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.
8,038
datasets available to search
ShareScore release 0.7.1
Dataset results
8,038 results for “validation”
Data for figures and tables in: "Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument"
<p>Supplementary material to DESI's publication 'Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument' to comply with the data management plan.</p>
Experimental Validation video for paper "The Critical Role of Effective Communication in Human-Robot Collaborative Assembly"
<p>Experimental Validation video for paper "The Critical Role of Effective Communication in Human-Robot Collaborative Assembly".</p><p>The video shows a collaborative manipulator executing a collaborative assembly job with the user using a natural vocal communication architecture. The experiment compares the proposed framework with the state-of-art interaction and highlight the differences.</p>
Replication Package for "VALIDATE: A Deep Dive into Vulnerability Prediction Datasets"
<p>Replication Package for "VALIDATE: A Deep Dive into Vulnerability Prediction Datasets"</p><ul><li>SDR Results</li><li>SDR Queries</li><li>VALIDATE User Guide</li><li>Original Studies References in BibTeX</li></ul>
Establishing Fully-Automated Fundus-Controlled Dark Adaptometry: A Validation and Retest-Reliability Study
<p>This is the data presented in our manuscript <i>'Establishing Fully-Automated Fundus-Controlled Dark Adaptometry: A Validation and Retest-Reliability Study'</i> published in Translational Vision Science & Technology.</p>
Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers - Part II
<p>Dataset Part II for publication "Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers", in Nature Communications.</p>
Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers - Part I
<p>Dataset Part I for publication "Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers", in Nature Communications.</p>
Experimental data from the initial validation of spark-eclib, a new framework for distributed metaheuristics in Spark
<p>This repository contains the experimental data obtained from two series of experiments to validate and profile <a href="https://doi.org/10.5281/zenodo.8431048"><strong>spark-eclib</strong></a>, a framework written in Scala to support the development of distributed population-based metaheuristics and their application to the global optimization of large-scale problems in Spark clusters:</p> <ul> <li>Experiments to validate the proposal of a generic topology for distributed PSO algorithms.</li> <li>Experiments to profile the parallel implementations of a PSO template.</li> </ul>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class III) vs NoLineal (Class III)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions (linear interactions)</strong> and <strong>high-order interactions (non-linear interactions)</strong>.</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset, whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlinearx means that the linear coupling occurs in variable <em><strong>x</strong></em> (class III) whereas the non-linear coupling occurs in variable<em><strong> x</strong></em> (class III).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the<strong><em> x</em></strong> and <strong><em>y</em></strong> variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class III) vs NoLineal (Class II)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in<strong> simplicial complexe</strong>s. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and <strong>high-order interactions</strong> (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (second), whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlineary means that the linear coupling occurs in variable <em><strong>x</strong></em> (class III) whereas the non-linear coupling occurs in variable <em><strong>y</strong></em> (class II).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the <em><strong>x</strong></em> and <em><strong>y</strong></em> variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class II) vs NoLineal (Class III)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and <strong>high-order interactions</strong> (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (third), whose name explicitly indicates in which state variable occurs each coupling. In these case, Lineary-nonlinearx means that the linear coupling occurs in <strong>variable y</strong> (class II) whereas the non-linear coupling occurs in <strong>variable x</strong> (class III).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the x and y variables of each oscillator and the rows correspond to time-varying samples.</p>
Experimental validation of simplicial complexes in multivariable coupled oscillators. Coupling: Lineal (Class II) vs NoLineal (Class II)
<p>The data sets correspond to the experimental implementation of synchronization phenomenon in <strong>simplicial complexes</strong>. In this particular case, the simplicial complex consists of 3-node network, where each node is an electronic Rössler-like oscillator whose parameters were fixed to operate in <strong>chaotic regime</strong>. In simplicial complexes, it is possible to model two types of interactions among nodes: <strong>pair-wise interactions</strong> (linear interactions) and<strong> high-order interaction</strong>s (non-linear interactions).</p> <p>The complete experiment consists of coupling simultaneously by means of linear and non-linear interactions the simplicial complex, the coupling occurs in state variables x (class III) and y (class II). The full data sets are organized in four Dataset (fourth), whose name explicitly indicates in which state variable occurs each coupling. In these case, Linearx-nonlinearx means that the linear coupling occurs in variable <strong>y</strong> (class II) whereas the non-linear coupling occurs in variable <strong>y</strong> (class II).</p> <p>Now, each folder contains 10000 files which come from varying the linear coupling and the nonlinear coupling 100 times each one. The file name is composed as follows: rootname XX YY, where XX corresponds to the variation number in linear coupling, whereas YY corresponds to the variation number in non-linear coupling.</p> <p>Internally in each file we can find 6 columns and 30,000 rows. Each pair of columns corresponds to the x and y variables of each oscillator and the rows correspond to time-varying samples.</p>
Profiling of pancreatic adenocarcinoma using artificial intelligence-based integration of multi-omic and computational pathology features - Validation Data Sets
<p>Two public validation cohorts were utilized in the MT-Pilot study, the Cancer Genome Atlas (TCGA) and cohort-1 Johns Hopkins University (JHU). These datasets included DNA, RNA, clinical data, and tissue protein analytes analyzed for survival outcome prediction using AI/Machine Learning modeling. </p>
Antibody Validation for Cyclical Immunofluorescence Microscopy of Human Kidneys (Part 1, Figures 31 and 33)
<p>This dataset includes Cyclical Immunofluorescnce (CyCIF) images (15-20 channels) of frozen human kidney sections interogated with a panel of 12 validated antibodies designed to evaluate renal tubular cell segmentation (Figures 31 and 32), an a panel of 12 validated antibodies and a lectin designed to evaluate glomerular and glomerulus-associated structures in the normal human kidney (Figure 33). We have attached an excel file (Supplemental Table 2) that includes all of the experimental and (de-identified) patient metadata associated with these images, with information and comments about each of the channel images, the antibodies used, CyCIF cycles, and the cell types and extracellular matrix compartments identified with these combinations of antibodies. Because of the sixze of the images, we have divided this into two separate datasets (Antibody Validation for Cyclical Immunofluorescence Parts 1 and 2). </p>
Antibody Validation for Immunofluorescence Microscopy of Human Kidneys (Part 2, Figures 16-30)
<p>This dataset includes multiplex immunofluorescence images (mostly 3+1 channels) of frozen human kidney sections that have been used to validate a panel of 27 antibodies and 1 lectin designed to define the main cellular and extracellular matrix (ECM) comparments in the normal human kidney. We have attached an excel file (Supplemental Table 1) that includes all of the experimental and (de-identified) patient metadata associated with these images with information, and comments about each of the images, the antibodies used, and the cell types and ECM compoartments identified using these antibodies. Because of the size and number of images used for these studies, we have divided this into two separate datasets (Antibody validation studies Parts 1 and 2). </p> <p>A subset of these antibodies have also been evaluated for both 2D and 3D cyclical immunofluorescence studies that have been included in separate datasets under this umbrella "community". These are identified in the "Antibodies used" tab in Supplemental Table 1 (CyCIF Cycles). </p>
Antibody Validation for Immunofluorescence Microscopy of Human Kidneys (Part 1, Figures 1-15)
<p>This dataset includes multiplex immunofloresence images (mostly 3+1 channels) of frozen human kidney sections that have been used to validate a panel of 27 antibodies and 1 lectin designed to define the main cellular and extracellular matrix compartments in the normal human kidney. We have attached an excel file (Supplemental Table 1) that includes all of the experimental and (deidentified) patient metadata associated with these images with information and comments about each of the images, the antibodies used, and the cell types and ECM compartments identified using these antibodies. Because of the size and number of images used for these validation studies, we have divided this into two separate datasets (Antibody validation studies Parts 1 and 2). </p> <p>A subset of these antibodies have also been evaluated for both 2D and 3D cyclical immunofluoresecnce studies that have been included in separate datasets under this umbrella "community". These are identfied in the "Antibodies used" tab in Supplemental Table 1 (CyCIF Cycles). </p> <p> </p> <p> </p> <p> </p>
qPCR results from design and partial validation of three novel eDNA qPCR assays for several common North American tick (Arachnida: Ixodida) species
<p>The range expansion of ticks to higher latitudes poses a severe threat to human health exposing human populations who had no prior contact with ticks to several harmful tick-borne diseases. Early detection of ticks in new areas is critical to help inform the public and medical professionals of the dangers associated with tick encounters. Environmental DNA represents a novel survey method that could provide reliable records of tick occurrences and timely warnings of their range expansions. In this study, we designed three novel eDNA qPCR assays for three common North American tick species (<em>Dermacentor variabilis</em>, <em>Amblyomma americanum</em>, and <em>Ixodes scapularis</em>) and tested them on samples of grasses collected from grasslands and forests in Illinois. We provide <em>in silico</em> and <em>in vitro </em>validation of all three assays, however we were unable to generate any positive detections from field samples. Our lack of eDNA detections likely stems from low eDNA deposition rates coupled with rapid degradation in grasslands and forests, a problem exacerbated by terrestrial eDNA sampling methods that are limited by volume of substrate. We provide recommendations for improving sample collection methods to increase detection probability in future efforts. Continued research should focus on the viability of eDNA to detect small terrestrial invertebrates, like ticks, and it potential as early warning indicator of the spread of vector-borne diseases.</p>
Monitoring mobility in older adults using a global positioning system (GPS) smartwatch and accelerometer: A validation study
<p><strong>Background</strong></p> <p>There is interest in identifying the most reliable method for detecting early mobility limitations. Accelerometry and Global Positioning System (GPS) could provide insight into declines in mobility, but few studies have used this multi-sensor approach to monitor mobility in older adults. </p> <p><strong>Methods</strong></p> <p>Thirty-two volunteers (66.2±6.3 years) agreed to participate in our validation study. We conducted two experiments to determine the validity of the TicWatch S2 and Pro 3 Ultra GPS models against the Qstarz receiver in measuring life-space mobility, trip frequency, duration, and mode. We also assessed the accuracy of the TicWatch in measuring step count and agreement with the ActiGraph wGT3X-BT for activity counts and sedentary behavior. Participants wore devices simultaneously for three consecutive days and recorded activity and trip information.</p> <p><strong><span>Results</span></strong></p> <p>The TicWatch Pro 3 Ultra GPS performed better than the S2 model and was similar to the Qstarz in all tested trip-related measures, and it was able to estimate both passive and active trip modes. Both models showed similar results to the Qstarz in life-space-related measures. The TicWatch S2 demonstrated good to excellent overall agreement with the ActiGraph algorithms for the time spent in sedentary and non-sedentary activities, with 84% and 87% agreement rates, respectively. Under supervised conditions, the TicWatch Pro 3 Ultra GPS measured step count consistently with the gold standard observer, with a bias of 0.4 steps. The thigh-worn ActiGraph algorithm accurately classified sitting and lying postures (97%) and standing postures (90%).</p> <p><strong>Conclusion</strong></p> <p>Our multi-sensor approach to monitoring mobility has the potential to capture both accelerometer-derived movement data and trip/life-space data only available through GPS. In this study, we found that the TicWatch models are valid devices for capturing GPS and raw accelerometer data, making them useful tools for assessing real-world mobility in older adults and advancing our knowledge of early mobility decline.</p>
Research data supporting article on implementation and validation of OpenMC cell-based R2S shutdown dose rate capabilities
<p>This file contains an archive of all research data that supports the article on implementation and validation of a cell-based R2S shutdown dose rate workflow in OpenMC.</p>
Data and Codes for Experimentally Validated Inverse design of Multi Property Fe-Co-Ni alloys: Data and codes release v1.0.1
<p>Data and Codes for Experimentally Validated Inverse design of Multi-Property Fe-Co-Ni alloys</p>
The many faces of early life adversity - Content overlap in validated assessment instruments as well as in fear and reward learning research
<p>The precise assessment of childhood adversity is crucial for understanding the impact of aversive events on mental and physical development. However, the plethora of assessment tools currently used in the literature with unknown overlap in childhood adversity types covered hamper comparability and cumulative knowledge generation. In this study, we conducted two separate item-level content analyses of in total 35 questionnaires aiming to assess childhood adversity. These include 13 questionnaires that were recently recommended based on strong psychometric properties as well as additional 25 questionnaires that were identified through a systematic literature search. The latter provides important insights into the actual use of childhood adversity questionnaires in a specific, exemplary research field (i.e., the association between childhood adversity and threat and reward learning). Of note, only 3 of the recommended questionnaires were employed in this research field. Both item-wise content analysis illustrate substantial heterogeneity in the adversity types assessed across these questionnaires and hence highlight limited overlap in content (i.e., adversity types) covered by different questionnaires. Furthermore, we observed considerable differences in structural properties across all included questionnaires such as the number of items, age ranges assessed as well as the specific response formats (e.g., binary vs. continuous assessments, self vs. caregiver). We discuss implications for the interpretation, comparability and integration of the results from the existing literature and derive specific recommendations for future research. In sum, the substantial heterogeneity in the assessment and operationalization of childhood adversity emphasizes the urgent need for theoretical and methodological solutions to promote comparability, replicability of childhood adversity assessment and foster cumulative knowledge generation in research on the association of childhood adversity and physical as well as psychological health.</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.