSSMs.zip</strong>: zipped file containing the structural Position Specific Scoring Matrices.</li> <li><strong>RIGs.zip</strong>: zipped file containing the RIG scores.</li> <li><strong>entropy.zip</strong>: zipped file containing the (rescaled) entropy.</li> <li><strong>plots.zip</strong>: zipped file containing the plots. </li> </ul> <p>All the scripts to build all these files are available at <a href="https://github.com/helmercitterich-lab/RIG">https://github.com/helmercitterich-lab/RIG</a>.</p>
Culverts_Data_Suplementary_Materials
<p>The supplementary material contains the spreadsheet with input data and calculation results of the CMOOP algorithm application on the analyzed road section.</p>
Supplementary Materials for Genomic insight into Pediococcus acidilactici HN9, a potential probiotic strain isolated from the traditional Thai-style fermented beef Nhang
<p>Figure S1: Subsystem information of the HN9 based on the RAST annotation server, <br> Figure S2: Phylogenetic analysis of Pediococcus acidilactici HN9 and other strains at the species level, Figure S3: Sequence alignment of Enterolysin A from Pediococcus pentosaceus ATCC 25745 with Enterolysin A identified in the HN9, <br> Figure S4: Identification of bacteriocin-encoding genes from all bacterial strains in the genus Pediococcus, <br> Table S1: The information of strain used in this study, <br> Table S2: Metadata of all strains used in this study.</p>
The Elusive Book, or the Digitization of the Materiality[-ies] of Books
<p>13<sup>th</sup> Annual Schoenberg Symposium on Manuscript Studies in the Digital Age: <em>invited</em> <em>presentation - online delivery, ‘The Elusive Book, </em><em>or the Digitization of the Materiality[-ies] of Books’</em> (18/11/2020)</p> <p>Abstract</p> <p>The digitization of books is generally understood as the capture of the page contents through photography and imaging. Not all features of books can be digitally acquired in this manner— we will refer to these as <em>untransferable</em> characteristics— and models and descriptive metadata are necessary steps to computerize important information about the structure and materiality of documents. Digitization, in fact, can do much more than reproducing books as texts to be read, and books are much more than flat sequences of pages: there is much information in books that has been largely ignored— so far. Among these, we find the physical form of books (e.g., bindings, the form and materials of its pages, inks, decorations, usage accretions, stains, and so on). While digitization tends to concentrate on the remediation of the content of books, we argue for an increased interest in the transmediation of the materiality of books. This digital representation and manipulation of an object’s materiality is achieved through a number of means, metadata designation being one of the most established processes to bring these <em>untransferable</em> features into the digital. Digital surrogates created in this manner have the potency to be more than mere replacements of the original objects. Instead, when the transformative nature of the digitization process is more fully harnessed, they can become digital cultural objects: digital objects that transcend the originals, work in synergy with them, and make them something more.</p> <p>Bio</p> <p>Alberto Campagnolo trained as a book conservator at the European Course for Conservators/Restorers of Book Materials (1998-2001) in Spoleto, Italy and has worked in that capacity in various institutions, amongst which the National Museum Wales, London Metropolitan Archives, St. Catherine’s Monastery (Egypt), and the Vatican Library. He studied Conservation of Library and Archive Materials (2001-2006) at Ca’ Foscari University Venice, Italy and then read for an MA in Digital Culture and Technology (2007-2009) at King’s College London. He pursued a PhD (2010-2015) on an <a href="http://ualresearchonline.arts.ac.uk/8749/">automated visualization of historical bookbinding structures</a> at the <a href="https://www.ligatus.org.uk/">Ligatus Research Centre</a> (University of the Arts, London). He is an adjunct professor of Digital Humanities at the University of Udine, Italy (2018-ongoing). Alberto has been collaborating (2013-ongoing) with Dot Porter (Schoenberg Institute for Manuscript Studies, University of Pennsylvania) on <a href="https://viscoll.org/">VisColl</a>, a modelling and visualization tool for the gathering structure of books in codex format. Since 2018 he has been an acting member of the <a href="https://iada-home.org/">IADA</a> board. He has been part of the Editorial board of the <a href="https://www.tandfonline.com/toc/yjpc20/current">Journal of Paper Conservation</a> since 2016, and he is now co-editor in-Chief with Aurélie Martin.</p>
Training data for 'Genome annotation with Maker' tutorial (Galaxy Training Material)
<p>The data provided here are part of a Galaxy Training Network tutorial for genome annotation with Maker.</p> <p>It is based on data used in <a href="http://weatherby.genetics.utah.edu/MAKER/wiki/index.php/MAKER_Tutorial_for_WGS_Assembly_and_Annotation_Winter_School_2018">another Maker tutorial</a>.</p> <p>The full genome was <a href="https://www.ncbi.nlm.nih.gov/genome/?term=Schizosaccharomyces%20pombe[Organism]&cmd=DetailsSearch">downloaded from NCBI</a>, and mitochondria sequence removed from it for simplicity.</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.