Find research datasets worth reusing

Giant vortex clusters in a two-dimensional quantum fluid: Data sets

This data set collates the experimental and simulation data for the paper "Giant vortex clusters in a two-dimensional quantum fluid." Database S1: Data_Excel_Sheet.xlsx contains the data shown in Figs. 1, 3, and 4 of the paper. Database S2: Exp_Vortex_Location_Data.zip contains the experimental vortex positions. Database S3: 2DGPE.zip contains the outputs of the 2D GPE simulations, along with the generating scripts. Database S4: MonteCarlo_raw.zip contains the Monte Carlo outputs used to generate the shown in Fig. 1.  Additional scripts to reproduce the MC data, GPE data, and reproduce the figures may be found at <a href="https://github.com/UQBEC/GiantVortices">https://github.com/UQBEC/GiantVortices</a>.

Processed TCGA pan-cancer data set used in the I-Boost paper (Wong et al. 2019)

This data set contains the clinical and genomics data for 1,420 subjects analyzed in the paper: Wong KY, Fan C, Tanioka M, Parker JS, Nobel AB, Zeng D, Lin DY, Perou CM. I-Boost: an integrative boosting approach for predicting survival time with multiple genomics platforms. Genome Biology. 2019. It contains data on time to death, cancer type, 4 clinical variables, expression of 12,434 genes, somatic mutation of 130 genes, expression of 305 miRNA, expression of 136 proteins or phospho-proteins, copy number of 216 DNA segments, and 497 gene expression modules. Data on time to death, clinical variables, somatic mutation, copy number variation, mRNA expression, and miRNA expression were derived from the pan-cancer data set at Synapse (syn2468297 at <a href="https://www.synapse.org/#!Synapse:syn2468297">https://www.synapse.org/#!Synapse:syn2468297</a>). The protein expression data were obtained from Broad GDAC Firehose (<a href="https://gdac.broadinstitute.org/runs/stddata__2016_01_28/">https://gdac.broadinstitute.org/runs/stddata__2016_01_28/</a>).

opencc-by-4.0May 2018View details →

Data set for "Measuring synchronization and anticipation between individual investors from their daily performance"

The data stored here is used as a support of the paper "Measuring synchronization and anticipation between individual investors from their daily performance" where a measure based on Mutual Information and Transfer of Entropy is used in order to map investors' behaviour and which ones are following same behavioural patterns. The study linked to this data is published on pre-print Arxiv.org  with the following citation:     Mario Gutiérrez-Roig, Javier Borge-Holthoeffer, Alex Arenas and     Josep Perelló. Measuring synchronization and anticipation between     individual investors from their daily performance (2018)

opencc-by-4.0Mar 2019View details →

Large scale experiments for an alternative erosion control measure using sand-filled geosystems. Data set produced at the CIEM flume, Hydralab+

Sand-filled geosystems have the potential to mimic aspects of natural and nature-based features that can enhance the resilience of coastal areas challenged by climate, with additional (structural) reinforcement. Knowledge gaps can be identified. For instance, (i) the sediment transport mechanisms around the geosystem; (ii) the amount of erosion in the leeside when the system is overtopped; (iii) quantitative contribution the geosystem for the wave overtopping reduction; and (iv) failure mechanisms of the geosystem under extreme conditions. Specific tests are proposed in order to fill the defined knowledge gap and answer the following research questions: <ol> <li>How do nearshore coastal processes (wave transformation, sediment transport) and wave structure interactions during extreme events differ from those during more usual big storm conditions for situations with and without the geosystem?</li> <li>How do feedbacks between the hydrodynamics and morphology of natural and nature-based features affect flooding, erosion, and recovery of coastal areas when erosion is limited by the 'geosystem'?</li> <li>How to conceive a dynamic coastal protection that can easily adapt to climate change in areas experiencing coastal squeeze (i.e. dense urban environment and human infrastructure with sea encroaching land) and vulnerable to coastal erosion and flooding risks?</li> </ol> The set of experiments, done at the large wave Flume (CIEM) in Barcelona, are here described in order to answer the previous questions. These experiments started on October 2018 and ended at the end of November 2018. These tests include different configurations: an initial benchmark tests in order to test the wave conditions were no geosystem protection is used, a second layout with a geotube used as a geosystem protection and finally a third layout were geobags are used as a protection.

opencc-by-4.0Mar 2019View details →

Large scale experiments for an alternative erosion control measure using sand-filled geosystems. Data set produced at the CIEM flume, Hydralab+

Sand-filled geosystems have the potential to mimic aspects of natural and nature-based features that can enhance the resilience of coastal areas challenged by climate, with additional (structural) reinforcement. Knowledge gaps can be identified. For instance, (i) the sediment transport mechanisms around the geosystem; (ii) the amount of erosion in the leeside when the system is overtopped; (iii) quantitative contribution the geosystem for the wave overtopping reduction; and (iv) failure mechanisms of the geosystem under extreme conditions. Specific tests are proposed in order to fill the defined knowledge gap and answer the following research questions: <ol> <li>How do nearshore coastal processes (wave transformation, sediment transport) and wave structure interactions during extreme events differ from those during more usual big storm conditions for situations with and without the geosystem?</li> <li>How do feedbacks between the hydrodynamics and morphology of natural and nature-based features affect flooding, erosion, and recovery of coastal areas when erosion is limited by the 'geosystem'?</li> <li>How to conceive a dynamic coastal protection that can easily adapt to climate change in areas experiencing coastal squeeze (i.e. dense urban environment and human infrastructure with sea encroaching land) and vulnerable to coastal erosion and flooding risks?</li> </ol> The set of experiments, done at the large wave Flume (CIEM) in Barcelona, are here described in order to answer the previous questions. These experiments started on October 2018 and ended at the end of November 2018. These tests include different configurations: an initial benchmark tests in order to test the wave conditions were no geosystem protection is used, a second layout with a geotube used as a geosystem protection and finally a third layout were geobags are used as a protection.

opencc-by-4.0Apr 2019View details →

Data set for Sicoli et al. - Conformational tuning of a DNA-bound transcription factor

The data set contains NMR, EPR and MD data. The NMR folder contains 1H-15N correlation NMR data of DNA-bound MAX with a paramagnetic MTSL spin label at position 5, with a chemically reduced, diamagnetic spin label, respectively. The EPR folder contains DEER data of MAX for three difference labeling positions R5C, G35C and R55C, with and without bound DNA. The MD folder contains MD trajecrories at three different temperatures, 310 K, 320 K and 330 K. Further details can be found in the readme.txt files in the respective folders.

opencc-by-4.0Apr 2019View details →

Data set on linguistic similarity of German dialects

- The data provide information on pairwise dialect similarities for 439 NUTS 3 regions in Germany - Data come from the maps and questionnaires of the Sprachatlas des Deutschen Reichs, digitized using ArcGIS software - The data source is a questionnaire with translations of standardized German sentences into local dialects between 1879 and 1888 - The measure is defined as the number of co-occurrences for all pairs of sites (z-scaled)

Serial Rotation Electron Diffraction (automated continuous RED) raw data sets

Serial Rotation Electron Diffraction (automated continuous RED) raw data sets Containing: TIFF images for particle recognition SMV files for XDS processing XDS input files (automatically generated)

opencc-by-4.0Apr 2013View details →

Synthetic Data for Neutrophil Analysis: Sets with irregular shapes and Poisson noise

Synthetic Datasets with irregular shapes and Poisson noise. Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):   https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636 http://www.phagosight.org https://github.com/phagosight/phagosight   A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames. Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation.  Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by irregular shapes (sum of Gaussians) and Poisson Noise (check the corresponding sets with regular shapes, i.e. Gaussians with Gaussian noise plus another set with a single large neutrophil and Poisson noise) distributions of higher intensities than the background. The orientation of the Poisson varied according to the displacement of the artificial neutrophils, i.e.they were round when the cells were static, or elongated when in movement. The tracks with the Shapes were saved as the gold standard and five different data sets were generated by adding varying levels of white Poisson noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.   Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 5): <ul> <li>    x,y,t trajectories    ThreeDTracks</li> <li>    Ground Truth       syntheticData_P_mat_La </li> <li>    First data set         syntheticData_P1_mat_Re</li> <li>    Second data set     syntheticData_P2_mat_Re</li> <li>    Third data set       syntheticData_P3_mat_Re</li> <li>    Fourth data set     syntheticData_P4_mat_Re</li> <li>    Fifth data set        syntheticData_P5_mat_Re</li> </ul> Corresponding GIF files are also included as illustrations of the cells in motion.   Main Reference: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636">PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model </a> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a>

opencc-by-4.0Apr 2013View details →

Synthetic Data for Neutrophil Analysis: Sets with regular shapes and Gaussian noise

Synthetic Datasets with regular shapes and Gaussian noise. Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):   https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636 http://www.phagosight.org https://github.com/phagosight/phagosight   A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames. Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation.  Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by Gaussian distributions of higher intensities than the background and Gaussian noise (check the corresponding irregular shapes with Poisson noise plus another set with a single large neutrophil and Poisson noise). The orientation of the Gaussians varied according to the displacement of the artificial neutrophils, i.e.they were round when the cells were static, or elongated when in movement. The tracks with the Gaussians were saved as the gold standard and five different data sets were generated by adding varying levels of white Gaussian noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.   Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 6): <ul> <li>    x,y,t trajectories    ThreeDTracks</li> <li>    Ground Truth       syntheticData0_mat_Re </li> <li>    First data set         syntheticData1_mat_Re</li> <li>    Second data set     syntheticData2_mat_Re</li> <li>    Third data set       syntheticData3_mat_Re</li> <li>    Fourth data set     syntheticData4_mat_Re</li> <li>    Fifth data set         syntheticData5_mat_Re</li> <li>    Sixth data set         syntheticData6_mat_Re</li> </ul>   Corresponding GIF files are also included as illustrations of the cells in motion.   Main Reference: <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636">PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model </a> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a>

Application Cases of Inverse Modelling with the PROPTI Framework - Data Set

Contents Set of simulation data, supplementary for a paper submitted to (published: 15 June 2019) the Fire Safety Journal, with the title <a href="https://www.sciencedirect.com/science/article/pii/S0379711219300438">"Application Cases of Inverse Modelling with the PROPTI Framework"</a>. See also our project at <a href="https://www.researchgate.net/project/PROPTI-An-Generalised-Inverse-Modelling-Framework">ResearchGate</a>. This repository contains the complete input data for each IMP run of the mass loss calorimeter, shown in this paper. This comprises of the experimental data files, the templates for the simulation models and the input file for PROPTI. The data base files are provided. This includes the original ones created by PROPTI during the run, as well as the cleaned data base files, used to create the plots, and the extracted best parameter sets per generation. Plots, created during the IMP runs as means of monitoring the progress are also included. Furthermore, the repository contains a small collection of Jupyter notebooks which have been used to process the data base files and create the plots presented in this paper. The full factorial simulations were set up from within a Jupyter notebook. This notebook and the conducted simulations are also part of this repository. Data of the various TGA simulations are provided within a very <a href="https://zenodo.org/record/2538851#.XSXfAXtCSUk">similar repository</a>, linked to a <a href="https://www.researchgate.net/publication/328933654_PROPTI_-_A_Generalised_Inverse_Modelling_Framework">conference paper</a> (ESFSS 2018, Nancy, France). Finally, the simulation input files, PROPTI input, as well as the custom script for file handling in concert with OpenFOAM, are provided.   Technical Information Each ZIP archive represents a sub-directory of the original directory. For the analysis scripts, the Jupyter notebooks, to work properly out of the box it is necessary to keep this structure. Thus, simply extract all archives into the same directory. Note: Size on disc, after extraction, is about 4.1 GB. Version 2 adds about 5.1 GB.   Version 2: Version 2 contains new IMP runs that address an error in determining the normalised residual mass, see Jupyter Notebook "RevisedTargetAssessment.ipynb", as well as input from the reviewers. The IMP runs are denoted by "08" after the optimisation algorithm label, e.g. "MLC_FSCABC_08_new_75kw_Ins".

opencc-by-nc-sa-4.0May 2019View details →

Prince Edward Island (Canada) Predictive Soil Mapping data set (30 m)

Prince Edward Island (Canada) Predictive Soil Mapping data set. Training points include: <ul> <li>soil organic matter (624 points): unit: percent, g/100g ) samples from the topsoil (0-23 cm depth),</li> <li>soil types (672 points),</li> </ul> Covariate layers include: <ul> <li>DEM derivatives (Channel_Network_Base_Level.tif, MRRTF.tif, Relative_Slope_Position.tif, Slope.tif, TWI.tif, Valley_Depth.tif, Vertical_Distance_To_Channel_Network.tif),</li> <li>landcover_2016_reclassify.tif (categorical values),</li> <li>DSS_soil_polygons.tif (soil polygons),</li> </ul> Some covariates are type numeric, some type factor. To use the pre-processed data download only the RDS file. E.g. "PEI100m.soil.rds" contains all covariates layers resampled to 100 m resolution and all training points.

opencc-by-4.0Jun 2019View details →

Gone with the wind data sets

The data used for the research article Gone with the wind: Effects of wind on honey bee visitation rate and foraging behaviour. These include data for the direct effect of wind on all flower spacings and behaviour as well as the data sheets used for analysing data on only one or two spacings. A separate spreadsheet for the data on the indirect effects is also attached.

opencc-by-4.0Aug 2018View details →

Survey Data Set Part 1 - Attitudes Towards Videos as a Documentation Option for Communication in Requirements Engineering

In 2017, we conducted an online survey to explore software professionals' attitudes towards videos as a documentation option for communication in requirements engineering. The survey covered the following topics: <ul> <li>Demographics</li> <li>Attitude towards videos as a medium in RE including its strengths, weaknesses, opportunities, and threats</li> <li>Current production and use of videos in RE, respectively the obstacles that prevent the production and use of videos</li> </ul> 64 out of 106 software professionals from industry and academia completed the survey. The survey was implemented in LimeSurvey and distributed across several communication channels such as LinkedIn, ResearchGate, and a mailing list of a German RE professionals group. This dataset includes the following files: <ul> <li>"Raw and analyzed data.xlsx" contains the raw and analyzed survey responses which are anonymized <ul> <li>This data includes demographics and attitude.</li> <li>The data on video production and use are included in: <a href="https://zenodo.org/record/4064741">Survey Data Set Part 2 - Attitudes Towards Videos as a Documentation Option for Communication in Requirements Engineering</a>.</li> </ul> </li> <li>"Survey - Offline version.docx" contains the questions and possible answers of the survey</li> <li>"Survey - Offline version.pdf" contains the questions and possible answers of the survey</li> </ul> This survey was designed, conducted, and analyzed by Oliver Karras (<a href="https://twitter.com/KarrasOliver">@KarrasOliver</a>).

opencc-by-4.0May 2019View details →

Raw data set: One-Step Fabrication of GeSn Branched Nanowires

This is the raw data set for the publication titled " One-Step Fabrication of GeSn Branched Nanowires" in the journal Chemistry of Materials (Chem. Mater.201931114016-4024). Below is the abstract of the publicaiton. Abstract: We report for the first time the self-catalysed, single step growth of branched GeSn nanostructures by a catalytic vapour-liquid-solid (VLS) mechanism.  These typical GeSn nanostructures consist of <111> oriented Sn rich (~8 at. %) GeSn “branches” grown epitaxially on GeSn “trunks”, with a Sn content of ~ 4 at. %.  The trunks are seeded from Au0.80Ag0.20 nanoparticles followed by the catalytic growth of secondary branches (diameter ~ 50 nm) from the excess of Sn on the sidewalls of the trunks, as determined by high resolution electron microscopy and energy dispersive X-ray (EDX) analysis.  The nanowires, with <111> directed GeSn branches oriented at ~ 70 ° to the trunks, have no apparent defects or change in crystal structure at the trunk-branch interface; structural quality is retained at the interface with epitaxial crystallographic relation.  Electrochemical performance of these highly ordered GeSn nanostructures were explored as a potential anode material for Li-ion batteries, due to their high surface to volume ratio and increased charge carrier pathways.  The unique structure of branched nanowires led to high specific capacities comparable to, or greater than, conventional Ge nanowire anode materials and Ge1-xSnx nanocrystals.We report for the first time the self-catalysed, single step growth of branched GeSn nanostructures by a catalytic vapour-liquid-solid (VLS) mechanism.  These typical GeSn nanostructures consist of <111> oriented Sn rich (~8 at. %) GeSn “branches” grown epitaxially on GeSn “trunks”, with a Sn content of ~ 4 at. %.  The trunks are seeded from Au0.80Ag0.20 nanoparticles followed by the catalytic growth of secondary branches (diameter ~ 50 nm) from the excess of Sn on the sidewalls of the trunks, as determined by high resolution electron microscopy and energy dispersive X-ray (EDX) analysis.  The nanowires, with <111> directed GeSn branches oriented at ~ 70 ° to the trunks, have no apparent defects or change in crystal structure at the trunk-branch interface; structural quality is retained at the interface with epitaxial crystallographic relation.  Electrochemical performance of these highly ordered GeSn nanostructures were explored as a potential anode material for Li-ion batteries, due to their high surface to volume ratio and increased charge carrier pathways.  The unique structure of branched nanowires led to high specific capacities comparable to, or greater than, conventional Ge nanowire anode materials and Ge1-xSnx nanocrystals.

opencc-by-4.0Dec 2018View details →

Data set of Ultrathin Eu- and Er-Doped Y2O3 Films with Optimized Optical Properties for Quantum Technologies

Data corresponding to the figures of the publication " Ultrathin Eu- and Er-Doped Y2O3 Films with Optimized Optical Properties for Quantum Technologies " by M. Scarafagio et al. J. Phys. Chem. C 2019, 123, 13354-13364 (<a href="https://doi.org/10.1021/acs.jpcc.9b02597">https://doi.org/10.1021/acs.jpcc.9b02597</a>). A text file describes data in each compressed folder, please refer to the caption in the publication for more details.

Eye on Core Trust Seal - Data Set

This data set includes extracted information from 40 CoreTrustSeal (CTS) self-assessment reports, which were publicly available by January 15th 2019 at https://www.coretrustseal.org/why-certification/certified-repositories/. The authors extracted general information from the title pages of the self-assessment reports, as well as responses to criterion "R0 - Background Information / Context". Sheet "Extracted_Information" includes all extracted info, whereas "Level_of_Curation", "Designated_Community" and "Repository_Type" include normalized and categorized data. The data cleansing / normalization and analysis processes are described in the paper "Eye on Core Trust Seal - Recommendations for Criterion R0 from Digital Preservation and Research Data Management Perspectives" to be released as part of the Proceedings of iPRES2019, the 16th International Conference on Digital Preservation. The data set forms the basis for an extended analysis of Core Trust Seal criterion R0 from the perspectives of the digital preservation and research data management domain. Abstract of the accompanying paper: The CoreTrustSeal (CTS) is an accepted trustworthy digital repository certification process for both, research data management and digital preservation communities alike. But does it build on concepts known and understood by both of these communities? We take an in-depth look at the CTS requirement R0 - Background Information / Context, in which the applicants are asked to define their repository  type, designated community and level of curation performed. By extracting information from the publicly available assessment reports and cross-checking these against available supporting information, we reflect on CTS from three viewpoints: the process, the institutional, and the community view. We distill concrete recommendations, which will be fed back to the CTS Board as part of the 2019 public call for review.

Test data set for macros accompanying the publication Multi-parameter screening method for developing optimized red fluorescent proteins

This a bundle of test data can be used to run the macros accompanying the publication Multi-parameter screening method for developing optimized red fluorescent proteins. These data sets can be used to run the following macros that can be found on GitHub: <ol> <li><a href="https://github.com/molcyto/MC-Ratio-96-wells">https://github.com/molcyto/MC-Ratio-96-wells</a></li> <li><a href="https://github.com/molcyto/MC-Ratio-Petri-dish">https://github.com/molcyto/MC-Ratio-Petri-dish</a></li> <li><a href="https://github.com/molcyto/MC-FLIM-Petri-dish">https://github.com/molcyto/MC-FLIM-Petri-dish</a></li> <li><a href="https://github.com/molcyto/MC-Bleach-96-wells">https://github.com/molcyto/MC-Bleach-96-wells</a></li> <li><a href="https://github.com/molcyto/MC-Scatter5D">https://github.com/molcyto/MC-Scatter5D</a></li> <li><a href="https://github.com/molcyto/MC-FLIM-96-wells">https://github.com/molcyto/MC-FLIM-96-wells</a></li> </ol> Funding: This work was supported by the NWO CW-Echo grant 711.011.018 (M.A.H. and T.W.J.G.), grant 12149 (T.W.J.G.) from the Foundation for Technological Sciences (STW) from the Netherlands

3D-structured Supports create complete Data Sets for Electron Crystallography

Each tar file contains the raw files in HDF5 format, together with the XDS.INP file used for data integration. NB: The meta-data in the HDF5 files have no meaning, please refer to the respective XDS.INP file for respective information.

PCA SUB ELITE YOUTH Handball DATA_SET

The presented data base refers to results of study about PCA in Handball locomotion analysis of youth sub-elite handball players.