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.
328
datasets available to search
ShareScore release 0.9.0
Dataset results
328 results for “Analysis results”
Gait analysis results for different pediatric prosthetic knee prescription protocols
<p>Traditionally, children who need a prosthetic knee joint are not provided with one in their first prosthesis. An alternative Early Knee protocol provides a flexing knee in the first prosthesis. The purpose of this multi-site study was to examine kinematic outcomes during walking in separate groups of young children in an Early prosthetic knee prescription protocol (EK) versus a traditional prosthetic knee protocol (TK), along with a population of children without lower limb amputations. Eighteen children aged 12 months to five years were recruited for this study at two clinical sites, six in each of the three groups. Children in the two prosthesis groups had unilateral limb loss and had been treated at one site with the TK protocol or at another with the EK protocol. All children walked at self-selected speed while kinematic data were collected using similar Vicon motion analysis systems. Data include joint angles, extrema, and ranges of motion used for the determination of temporal and spatial gait parameters and swing-phase clearance adaptations. </p>
InSAR time series analysis results of ALOS-2/PALSAR-2 data for the post-eruptive displacement of the 2015 phreatic eruption of Hakone volcano, Japan
<p>This repository contains the InSAR products used in Doke et al., GRL (submitted).</p> <p> </p> <p><strong>Dataset 1</strong>: Surface velocity data estimated by InSAR time series analysis with NetCDF grid format.</p> <ol> <li>surface_velocity_p126.nc</li> <li>surface_velocity_p18.nc</li> </ol> <p> </p> <p><strong>Dataset 2</strong>: Time-series of LOS displacements in selected locations with text format.</p> <ol> <li>time_series_p126.txt</li> <li>time_series_p18.txt</li> </ol> <p> </p> <p><strong>Dataset 3</strong>: Inputs and results of model inversion with shapefile.</p> <p>Subsampled observation data, modeled (simulated) displacements, and other parameters are shown in attribute tables in shapefiles. Shapefiles that show the location of the estimated models are also included in ZIP files.</p> <ol> <li>point_source_deflation.zip</li> <li>sill_deflation.zip</li> </ol>
Results for paper ""An adaptive, hanging-node, discontinuous isogeometric analysis method for the first-order form of the neutron transport equation with discrete ordinate (S_N) angular discretisation"
<p>This spreadsheet contains the results used to generate the plots in the paper "An adaptive, hanging-node, discontinuous isogeometric analysis method for the first-order form of the neutron transport equation with discrete ordinate (S_N) angular discretisation".</p>
Appendix_Results_of_quantitative_qualitative_analysis (42-language sample)
<p>A dataset showing results of quantitative and qualitative analysis on the basis of a 42-language sample.</p>
Appendix_results_qual_analysis_summarized (42-language sample)
<p>A .pdf file that plots verb scores (1 to 3) in main and adverbial clauses in the sample languages covered by the CIEP (42-language sample).</p>
Analysis of heme and iron influence on Porphyromonas gingivalis A7436 and ATCC 33277 strains genes expression (microarray results)
<p>The aim of this study was to analyze phenotypic differences between <i>P. gingivalis</i> more virulent A7436 and less virulent ATCC 33277 (33277) strains. The analysis comprised the influence of heme and iron on <i>P. gingivalis</i> gene expression. </p><p><i>P. gingivalis</i> A7436 and 33277 strains were cultured in basal medium (3% trypticase soy broth and 0.5% yeast extract), supplemented with 3.6 mM L-cysteine hydrochloride, and 0.5 mg/l menadione, in anaerobic conditions (80% N2, 10% H2 and 10% CO2). To generate heme and iron-limited conditions, the medium was supplemented with 0.16 mM of the iron chelator 2,2-dipyridyl (DIP conditions). To generate heme and iron-rich conditions, the medium was supplemented with 0.0077mM hemin chloride (Hm conditions). Three sample replicates of A7436 and 33277 strains were grown in Hm or DIP conditions for 20 hours. RNA isolation and microarray analysis were performed in IMGM laboratories (Martinsried, Germany), as described by Śmiga et al. (2023).</p><p>The online tool eArray (http://earray.chem.agilent.com/; Agilent Technologies, Santa Clara, CA, USA) was used to design an Agilent Custom <i>Porphyromonas gingivalis</i> A7436 Gene Expression Microarray (8×15K format). Probes were prepared based on <i>P. gingivalis</i> transcriptome information derived from the NCBI reference sequence NZ_CP011995.1. Total RNA isolation, RNA quantity, and quality were determined as described by Curaszkiewicz et al. 2014. For internal labeling control, the total RNA was spiked with <i>in vitro </i>synthesized polyadenylated transcripts (One-Color RNA Spike-In Mix; Agilent Technologies). Subsequently, samples were reverse transcribed into cDNA and then converted into cyanine-3-labeled complementary RNA (cRNA) with Low Input Quick-Amp Labeling Kit One-Color (Agilent Technologies). For microarray hybridization, a Gene Expression Hybridization Kit (Agilent Technologies) was used. Labeled cRNA was hybridized for 17 hours at 65℃ on Agilent Custom GE 8×15K Microarrays, washed according to the manufacturer's protocol, and dried with acetonitrile (Sigma-Aldrich). The fluorescence of samples was detected with Scan Control A.8.4.1 software (Agilent Technologies) on the Agilent DNA Microarray Scanner (Agilent Technologies) and extracted from the images using Feature Extraction 10.7.3.1 software (Agilent Technologies). For data analysis, Feature Extraction 10.7.3.1 (Agilent Technologies), GeneSpring GX 13.1.1 (Agilent Technologies), and Excel 2010 (Microsoft, Redmond, WA, USA) were used. For statistical analysis, Welch's approximate <i>t</i>-test was used. Differences in gene expression are shown as fold change values (FC). The average was calculated from the normalized signal values and they were transformed from the log2 to the linear scale. Increases and decreases in gene expression are shown as positive and negative numbers, respectively. The fold change in gene expression was considered significant for FC ≥ 2 or FC ≤ -2 and <i>P</i>-value ≤ 0.05</p><ul><li>Ciuraszkiewicz J, Śmiga M, Mackiewicz P, Gmiterek A, Bielecki M, Olczak M, Olczak T. 2014. Fur homolog regulates <i>Porphyromonas gingivalis </i>virulence under low-iron/heme conditions through a complex regulatory network. Mol Oral Microbiol 29:333-353. doi: 10.1111/omi.12077.</li><li>Śmiga M, Ślęzak P, Olczak T. 2023. Comparative analysis of <i>Porphyromonas gingivalis</i> A7436 and ATCC 33277 strains reveals differences in the expression of heme acquisition systems. Microbiol Spectr (revised manuscript under revision).</li></ul>
Photoactivation of the Orange Carotenoid Protein Requires Two Light-Driven Reactions Mediated by a Metastable Monomeric Intermediate – Absorption Spectra and Global Analysis Results, Molecular Dynamics Simulations
<p>Time-resolved absorption and molecular dynamics trajectory datasets associated with: Rose, J. B.; Gascón, J. A.; Sutter, M.; Sheppard, D. I.; Kerfeld, C. A.; Beck, W. F. Photoactivation of the Orange Carotenoid Protein Requires Two Light-Driven Reactions Mediated by a Metastable Monomeric Intermediate. <i>Phys. Chem. Chem. Phys.</i> <strong>2023</strong>, DOI: 10.1039/d3cp04484j.</p>
Results from DSC analysis over glass fibre reinforced SMC (50009092 grade by Menzolit supplier)
<p>Results from DSC analysis over glass fibre reinforced SMC automotive grade (50009092 grade provided by Menzolit supplier)</p>
Results from DSC analysis over glass fibre reinforced SMC (50007150 grade by Menzolit supplier)
<p>Results from DSC analysis over glass fibre reinforced SMC for automotive applications (50007150 grade provided by Menzolit supplier)</p>
Appendix #2: Results of quntitative and qualitative analysis
<p>An unprocessed .xlsx document showing the results of quantative and qualitative analysis on the 45-language sample.</p>
Results and analysis script from a discrete choice experiment assessing public preferences for rewilding in the Oder Delta
<p>1. Rewilding is an emerging paradigm in restoration science, and is increasingly gaining popularity as a cost-effective ecosystem restoration option. A rewilding framework was recently proposed that contains three integral components: restoring trophic complexity, allowing for stochastic disturbances, and enhancing species' potential to disperse. However, as of yet, there has been limited quantitative analysis looking at public preference for rewilding and each of its elements.</p> <p>2. We used a discrete choice experiment approach to determine public preference for rewilding in the Oder Delta. The unique geographical context of the Oder Delta, spreading evenly across two countries, allowed us to analyze differences between the German (n = 1,005) and Polish (n = 1,066) samples.</p> <p>3. In both countries, we found respondents were willing to pay for rewilding interventions when compared against a status quo option. Notably, preferences were strongest for restoring trophic complexity through promoting the comeback of large mammals.</p> <p>4. In addition, we found respondents living locally to the study region had significantly different preferences than the nationwide samples, exhibiting negative willingness to pay for the restoration of natural flooding regimes and the presence of large predator species.</p>
Results of the diahaline overturning analysis for the Persian Gulf
<p>This archive stores the main model results and the script for the diahaline analysis of the Persian Gulf using GETM model results in the draft submitted to Geophysical Research Letters: "Diahaline overturning and mixing in a semi-enclosed marginal sea with excess evaporation" by Lorenz, Klingbeil & Burchard</p>
Results of Mothra analysis of all iCollections butterflies
<p>Results of Mothra analysis of all iCollections butterflies including analysis pipeline files. This dataset supports the publication: "Applying computer vision to digitised natural history collections for climate change research: temperature-size responses in British butterflies"</p>
WP2 Task 2.4 Multi Actor Approach survey results and analysis
<p>WP2 Task 2.4 Multi Actor Approach survey results and analysis</p>
Inputs and results of "A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.'s case"
<p>This repository contains the datasets and visualizations generated in our work: <strong>"A qualitative and quantitative analysis of open citations to retracted articles: the Wakefield 1998 et al.’s case"</strong>.</p> <p><strong>Note:</strong> the data are all contained inside the <strong><em>data.zip</em> </strong>file. You need to unzip the container to get access to all the files and directories listed below.</p> <p>The data (citations) gathered accompanied by their annotated characteristics are stored in <strong><em>data/</em>:</strong></p> <ul> <li><em><strong>"cits_features.csv": </strong></em>a dataset containing all the entities (rows in the CSV) which have cited the Wakefield et al. retracted article, and a set of features characterizing each citing entity (columns in the CSV). The features included are: DOI ("doi"), year of publication ("year"), the title ("title"), the venue identifier ("source_id"), the title of the venue ("source_title"), yes/no value in case the entity is retracted as well ("retracted"), the subject area ("area"), the subject category ("category"), the sections of the in-text citations ("intext_citation.section"), the value of the reference pointer ("intext_citation.pointer"), the in-text citation function ("intext_citation.intent"), the in-text citation perceived sentiment ("intext_citation.sentiment"), and a yes/no value to denote whether the in-text citation context mentions the retraction of the cited entity ("intext_citation.section.ret_mention").<br> <strong>Note: </strong>this dataset is licensed under a <a href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons public domain dedication (CC0)</a>.</li> <li><em><strong>"cits_text.csv": </strong>this dataset stores the abstract ("abstract") and the in-text citations context ("intext_citation.context") </em>for each citing entity identified using the DOI value ("doi").<br> <strong>Note: </strong>the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work.</li> </ul> <p><strong>Topic modeling</strong></p> <p>We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the <em><strong>topic_modeling/</strong></em> directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools and creating a completely customizable visual workflow [1]. The topic modeling results for each textual feature are separated into two different folders, <em><strong>abstract/</strong></em> for the abstracts, and <em><strong>intext_cit/</strong></em> for the in-text citation contexts. Both the directories contain the datasets and visualizations generated using MITAO. </p> <p> </p> <p><strong>References</strong></p> <p>[1] Ferri, P., Heibi, I., Pareschi, L., & Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. <a href="https://doi.org/10.19245/25.05.pij.5.2.3">https://doi.org/10.19245/25.05.pij.5.2.3</a></p>
Phylogenetic analysis results
<p>Phylogenetic analysis results</p>
Datasets for Material Modal Composite Analysis results in Duanjiapo loess section
<p>The dataset is affilicated to the manuscript titled "Genesis of Loess Particles on the Chinese Loess Plateau" that is submitted for publication in the journal of Geochemistry, Geophysics, Geosystems. The original instrumental data packages were provided in the excel files (Data1, Data2, Data3, and Data4).</p>
Surface texture analysis in Toothfrax and MountainsMap® SSFA module: Different software packages, different results? [ConfoMap analysis]
<p>This record is a supplementary material to the pre-print with the DOI <a href="https://doi.org/10.5281/zenodo.7219877">10.5281/zenodo.7219877</a>.</p> <p>It contains the results of the 3D surface texture analysis on surfaces from three datasets: </p> <ul> <li>Sheep's teeth</li> <li>Guinea pig's teeth</li> <li>Lithic flakes</li> </ul> <p>Each surface has been processed in batch with a template. The result of the analysis on each surface is saved in MNT format (including all original and processed surfaces, as well as results) and exported to a PDF file.</p> <p>Ultimately, the results are collated into CSV files (see <a href="https://doi.org/10.5281/zenodo.7219855">10.5281/zenodo.7219855</a>).</p> <p>The analysis has been performed with ConfoMap (a derivative of MountainsMap) v. 8.2.9767.</p> <p> </p>
RNAseq data and analysis results from hippocampus of IVH+ICP, IVH, and sham control rats
<p>Supporting data from the RNAseq experiments appearing in the original manuscript "Sustained ICP Elevation Is a Driver of Spatial Memory Deficits After Intraventricular Hemorrhage and Leads to Activation of Distinct Microglial Signaling Pathways" accepted to Translational Stroke Research on June 24, 2022 (published July 12, 2022). Full experimental and technical details are available at <a href="https://doi.org/10.1007/s12975-022-01061-0">https://doi.org/10.1007/s12975-022-01061-0</a>. </p>
Inputs and results of "A quantitative and qualitative citation analysis to retracted articles in the humanities domain"
<p>This repository contains the datasets and visualizations generated in our work: <strong>"A quantitative and qualitative citation analysis to retracted articles in the humanities domain"</strong>.</p> <p><strong>Note:</strong> the data are all contained inside the <strong><em>data.zip</em> </strong>file. You need to unzip the container to get access to all the files and directories listed below.</p> <p>The data (citations) gathered accompanied by their annotated characteristics are stored in <strong><em>data/</em>:</strong></p> <ul> <li><em>cits.csv: </em>a dataset containing all the entities (rows in the CSV) which have cited a retracted article in the humanities domain. Each citing entity (row) is accompanied by a set of features (columns) that characterizes it.<br> <strong>Note: </strong>this dataset is licensed under a <a href="https://creativecommons.org/publicdomain/zero/1.0/legalcode">Creative Commons public domain dedication (CC0)</a>.</li> <li><em>content.csv: </em>a dataset containing the abstracts and the in-text citation contexts of all the citing entities gathered.<br> <strong>Note: </strong>the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work.</li> <li><em>excluded_hum_retractions.csv: </em>a list of the 12 humanities retracted articles with a humanities affinity score < 2, therefore excluded from the analysis. </li> </ul> <p> </p> <p><strong>Topic modeling</strong></p> <p>We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the <em><strong>topic_model/</strong></em> directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools and creating a completely customizable visual workflow [1]. The directory <em><strong>workflow/ </strong></em>contains the workflows used in MITAO. The topic modeling results for each textual feature are separated into two different folders, <em><strong>abstract/</strong></em> for the abstracts, and <em><strong>cits_context/</strong></em> for the in-text citation contexts. Both the directories contain the following directories/files: </p> <ul> <li> <p><em><strong>datasets_and_views/: </strong></em>the datasets and visualizations generated using MITAO. </p> </li> <li> <p><em><strong>ldamodel_corpus_dict/: </strong></em>it contains the dictionary, the LDA topic model, and the tokenized and vectorized corpus.</p> </li> <li><em><strong>rawdata/: </strong></em>the textual collection, metadata, and stopwords used as input in the workflow of MITAO</li> </ul> <p> </p> <p><strong>References</strong></p> <p>[1] Ferri, P., Heibi, I., Pareschi, L., & Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. <a href="https://doi.org/10.19245/25.05.pij.5.2.3">https://doi.org/10.19245/25.05.pij.5.2.3</a></p> <p> </p> <ol> </ol>
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.