Research Dataset Catalog and ShareScore Ratings | ScienceDex

zenodo40/100

Fig. 3 in Tools and Methods to Assess Field Performance Locomotion activity meter for quality assessment of mass-reared sterile male moths (Lepidoptera)

Fig. 3. Mean activity counts for before and afer pheromone exposure (lef), and the mean afer/before activity ratio (right), for un-irradiated (0 Gy = −) and irradiated (300 Gy = +) Epiphyas postvittana males. Error bars are 95% confidence limits for each mean. An afer/before ratio of 1 (marked) indicates an equal level of activity before and afer pheromone exposure.

opencc-by-4.0Jun 2016View details →

zenodo40/100

Fig. 2 in Tools and Methods to Assess Field Performance Locomotion activity meter for quality assessment of mass-reared sterile male moths (Lepidoptera)

Fig. 2. Measured activity of male Epiphyas postvittana as summed counts at 30 s intervals in a locomotor activity monitor, before and afer pheromone stimulus of irradiated and non-irradiated moths.

opencc-by-4.0Jun 2016View details →

zenodo40/100

Fig. 1 in Tools and Methods to Assess Field Performance Locomotion activity meter for quality assessment of mass-reared sterile male moths (Lepidoptera)

Fig. 1. An illustration of the modified Locomotion Activity Monitor set-up used for the bioassays in this study. Synthetic pheromone was puffed (2 s) from upwind to stimulate LBAM males into wing fanning. Each time a male moved through the beam array it was counted as 1 observation. Comparisons were made between pre-pheromone exposure activity and post-pheromone exposure activity for each treatment.

opencc-by-4.0Jun 2016View details →

zenodo40/100

Fig. 4 in Tools and Methods to Assess Field Performance Locomotion activity meter for quality assessment of mass-reared sterile male moths (Lepidoptera)

Fig. 4. Mean activity counts for before and afer pheromone exposure (lef), and the mean afer/before activity ratio (right), un-irradiated (0 Gy) and irradiated (300 Gy) Epiphyas postvittana males exposed to 1 of 4 levels of temperature shock (0, 1, 2, 4 h at 30 °C). Error bars are 95% confidence limits for each mean. An afer/before ratio of 1 (marked) indicates an equal level of activity before and afer pheromone exposure.

opencc-by-4.0Jun 2016View details →

zenodo40/100

Expert-based literature review on RRI indicators for science education assessment: PERFORM analysis matrix

The document contains the main variables and categories of analysis of the expert-based literature review conducted as part of the assessment impact developed in the PERFORM project. This literature review globally aimed to identify and characterize assessment frameworks used in the context of science learning and engagement with young people. Specifically, it examined the operationalization of: i) RRI values and process requirements, ii) transversal competences, iii) experiential aspects, and iv) cognitive aspects. In doing that assessment gaps and challenges where identified relevant to the context of PERFORM and, more broadly, to the development of science education assessments incorporating the RRI dimension. By assessment framework we refer to a set of interlinked criteria, practices and concepts providing a systematic way of data collection, analysis and interpretation to the study of science learning and engagement. The template for data collection was organised in different sections approaching the following specific review questions and sub-questions: <ol> <li>What assessment frameworks can be identified in the selected sample? <ol> <li>On which disciplines are they based?</li> <li>What is being assessed in these frameworks?</li> <li>How it is the evaluation conducted?</li> <li>What are the challenges of each approach for assessing science learning and engagement?</li> </ol> </li> <li>How are transversal competences, RRI and emotional factors included in these frameworks? <ol> <li>How are these notions operationalised?</li> <li>What kinds of evaluation indicators are applied for data collection, if any?</li> </ol> </li> </ol>

opencc-by-4.0Jan 2018View details →

zenodo40/100

Assessing the sustainability performance of sustainability management software - replication package

This is the replication package for the article "Assessing the sustainability performance of sustainability management software", published in Technologies – SI &bdquo;Advanced Green Information and Communication Technology“ Contents The repository contains the following files: <ul> <li>Data_-_Scenario_Hardware_Measurement.csv: measurement data acquired during the measurement of the standard usage scenario</li> <li>Data_-_Scenario_Log.txt: timestamp log file for the measurements of the standard usage scenario</li> <li>Data_-_Baseline_Hardware_Measurement.csv: baseline meaurements</li> <li>Data_-_Baseline_Log.txt: baseline timestamp log file</li> <li>R_image.Rdata: data is also available in an R image dump</li> <li>R_Analysis_Script.R: analysis script, written in R</li> <li>Results_SCSS_WeSustain_ESM.pdf: results of the analysis</li> <li>Results_and_calculation_for_Indicators_1.2.b_and_1.2.c.ods: calculation for indicators 1.1.4.d) 1.2.b) and 1.2.c)</li> <li>Usage-scenario_WeSustain_ESM.pdf: description of the standard usage scenario</li> </ul> Usage To recreate the analysis, run the R script and, if necessary, modify lines 103 to 115 to fit the filenames where to find the data. Lines 193 to 217 need to be executed manually, to generate the desired plots and calculations. It is also possible to load the R_image.RData data dump into an R session, import the library `psych` (line 2 in the script) and manually execute lines 193 to 217 to generate the desired plots and calculations.

opencc-by-nc-4.0Sep 2018View details →

zenodo40/100

Hyperparameter tuning and performance assessment of statistical and machine-learning models using spatial data.

This is a research compendium (RC) for the publication "Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data". The code (including figures, appendices and the manuscript) is packed in pathogen-modeling-3.zip or can be found directly in the <a href="https://github.com/pat-s/pathogen-modeling">Github repository</a>. <ul> <li>Publication figures: analysis/paper/submission/3/latex-source-files/</li> <li>Appendices: analysis/paper/submission/3/</li> </ul> This RC represents a static snapshot at the time of submission. The Github repository will receive changes after the publication was published. Data sources <ul> <li>Atlas Climatico: <a href="http://opengis.uab.es/wms/iberia/index.htm">http://opengis.uab.es/wms/iberia/index.htm</a></li> <li>DEM: ftp://ftp.geo.euskadi.eus/lidar/MDE_LIDAR_2016_ETRS89/</li> <li>Lithology: <a href="http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home">http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home</a></li> <li>pH: <a href="https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0">https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0</a></li> <li>soil: <a href="https://www.isric.org/explore/soilgrids">https://www.isric.org/explore/soilgrids</a></li> </ul> Licenses All files are shared via the given license with the exception of "soil.tif" which is shared via the ODbL license.

opencc-by-4.0Apr 2019View details →

zenodo40/100

Long-term Performance and Life Cycle Assessment of Energy Piles in three Different Climatic Conditions_Dataset

In this file it is possible to find the dataset linked to the related pubblication. In the file each spreadsheet corresponf to a picture of the paper.

opencc-by-4.0Jul 2019View details →

zenodo40/100

Deliverable D6.2 "TOOL FOR PERFORMANCE ASSESSMENT"- BN network and Bellman shortest path analysis_Module 3_Annex 6

This file will introduce the BN network and Bellman shortest path analysis Module 3 Annex 6 in deliverable D6.2 "TOOL FOR PERFORMANCE ASSESSMENT".

opencc-by-4.0May 2023View details →

zenodo40/100

Evaporative cooling driven by a Venturi tube revisited; Assessing the performance of different refrigerant-circulating pairs Data Sheet

File data collected for article "Evaporative cooling driven by a Venturi tube revisited; Assessing the performance of different refrigerant-circulating pairs " in Origin format. Includes temperature measurements and graphs exposed in the article.

opencc-by-4.0Jun 2023View details →

zenodo40/100

Dataset for the article: Evaluating the Predictive Performance of Quick Methods for Estimating Task Difficulty and Student Ability in Automated Computer Programming Assessment

This open access repository houses the dataset utilized in the research article:Pankiewicz, M. (2023). Evaluating the Predictive Performance of Quick Methods for Estimating Task Difficulty and Student Ability in Automated Computer Programming Assessment. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 1413-1418). Vienna, Austria: Association for the Advancement of Computing in Education (AACE). Retrieved from https://www.learntechlib.org/primary/p/222666The repository includes these files:"submissions.csv": This data file captures the evaluation results of programming assignments. It is organized by the following columns: <ul><li>"user_id": The unique identifier for each student who submitted the assignment.</li><li>"task_id": The unique identifier for each task that received submissions.</li><li>"submission_seconds": The number of seconds since the first user accessed the initial task's description within the system.</li><li>"correct": The outcome of the evaluation (1 denotes correct; 0 denotes incorrect).</li><li>"subject": The specific subject matter that the task addresses.</li></ul> "subjects.csv": This data file comprises the roster of subjects for which tasks have been assigned within the system. It includes these columns: <ul><li>"subject_id": The unique identifier for each subject.</li><li>"subject": The actual name of the subject.</li></ul>

opencc-zeroJun 2023View details →

zenodo40/100

Dataset for the assessment of presence and performance in an augmented reality environment for motor imitation learning: a case-study on violinists.

Data description <ol> <li>Repository structure</li> </ol> The repository contains several zip files, which contain a set of individual data files. We describe the general content of every zip file and supplement this information with a table describing the individual data files in the zip file. An overview of the different zip-files is given in Table 1.   <table> <tbody> <tr> <td> Zip-files in repository </td> <td> description </td> </tr> <tr> <td> Labeled_MoCap_Data.zip </td> <td> Labeled motion capture data </td> </tr> <tr> <td> Joint_Angle_Data.zip </td> <td> Joint angles extracted from mocap data </td> </tr> <tr> <td> Analyzed_Data.zip </td> <td> Filtered and analyzed mocap data </td> </tr> <tr> <td> Audio_Data.zip </td> <td> Audio data participants </td> </tr> <tr> <td> Questionnaire_Data.zip </td> <td> Questionnaire data </td> </tr> <tr> <td> Scores.zip </td> <td> Scores played by participants </td> </tr> <tr> <td> Avatar_Data.zip </td> <td> All data collected for the avatars </td> </tr> </tbody> </table>  Table 1: overview of different zip-files in repository.   <ol> <li> </li> </ol> Csv format with labeled MoCap Data, including data labels. Every column is a data stream from a marker. Every marker has 3 data streams, referring to the x, y, and z coordinates of the marker position. In addition, the violin (3-4 markers) and the violin bow (3 markers) are labelled as well. An overview of the different labels and their meaning is given in Table 2. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (MoCap), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_MoCap.csv’ for a participant (see Table 2).   <table> <tbody> <tr> <td> File Name </td> <td> Labeled_MoCap_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Labeled MoCap Data </td> </tr> <tr> <td> P001_T2_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_MoCap.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_MoCap.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_MoCap.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_MoCap.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_MoCap.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_MoCap.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_MoCap.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_MoCap.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_MoCap.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_MoCap.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_MoCap.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_MoCap.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_MoCap.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_MoCap.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_MoCap.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_MoCap.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_MoCap.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_MoCap.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_MoCap.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_MoCap.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_MoCap.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_MoCap.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 2: content and file structure of Labeled_MoCap_Data.zip.   <ol> <li> </li> </ol> Csv format with joint angles, including data labels. Every column is a data stream from a joint. Every joint has a varying number of data streams, depending on the calculated angles. In addition to joint angles, the angles of the instrument relative to the body are given as well, the distances of the bow to the bridge, and to distances of the bow to the strings, respectively. An overview of the different labels and their meaning is given in Table 3. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (JointAngles), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_JointAngles.csv’ for a participant (see Table 3).   <table> <tbody> <tr> <td> File Name </td> <td> Joint_Angle_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Joint Angle Data </td> </tr> <tr> <td> P001_T2_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_JointAngles.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_JointAngles.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_JointAngles.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_JointAngles.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_JointAngles.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_JointAngles.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_JointAngles.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_JointAngles.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_JointAngles.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_JointAngles.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_JointAngles.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_JointAngles.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_JointAngles.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_JointAngles.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_JointAngles.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_JointAngles.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_JointAngles.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_JointAngles.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_JointAngles.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_JointAngles.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_JointAngles.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_JointAngles.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 3: content and file structure of Joint_Angle_Data.zip.   <ol> <li> </li> </ol> Time series of filtered and analyzed data. The distances of the bow to the bridge and frog, are filtered so that only bow strokes with a certain bowing length and a certain loudness level are retained. The resulting collection of regions-of-interest (ROIs) is then analyzed for movement smoothness (as assessed with the SPARC index), and a comparison is made between the profile of avatar bowing movements and participant bowing movements by means of the Procrustes distance. These data are presented as csv files with 4 columns: SPARC index per ROI, Procrustes distance between the bow movement of the avatar and participant, index of start and end of each ROI. One data file per participant (P001-P011), per trial (T1-T4), per condition (2D/3D) is presented. Additionally, the data type (AnalyzedData), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_ AnalyzedData.csv’ for a participant (see Table 4).   <table> <tbody> <tr> <td> File Name </td> <td> Analyzed_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Analyzed Data </td> </tr> <tr> <td> P001_T2_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_AnalyzedData.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_AnalyzedData.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_AnalyzedData.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_AnalyzedData.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_AnalyzedData.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_AnalyzedData.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_AnalyzedData.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_AnalyzedData.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_AnalyzedData.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_AnalyzedData.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_AnalyzedData.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_AnalyzedData.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_AnalyzedData.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_AnalyzedData.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_AnalyzedData.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_AnalyzedData.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_AnalyzedData.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_AnalyzedData.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_AnalyzedData.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_AnalyzedData.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_AnalyzedData.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_AnalyzedData.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 4: content and file structure of Analyzed_Data.zip.   <ol> <li> </li> </ol> Wav-files are presented per participant (P001-P011), per trial (T1-T4), per condition (2D/3D). Audio files contain 2 tracks (left and right microphone), i.e., they are stereo recordings. Additionally, the data type (Audio), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘P001_T1_2D_F1_Audio.wav’ for a participant (see Table 5).   <table> <tbody> <tr> <td> File Name </td> <td> Audio_Data.zip </td> </tr> <tr> <td> Content </td> <td> Participant </td> <td> Trial </td> <td> Condition </td> <td> Piece </td> <td> Data Type </td> </tr> <tr> <td> P001_T1_2D_F2_Audio.csv </td> <td> 1 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> Audio Data </td> </tr> <tr> <td> P001_T2_2D_F2_Audio.csv </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T3_2D_F2_Audio.csv </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T4_2D_F2_Audio.csv </td> <td> 1 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P001_T1_3D_F1_Audio.csv </td> <td> 1 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T2_3D_F1_Audio.csv </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T3_3D_F1_Audio.csv </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P001_T4_3D_F1_Audio.csv </td> <td> 1 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_2D_F1_Audio.csv </td> <td> 2 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T2_2D_F1_Audio.csv </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T3_2D_F1_Audio.csv </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T4_2D_F1_Audio.csv </td> <td> 2 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P002_T1_3D_F2_Audio.csv </td> <td> 2 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T2_3D_F2_Audio.csv </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T3_3D_F2_Audio.csv </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P002_T4_3D_F2_Audio.csv </td> <td> 2 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P003_T1_2D_F3_Audio.csv </td> <td> 3 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T2_2D_F3_Audio.csv </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T3_2D_F3_Audio.csv </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T4_2D_F3_Audio.csv </td> <td> 3 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P003_T1_3D_F4_Audio.csv </td> <td> 3 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T2_3D_F4_Audio.csv </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T3_3D_F4_Audio.csv </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P003_T4_3D_F4_Audio.csv </td> <td> 3 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P004_T1_2D_F1_Audio.csv </td> <td> 4 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T2_2D_F1_Audio.csv </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T3_2D_F1_Audio.csv </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T4_2D_F1_Audio.csv </td> <td> 4 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P004_T1_3D_F2_Audio.csv </td> <td> 4 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T2_3D_F2_Audio.csv </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T3_3D_F2_Audio.csv </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P004_T4_3D_F2_Audio.csv </td> <td> 4 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P005_T1_2D_F3_Audio.csv </td> <td> 5 </td> <td> 1 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T2_2D_F3_Audio.csv </td> <td> 5 </td> <td> 2 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T3_2D_F3_Audio.csv </td> <td> 5 </td> <td> 3 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T4_2D_F3_Audio.csv </td> <td> 5 </td> <td> 4 </td> <td> 2 </td> <td> 3 </td> </tr> <tr> <td> P005_T1_3D_F4_Audio.csv </td> <td> 5 </td> <td> 1 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T2_3D_F4_Audio.csv </td> <td> 5 </td> <td> 2 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T3_3D_F4_Audio.csv </td> <td> 5 </td> <td> 3 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P005_T4_3D_F4_Audio.csv </td> <td> 5 </td> <td> 4 </td> <td> 3 </td> <td> 4 </td> </tr> <tr> <td> P006_T1_2D_F1_Audio.csv </td> <td> 6 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T2_2D_F1_Audio.csv </td> <td> 6 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T3_2D_F1_Audio.csv </td> <td> 6 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T4_2D_F1_Audio.csv </td> <td> 6 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P006_T1_3D_F2_Audio.csv </td> <td> 6 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T2_3D_F2_Audio.csv </td> <td> 6 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T3_3D_F2_Audio.csv </td> <td> 6 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P006_T4_3D_F2_Audio.csv </td> <td> 6 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P007_T1_2D_F4_Audio.csv </td> <td> 7 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T2_2D_F4_Audio.csv </td> <td> 7 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T3_2D_F4_Audio.csv </td> <td> 7 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T4_2D_F4_Audio.csv </td> <td> 7 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P007_T1_3D_F3_Audio.csv </td> <td> 7 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T2_3D_F3_Audio.csv </td> <td> 7 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T3_3D_F3_Audio.csv </td> <td> 7 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P007_T4_3D_F3_Audio.csv </td> <td> 7 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T1_2D_F4_Audio.csv </td> <td> 8 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T2_2D_F4_Audio.csv </td> <td> 8 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T3_2D_F4_Audio.csv </td> <td> 8 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T4_2D_F4_Audio.csv </td> <td> 8 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P008_T1_3D_F3_Audio.csv </td> <td> 8 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T2_3D_F3_Audio.csv </td> <td> 8 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T3_3D_F3_Audio.csv </td> <td> 8 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P008_T4_3D_F3_Audio.csv </td> <td> 8 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P009_T1_2D_F1_Audio.csv </td> <td> 9 </td> <td> 1 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T2_2D_F1_Audio.csv </td> <td> 9 </td> <td> 2 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T3_2D_F1_Audio.csv </td> <td> 9 </td> <td> 3 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T4_2D_F1_Audio.csv </td> <td> 9 </td> <td> 4 </td> <td> 2 </td> <td> 1 </td> </tr> <tr> <td> P009_T1_3D_F2_Audio.csv </td> <td> 9 </td> <td> 1 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T2_3D_F2_Audio.csv </td> <td> 9 </td> <td> 2 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T3_3D_F2_Audio.csv </td> <td> 9 </td> <td> 3 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P009_T4_3D_F2_Audio.csv </td> <td> 9 </td> <td> 4 </td> <td> 3 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_2D_F2_Audio.csv </td> <td> 10 </td> <td> 1 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T2_2D_F2_Audio.csv </td> <td> 10 </td> <td> 2 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T3_2D_F2_Audio.csv </td> <td> 10 </td> <td> 3 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T4_2D_F2_Audio.csv </td> <td> 10 </td> <td> 4 </td> <td> 2 </td> <td> 2 </td> </tr> <tr> <td> P010_T1_3D_F1_Audio.csv </td> <td> 10 </td> <td> 1 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T2_3D_F1_Audio.csv </td> <td> 10 </td> <td> 2 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T3_3D_F1_Audio.csv </td> <td> 10 </td> <td> 3 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P010_T4_3D_F1_Audio.csv </td> <td> 10 </td> <td> 4 </td> <td> 3 </td> <td> 1 </td> </tr> <tr> <td> P011_T1_2D_F4_Audio.csv </td> <td> 11 </td> <td> 1 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T2_2D_F4_Audio.csv </td> <td> 11 </td> <td> 2 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T3_2D_F4_Audio.csv </td> <td> 11 </td> <td> 3 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T4_2D_F4_Audio.csv </td> <td> 11 </td> <td> 4 </td> <td> 2 </td> <td> 4 </td> </tr> <tr> <td> P011_T1_3D_F3_Audio.csv </td> <td> 11 </td> <td> 1 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T2_3D_F3_Audio.csv </td> <td> 11 </td> <td> 2 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T3_3D_F3_Audio.csv </td> <td> 11 </td> <td> 3 </td> <td> 3 </td> <td> 3 </td> </tr> <tr> <td> P011_T4_3D_F3_Audio.csv </td> <td> 11 </td> <td> 4 </td> <td> 3 </td> <td> 3 </td> </tr> </tbody> </table> Table 5: content and file structure of Audio_Data.zip.   <ol> <li> </li> </ol> The results of 5 standardized questionnaires are presented: the Makransky Multimodal Presence Questionnaire (the social presence subset or MPQS and the physical presence subset or MPQP), the Witmer Presence Questionnaire (WPQ), the Immersive Tendencies Questionnaire (ITQ), the Musical Sophistication Index (MSI), and the Sense of Musical Agency Questionnaire (SOMA). Additionally, demographic data (DQ) were collected, along with some open questions (OQ). The answers to the questionnaires are organized in 3 csv files: ‘MB.csv’, containing answers to the questionnaires presented before the first session (ITQ, MSI and some DQ); and ‘C1.csv’ and ‘C2.csv’, containing the answers to the questionnaires presented before and after each session (MPQS, MPQP, WPQ, SOMA, some DQ and some OQ) in the first and second condition, respectively. A csv file named ‘Legend.csv’ indicates the codes of all the questions, and where the answers to the questions can be found (see Table 6). Since some participants answered in Dutch, all responses were translated to English before adding them to the repository.   <table> <tbody> <tr> <td> File Name </td> <td> Questionnaire_Data.zip </td> </tr> <tr> <td> Content </td> </tr> <tr> <td> C1.csv </td> <td> questionnaires and answeres of condition 1 </td> </tr> <tr> <td> C2.csv </td> <td> questionnaires and answeres of condition 2 </td> </tr> <tr> <td> MB.csv </td> <td> questionnaires and answers related to musical background </td> </tr> <tr> <td> Legend.csv </td> <td> questions and question codes </td> </tr> </tbody> </table> Table 6: content and file structure of Questionnaire_Data.zip.   <ol> <li> </li> </ol> The scores which were played by both the avatar and the participants are provided, with the correct bowings and articulations. The fragment and the violin section are indicated in the filename. E.g., ‘First_Violin_F2.pdf’, contains the scores of fragment F2, as played by the first violins. See Table 7 for an overview of the file structure and the content.   <table> <tbody> <tr> <td> File Name </td> <td> Scores.zip </td> </tr> <tr> <td> Content </td> </tr> <tr> <td> First_Violin_F1.pdf </td> <td> Fragment F1 as played by the first violin section </td> </tr> <tr> <td> First_Violin_F2.pdf </td> <td> Fragment F2 as played by the first violin section </td> </tr> <tr> <td> Second_Violin_F3.pdf </td> <td> Fragment F3 as played by the second violin section </td> </tr> <tr> <td> Second_Violin_F4.pdf </td> <td> Fragment F4 as played by the second violin section </td> </tr> </tbody> </table> Table 7: content and file structure of Scores.zip.   <ol> <li> </li> </ol> This directory contains files in csv format with labeled MoCap Data, including data labels. Every column is a data stream from a marker. Every marker has 3 data streams, referring to the x, y, and z coordinates of the marker position. In addition, the violin (3-4 markers) and the violin bow (3 markers) are labelled as well. One data file per avatar (First Violin or Second Violin) is presented. Additionally, the data type (MoCap), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘First_Violin_F2_MoCap.csv’ for an avatar (see Table 8). Additionally, the directory contains files in csv format with joint angles, including data labels. Every column is a data stream from a joint. Every joint has a varying number of data streams, depending on the calculated angles. In addition to joint angles, the angles of the instrument relative to the body are given as well, the distances of the bow to the bridge, and the distances of the bow to the strings, respectively. One data file per avatar (First Violin or Second Violin) is presented. Additionally, the data type (JointAngles), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘Second_Violin_F3_JointAngles.csv’ for an avatar (see Table 8). Finally, this directory contains wav-files per avatar (First Violin or Second Violin). Audio files contain 2 tracks (left and right microphone), i.e., they are stereo recordings. Additionally, the data type (Audio), and the performed fragment (F1-F4) are given in the filename. An example of a file name is e.g., ‘First_Violin_F1_Audio.wav’ for an avatar (see Table 8).   <table> <tbody> <tr> <td> File Name </td> <td> Avatar_Data.zip </td> </tr> <tr> <td> Content </td> </tr> <tr> <td> First_Violin_F1_MoCap.csv </td> <td> MoCap data of the first violin avatar, playing fragment F1 </td> </tr> <tr> <td> First_Violin_F1_JointAngles.csv </td> <td> Joint angle data of the first violin avatar, playing fragment F1 </td> </tr> <tr> <td> First_Violin_F1_Audio.wav </td> <td> Audio data of the first violin avatar, playing fragment F1 </td> </tr> <tr> <td> First_Violin_F2_MoCap.csv </td> <td> MoCap data of the first violin avatar, playing fragment F2 </td> </tr> <tr> <td> First_Violin_F2_JointAngles.csv </td> <td> Joint angle data of the first violin avatar, playing fragment F2 </td> </tr> <tr> <td> First_Violin_F2_Audio.wav </td> <td> Audio data of the first violin avatar, playing fragment F2 </td> </tr> <tr> <td> Second_Violin_F3_MoCap.csv </td> <td> MoCap data of the second violin avatar, playing fragment F3 </td> </tr> <tr> <td> Second_Violin_F3_JointAngles.csv </td> <td> Joint angle data of the second violin avatar, playing fragment F3 </td> </tr> <tr> <td> Second_Violin_F3_Audio.wav </td> <td> Audio data of the second violin avatar, playing fragment F3 </td> </tr> <tr> <td> Second_Violin_F4_MoCap.csv </td> <td> MoCap data of the second violin avatar, playing fragment F4 </td> </tr> <tr> <td> Second_Violin_F4_JointAngles.csv </td> <td> Joint angle data of the second violin avatar, playing fragment F4 </td> </tr> <tr> <td> Second_Violin_F4_Audio.wav </td> <td> Audio data of the second violin avatar, playing fragment F4 </td> </tr> </tbody> </table> Table 8: content and file structure of Avatar_Data.zip.

opencc-by-4.0Jul 2023View details →

zenodo40/100

Environmental Performance Assessment of a Novel Process Concept for Propanol Production from Widely Available and Wasted Methane Sources

Dataset for associated publication.

opencc-by-4.0Jul 2022View details →

zenodo40/100

ChatGPT's performance in dentistry and allergy-immunology assessments: a comparative study

Data on ChatGPT 3's and ChatGPT 4's performance on self-assessment questions for dentistry (SFLEDM) and allergy and clinical immunology (EEAACI), sourced from the University of Bern’s Institute for Medical Education platform.

opencc-by-4.0Dec 2022View details →

dryad40/100