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

Data description

Repository structure

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.

Zip-files in repository

description

Labeled_MoCap_Data.zip

Labeled motion capture data

Joint_Angle_Data.zip

Joint angles extracted from mocap data

Analyzed_Data.zip

Filtered and analyzed mocap data

Audio_Data.zip

Audio data participants

Questionnaire_Data.zip

Questionnaire data

Scores.zip

Scores played by participants

Avatar_Data.zip

All data collected for the avatars

 Table 1: overview of different zip-files in repository.

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).

File Name

Labeled_MoCap_Data.zip

Content

Participant

Trial

Condition

Piece

Data Type

P001_T1_2D_F2_MoCap.csv

1

1

2

2

Labeled MoCap Data

P001_T2_2D_F2_MoCap.csv

1

2

2

2

P001_T3_2D_F2_MoCap.csv

1

3

2

2

P001_T4_2D_F2_MoCap.csv

1

4

2

2

P001_T1_3D_F1_MoCap.csv

1

1

3

1

P001_T2_3D_F1_MoCap.csv

1

2

3

1

P001_T3_3D_F1_MoCap.csv

1

3

3

1

P001_T4_3D_F1_MoCap.csv

1

4

3

1

P002_T1_2D_F1_MoCap.csv

2

1

2

1

P002_T2_2D_F1_MoCap.csv

2

2

2

1

P002_T3_2D_F1_MoCap.csv

2

3

2

1

P002_T4_2D_F1_MoCap.csv

2

4

2

1

P002_T1_3D_F2_MoCap.csv

2

1

3

2

P002_T2_3D_F2_MoCap.csv

2

2

3

2

P002_T3_3D_F2_MoCap.csv

2

3

3

2

P002_T4_3D_F2_MoCap.csv

2

4

3

2

P003_T1_2D_F3_MoCap.csv

3

1

2

3

P003_T2_2D_F3_MoCap.csv

3

2

2

3

P003_T3_2D_F3_MoCap.csv

3

3

2

3

P003_T4_2D_F3_MoCap.csv

3

4

2

3

P003_T1_3D_F4_MoCap.csv

3

1

3

4

P003_T2_3D_F4_MoCap.csv

3

2

3

4

P003_T3_3D_F4_MoCap.csv

3

3

3

4

P003_T4_3D_F4_MoCap.csv

3

4

3

4

P004_T1_2D_F1_MoCap.csv

4

1

2

1

P004_T2_2D_F1_MoCap.csv

4

2

2

1

P004_T3_2D_F1_MoCap.csv

4

3

2

1

P004_T4_2D_F1_MoCap.csv

4

4

2

1

P004_T1_3D_F2_MoCap.csv

4

1

3

2

P004_T2_3D_F2_MoCap.csv

4

2

3

2

P004_T3_3D_F2_MoCap.csv

4

3

3

2

P004_T4_3D_F2_MoCap.csv

4

4

3

2

P005_T1_2D_F3_MoCap.csv

5

1

2

3

P005_T2_2D_F3_MoCap.csv

5

2

2

3

P005_T3_2D_F3_MoCap.csv

5

3

2

3

P005_T4_2D_F3_MoCap.csv

5

4

2

3

P005_T1_3D_F4_MoCap.csv

5

1

3

4

P005_T2_3D_F4_MoCap.csv

5

2

3

4

P005_T3_3D_F4_MoCap.csv

5

3

3

4

P005_T4_3D_F4_MoCap.csv

5

4

3

4

P006_T1_2D_F1_MoCap.csv

6

1

2

1

P006_T2_2D_F1_MoCap.csv

6

2

2

1

P006_T3_2D_F1_MoCap.csv

6

3

2

1

P006_T4_2D_F1_MoCap.csv

6

4

2

1

P006_T1_3D_F2_MoCap.csv

6

1

3

2

P006_T2_3D_F2_MoCap.csv

6

2

3

2

P006_T3_3D_F2_MoCap.csv

6

3

3

2

P006_T4_3D_F2_MoCap.csv

6

4

3

2

P007_T1_2D_F4_MoCap.csv

7

1

2

4

P007_T2_2D_F4_MoCap.csv

7

2

2

4

P007_T3_2D_F4_MoCap.csv

7

3

2

4

P007_T4_2D_F4_MoCap.csv

7

4

2

4

P007_T1_3D_F3_MoCap.csv

7

1

3

3

P007_T2_3D_F3_MoCap.csv

7

2

3

3

P007_T3_3D_F3_MoCap.csv

7

3

3

3

P007_T4_3D_F3_MoCap.csv

7

4

3

3

P008_T1_2D_F4_MoCap.csv

8

1

2

4

P008_T2_2D_F4_MoCap.csv

8

2

2

4

P008_T3_2D_F4_MoCap.csv

8

3

2

4

P008_T4_2D_F4_MoCap.csv

8

4

2

4

P008_T1_3D_F3_MoCap.csv

8

1

3

3

P008_T2_3D_F3_MoCap.csv

8

2

3

3

P008_T3_3D_F3_MoCap.csv

8

3

3

3

P008_T4_3D_F3_MoCap.csv

8

4

3

3

P009_T1_2D_F1_MoCap.csv

9

1

2

1

P009_T2_2D_F1_MoCap.csv

9

2

2

1

P009_T3_2D_F1_MoCap.csv

9

3

2

1

P009_T4_2D_F1_MoCap.csv

9

4

2

1

P009_T1_3D_F2_MoCap.csv

9

1

3

2

P009_T2_3D_F2_MoCap.csv

9

2

3

2

P009_T3_3D_F2_MoCap.csv

9

3

3

2

P009_T4_3D_F2_MoCap.csv

9

4

3

2

P010_T1_2D_F2_MoCap.csv

10

1

2

2

P010_T2_2D_F2_MoCap.csv

10

2

2

2

P010_T3_2D_F2_MoCap.csv

10

3

2

2

P010_T4_2D_F2_MoCap.csv

10

4

2

2

P010_T1_3D_F1_MoCap.csv

10

1

3

1

P010_T2_3D_F1_MoCap.csv

10

2

3

1

P010_T3_3D_F1_MoCap.csv

10

3

3

1

P010_T4_3D_F1_MoCap.csv

10

4

3

1

P011_T1_2D_F4_MoCap.csv

11

1

2

4

P011_T2_2D_F4_MoCap.csv

11

2

2

4

P011_T3_2D_F4_MoCap.csv

11

3

2

4

P011_T4_2D_F4_MoCap.csv

11

4

2

4

P011_T1_3D_F3_MoCap.csv

11

1

3

3

P011_T2_3D_F3_MoCap.csv

11

2

3

3

P011_T3_3D_F3_MoCap.csv

11

3

3

3

P011_T4_3D_F3_MoCap.csv

11

4

3

3

Table 2: content and file structure of Labeled_MoCap_Data.zip.

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).

File Name

Joint_Angle_Data.zip

Content

Participant

Trial

Condition

Piece

Data Type

P001_T1_2D_F2_JointAngles.csv

1

1

2

2

Joint Angle Data

P001_T2_2D_F2_JointAngles.csv

1

2

2

2

P001_T3_2D_F2_JointAngles.csv

1

3

2

2

P001_T4_2D_F2_JointAngles.csv

1

4

2

2

P001_T1_3D_F1_JointAngles.csv

1

1

3

1

P001_T2_3D_F1_JointAngles.csv

1

2

3

1

P001_T3_3D_F1_JointAngles.csv

1

3

3

1

P001_T4_3D_F1_JointAngles.csv

1

4

3

1

P002_T1_2D_F1_JointAngles.csv

2

1

2

1

P002_T2_2D_F1_JointAngles.csv

2

2

2

1

P002_T3_2D_F1_JointAngles.csv

2

3

2

1

P002_T4_2D_F1_JointAngles.csv

2

4

2

1

P002_T1_3D_F2_JointAngles.csv

2

1

3

2

P002_T2_3D_F2_JointAngles.csv

2

2

3

2

P002_T3_3D_F2_JointAngles.csv

2

3

3

2

P002_T4_3D_F2_JointAngles.csv

2

4

3

2

P003_T1_2D_F3_JointAngles.csv

3

1

2

3

P003_T2_2D_F3_JointAngles.csv

3

2

2

3

P003_T3_2D_F3_JointAngles.csv

3

3

2

3

P003_T4_2D_F3_JointAngles.csv

3

4

2

3

P003_T1_3D_F4_JointAngles.csv

3

1

3

4

P003_T2_3D_F4_JointAngles.csv

3

2

3

4

P003_T3_3D_F4_JointAngles.csv

3

3

3

4

P003_T4_3D_F4_JointAngles.csv

3

4

3

4

P004_T1_2D_F1_JointAngles.csv

4

1

2

1

P004_T2_2D_F1_JointAngles.csv

4

2

2

1

P004_T3_2D_F1_JointAngles.csv

4

3

2

1

P004_T4_2D_F1_JointAngles.csv

4

4

2

1

P004_T1_3D_F2_JointAngles.csv

4

1

3

2

P004_T2_3D_F2_JointAngles.csv

4

2

3

2

P004_T3_3D_F2_JointAngles.csv

4

3

3

2

P004_T4_3D_F2_JointAngles.csv

4

4

3

2

P005_T1_2D_F3_JointAngles.csv

5

1

2

3

P005_T2_2D_F3_JointAngles.csv

5

2

2

3

P005_T3_2D_F3_JointAngles.csv

5

3

2

3

P005_T4_2D_F3_JointAngles.csv

5

4

2

3

P005_T1_3D_F4_JointAngles.csv

5

1

3

4

P005_T2_3D_F4_JointAngles.csv

5

2

3

4

P005_T3_3D_F4_JointAngles.csv

5

3

3

4

P005_T4_3D_F4_JointAngles.csv

5

4

3

4

P006_T1_2D_F1_JointAngles.csv

6

1

2

1

P006_T2_2D_F1_JointAngles.csv

6

2

2

1

P006_T3_2D_F1_JointAngles.csv

6

3

2

1

P006_T4_2D_F1_JointAngles.csv

6

4

2

1

P006_T1_3D_F2_JointAngles.csv

6

1

3

2

P006_T2_3D_F2_JointAngles.csv

6

2

3

2

P006_T3_3D_F2_JointAngles.csv

6

3

3

2

P006_T4_3D_F2_JointAngles.csv

6

4

3

2

P007_T1_2D_F4_JointAngles.csv

7

1

2

4

P007_T2_2D_F4_JointAngles.csv

7

2

2

4

P007_T3_2D_F4_JointAngles.csv

7

3

2

4

P007_T4_2D_F4_JointAngles.csv

7

4

2

4

P007_T1_3D_F3_JointAngles.csv

7

1

3

3

P007_T2_3D_F3_JointAngles.csv

7

2

3

3

P007_T3_3D_F3_JointAngles.csv

7

3

3

3

P007_T4_3D_F3_JointAngles.csv

7

4

3

3

P008_T1_2D_F4_JointAngles.csv

8

1

2

4

P008_T2_2D_F4_JointAngles.csv

8

2

2

4

P008_T3_2D_F4_JointAngles.csv

8

3

2

4

P008_T4_2D_F4_JointAngles.csv

8

4

2

4

P008_T1_3D_F3_JointAngles.csv

8

1

3

3

P008_T2_3D_F3_JointAngles.csv

8

2

3

3

P008_T3_3D_F3_JointAngles.csv

8

3

3

3

P008_T4_3D_F3_JointAngles.csv

8

4

3

3

P009_T1_2D_F1_JointAngles.csv

9

1

2

1

P009_T2_2D_F1_JointAngles.csv

9

2

2

1

P009_T3_2D_F1_JointAngles.csv

9

3

2

1

P009_T4_2D_F1_JointAngles.csv

9

4

2

1

P009_T1_3D_F2_JointAngles.csv

9

1

3

2

P009_T2_3D_F2_JointAngles.csv

9

2

3

2

P009_T3_3D_F2_JointAngles.csv

9

3

3

2

P009_T4_3D_F2_JointAngles.csv

9

4

3

2

P010_T1_2D_F2_JointAngles.csv

10

1

2

2

P010_T2_2D_F2_JointAngles.csv

10

2

2

2

P010_T3_2D_F2_JointAngles.csv

10

3

2

2

P010_T4_2D_F2_JointAngles.csv

10

4

2

2

P010_T1_3D_F1_JointAngles.csv

10

1

3

1

P010_T2_3D_F1_JointAngles.csv

10

2

3

1

P010_T3_3D_F1_JointAngles.csv

10

3

3

1

P010_T4_3D_F1_JointAngles.csv

10

4

3

1

P011_T1_2D_F4_JointAngles.csv

11

1

2

4

P011_T2_2D_F4_JointAngles.csv

11

2

2

4

P011_T3_2D_F4_JointAngles.csv

11

3

2

4

P011_T4_2D_F4_JointAngles.csv

11

4

2

4

P011_T1_3D_F3_JointAngles.csv

11

1

3

3

P011_T2_3D_F3_JointAngles.csv

11

2

3

3

P011_T3_3D_F3_JointAngles.csv

11

3

3

3

P011_T4_3D_F3_JointAngles.csv

11

4

3

3

Table 3: content and file structure of Joint_Angle_Data.zip.

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).

File Name

Analyzed_Data.zip

Content

Participant

Trial

Condition

Piece

Data Type

P001_T1_2D_F2_AnalyzedData.csv

1

1

2

2

Analyzed Data

P001_T2_2D_F2_AnalyzedData.csv

1

2

2

2

P001_T3_2D_F2_AnalyzedData.csv

1

3

2

2

P001_T4_2D_F2_AnalyzedData.csv

1

4

2

2

P001_T1_3D_F1_AnalyzedData.csv

1

1

3

1

P001_T2_3D_F1_AnalyzedData.csv

1

2

3

1

P001_T3_3D_F1_AnalyzedData.csv

1

3

3

1

P001_T4_3D_F1_AnalyzedData.csv

1

4

3

1

P002_T1_2D_F1_AnalyzedData.csv

2

1

2

1

P002_T2_2D_F1_AnalyzedData.csv

2

2

2

1

P002_T3_2D_F1_AnalyzedData.csv

2

3

2

1

P002_T4_2D_F1_AnalyzedData.csv

2

4

2

1

P002_T1_3D_F2_AnalyzedData.csv

2

1

3

2

P002_T2_3D_F2_AnalyzedData.csv

2

2

3

2

P002_T3_3D_F2_AnalyzedData.csv

2

3

3

2

P002_T4_3D_F2_AnalyzedData.csv

2

4

3

2

P003_T1_2D_F3_AnalyzedData.csv

3

1

2

3

P003_T2_2D_F3_AnalyzedData.csv

3

2

2

3

P003_T3_2D_F3_AnalyzedData.csv

3

3

2

3

P003_T4_2D_F3_AnalyzedData.csv

3

4

2

3

P003_T1_3D_F4_AnalyzedData.csv

3

1

3

4

P003_T2_3D_F4_AnalyzedData.csv

3

2

3

4

P003_T3_3D_F4_AnalyzedData.csv

3

3

3

4

P003_T4_3D_F4_AnalyzedData.csv

3

4

3

4

P004_T1_2D_F1_AnalyzedData.csv

4

1

2

1

P004_T2_2D_F1_AnalyzedData.csv

4

2

2

1

P004_T3_2D_F1_AnalyzedData.csv

4

3

2

1

P004_T4_2D_F1_AnalyzedData.csv

4

4

2

1

P004_T1_3D_F2_AnalyzedData.csv

4

1

3

2

P004_T2_3D_F2_AnalyzedData.csv

4

2

3

2

P004_T3_3D_F2_AnalyzedData.csv

4

3

3

2

P004_T4_3D_F2_AnalyzedData.csv

4

4

3

2

P005_T1_2D_F3_AnalyzedData.csv

5

1

2

3

P005_T2_2D_F3_AnalyzedData.csv

5

2

2

3

P005_T3_2D_F3_AnalyzedData.csv

5

3

2

3

P005_T4_2D_F3_AnalyzedData.csv

5

4

2

3

P005_T1_3D_F4_AnalyzedData.csv

5

1

3

4

P005_T2_3D_F4_AnalyzedData.csv

5

2

3

4

P005_T3_3D_F4_AnalyzedData.csv

5

3

3

4

P005_T4_3D_F4_AnalyzedData.csv

5

4

3

4

P006_T1_2D_F1_AnalyzedData.csv

6

1

2

1

P006_T2_2D_F1_AnalyzedData.csv

6

2

2

1

P006_T3_2D_F1_AnalyzedData.csv

6

3

2

1

P006_T4_2D_F1_AnalyzedData.csv

6

4

2

1

P006_T1_3D_F2_AnalyzedData.csv

6

1

3

2

P006_T2_3D_F2_AnalyzedData.csv

6

2

3

2

P006_T3_3D_F2_AnalyzedData.csv

6

3

3

2

P006_T4_3D_F2_AnalyzedData.csv

6

4

3

2

P007_T1_2D_F4_AnalyzedData.csv

7

1

2

4

P007_T2_2D_F4_AnalyzedData.csv

7

2

2

4

P007_T3_2D_F4_AnalyzedData.csv

7

3

2

4

P007_T4_2D_F4_AnalyzedData.csv

7

4

2

4

P007_T1_3D_F3_AnalyzedData.csv

7

1

3

3

P007_T2_3D_F3_AnalyzedData.csv

7

2

3

3

P007_T3_3D_F3_AnalyzedData.csv

7

3

3

3

P007_T4_3D_F3_AnalyzedData.csv

7

4

3

3

P008_T1_2D_F4_AnalyzedData.csv

8

1

2

4

P008_T2_2D_F4_AnalyzedData.csv

8

2

2

4

P008_T3_2D_F4_AnalyzedData.csv

8

3

2

4

P008_T4_2D_F4_AnalyzedData.csv

8

4

2

4

P008_T1_3D_F3_AnalyzedData.csv

8

1

3

3

P008_T2_3D_F3_AnalyzedData.csv

8

2

3

3

P008_T3_3D_F3_AnalyzedData.csv

8

3

3

3

P008_T4_3D_F3_AnalyzedData.csv

8

4

3

3

P009_T1_2D_F1_AnalyzedData.csv

9

1

2

1

P009_T2_2D_F1_AnalyzedData.csv

9

2

2

1

P009_T3_2D_F1_AnalyzedData.csv

9

3

2

1

P009_T4_2D_F1_AnalyzedData.csv

9

4

2

1

P009_T1_3D_F2_AnalyzedData.csv

9

1

3

2

P009_T2_3D_F2_AnalyzedData.csv

9

2

3

2

P009_T3_3D_F2_AnalyzedData.csv

9

3

3

2

P009_T4_3D_F2_AnalyzedData.csv

9

4

3

2

P010_T1_2D_F2_AnalyzedData.csv

10

1

2

2

P010_T2_2D_F2_AnalyzedData.csv

10

2

2

2

P010_T3_2D_F2_AnalyzedData.csv

10

3

2

2

P010_T4_2D_F2_AnalyzedData.csv

10

4

2

2

P010_T1_3D_F1_AnalyzedData.csv

10

1

3

1

P010_T2_3D_F1_AnalyzedData.csv

10

2

3

1

P010_T3_3D_F1_AnalyzedData.csv

10

3

3

1

P010_T4_3D_F1_AnalyzedData.csv

10

4

3

1

P011_T1_2D_F4_AnalyzedData.csv

11

1

2

4

P011_T2_2D_F4_AnalyzedData.csv

11

2

2

4

P011_T3_2D_F4_AnalyzedData.csv

11

3

2

4

P011_T4_2D_F4_AnalyzedData.csv

11

4

2

4

P011_T1_3D_F3_AnalyzedData.csv

11

1

3

3

P011_T2_3D_F3_AnalyzedData.csv

11

2

3

3

P011_T3_3D_F3_AnalyzedData.csv

11

3

3

3

P011_T4_3D_F3_AnalyzedData.csv

11

4

3

3

Table 4: content and file structure of Analyzed_Data.zip.

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).

File Name

Audio_Data.zip

Content

Participant

Trial

Condition

Piece

Data Type

P001_T1_2D_F2_Audio.csv

1

1

2

2

Audio Data

P001_T2_2D_F2_Audio.csv

1

2

2

2

P001_T3_2D_F2_Audio.csv

1

3

2

2

P001_T4_2D_F2_Audio.csv

1

4

2

2

P001_T1_3D_F1_Audio.csv

1

1

3

1

P001_T2_3D_F1_Audio.csv

1

2

3

1

P001_T3_3D_F1_Audio.csv

1

3

3

1

P001_T4_3D_F1_Audio.csv

1

4

3

1

P002_T1_2D_F1_Audio.csv

2

1

2

1

P002_T2_2D_F1_Audio.csv

2

2

2

1

P002_T3_2D_F1_Audio.csv

2

3

2

1

P002_T4_2D_F1_Audio.csv

2

4

2

1

P002_T1_3D_F2_Audio.csv

2

1

3

2

P002_T2_3D_F2_Audio.csv

2

2

3

2

P002_T3_3D_F2_Audio.csv

2

3

3

2

P002_T4_3D_F2_Audio.csv

2

4

3

2

P003_T1_2D_F3_Audio.csv

3

1

2

3

P003_T2_2D_F3_Audio.csv

3

2

2

3

P003_T3_2D_F3_Audio.csv

3

3

2

3

P003_T4_2D_F3_Audio.csv

3

4

2

3

P003_T1_3D_F4_Audio.csv

3

1

3

4

P003_T2_3D_F4_Audio.csv

3

2

3

4

P003_T3_3D_F4_Audio.csv

3

3

3

4

P003_T4_3D_F4_Audio.csv

3

4

3

4

P004_T1_2D_F1_Audio.csv

4

1

2

1

P004_T2_2D_F1_Audio.csv

4

2

2

1

P004_T3_2D_F1_Audio.csv

4

3

2

1

P004_T4_2D_F1_Audio.csv

4

4

2

1

P004_T1_3D_F2_Audio.csv

4

1

3

2

P004_T2_3D_F2_Audio.csv

4

2

3

2

P004_T3_3D_F2_Audio.csv

4

3

3

2

P004_T4_3D_F2_Audio.csv

4

4

3

2

P005_T1_2D_F3_Audio.csv

5

1

2

3

P005_T2_2D_F3_Audio.csv

5

2

2

3

P005_T3_2D_F3_Audio.csv

5

3

2

3

P005_T4_2D_F3_Audio.csv

5

4

2

3

P005_T1_3D_F4_Audio.csv

5

1

3

4

P005_T2_3D_F4_Audio.csv

5

2

3

4

P005_T3_3D_F4_Audio.csv

5

3

3

4

P005_T4_3D_F4_Audio.csv

5

4

3

4

P006_T1_2D_F1_Audio.csv

6

1

2

1

P006_T2_2D_F1_Audio.csv

6

2

2

1

P006_T3_2D_F1_Audio.csv

6

3

2

1

P006_T4_2D_F1_Audio.csv

6

4

2

1

P006_T1_3D_F2_Audio.csv

6

1

3

2

P006_T2_3D_F2_Audio.csv

6

2

3

2

P006_T3_3D_F2_Audio.csv

6

3

3

2

P006_T4_3D_F2_Audio.csv

6

4

3

2

P007_T1_2D_F4_Audio.csv

7

1

2

4

P007_T2_2D_F4_Audio.csv

7

2

2

4

P007_T3_2D_F4_Audio.csv

7

3

2

4

P007_T4_2D_F4_Audio.csv

7

4

2

4

P007_T1_3D_F3_Audio.csv

7

1

3

3

P007_T2_3D_F3_Audio.csv

7

2

3

3

P007_T3_3D_F3_Audio.csv

7

3

3

3

P007_T4_3D_F3_Audio.csv

7

4

3

3

P008_T1_2D_F4_Audio.csv

8

1

2

4

P008_T2_2D_F4_Audio.csv

8

2

2

4

P008_T3_2D_F4_Audio.csv

8

3

2

4

P008_T4_2D_F4_Audio.csv

8

4

2

4

P008_T1_3D_F3_Audio.csv

8

1

3

3

P008_T2_3D_F3_Audio.csv

8

2

3

3

P008_T3_3D_F3_Audio.csv

8

3

3

3

P008_T4_3D_F3_Audio.csv

8

4

3

3

P009_T1_2D_F1_Audio.csv

9

1

2

1

P009_T2_2D_F1_Audio.csv

9

2

2

1

P009_T3_2D_F1_Audio.csv

9

3

2

1

P009_T4_2D_F1_Audio.csv

9

4

2

1

P009_T1_3D_F2_Audio.csv

9

1

3

2

P009_T2_3D_F2_Audio.csv

9

2

3

2

P009_T3_3D_F2_Audio.csv

9

3

3

2

P009_T4_3D_F2_Audio.csv

9

4

3

2

P010_T1_2D_F2_Audio.csv

10

1

2

2

P010_T2_2D_F2_Audio.csv

10

2

2

2

P010_T3_2D_F2_Audio.csv

10

3

2

2

P010_T4_2D_F2_Audio.csv

10

4

2

2

P010_T1_3D_F1_Audio.csv

10

1

3

1

P010_T2_3D_F1_Audio.csv

10

2

3

1

P010_T3_3D_F1_Audio.csv

10

3

3

1

P010_T4_3D_F1_Audio.csv

10

4

3

1

P011_T1_2D_F4_Audio.csv

11

1

2

4

P011_T2_2D_F4_Audio.csv

11

2

2

4

P011_T3_2D_F4_Audio.csv

11

3

2

4

P011_T4_2D_F4_Audio.csv

11

4

2

4

P011_T1_3D_F3_Audio.csv

11

1

3

3

P011_T2_3D_F3_Audio.csv

11

2

3

3

P011_T3_3D_F3_Audio.csv

11

3

3

3

P011_T4_3D_F3_Audio.csv

11

4

3

3

Table 5: content and file structure of Audio_Data.zip.

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.

File Name

Questionnaire_Data.zip

Content

C1.csv

questionnaires and answeres of condition 1

C2.csv

questionnaires and answeres of condition 2

MB.csv

questionnaires and answers related to musical background

Legend.csv

questions and question codes

Table 6: content and file structure of Questionnaire_Data.zip.

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.

File Name

Scores.zip

Content

First_Violin_F1.pdf

Fragment F1 as played by the first violin section

First_Violin_F2.pdf

Fragment F2 as played by the first violin section

Second_Violin_F3.pdf

Fragment F3 as played by the second violin section

Second_Violin_F4.pdf

Fragment F4 as played by the second violin section

Table 7: content and file structure of Scores.zip.

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).

File Name

Avatar_Data.zip

Content

First_Violin_F1_MoCap.csv

MoCap data of the first violin avatar, playing fragment F1

First_Violin_F1_JointAngles.csv

Joint angle data of the first violin avatar, playing fragment F1

First_Violin_F1_Audio.wav

Audio data of the first violin avatar, playing fragment F1

First_Violin_F2_MoCap.csv

MoCap data of the first violin avatar, playing fragment F2

First_Violin_F2_JointAngles.csv

Joint angle data of the first violin avatar, playing fragment F2

First_Violin_F2_Audio.wav

Audio data of the first violin avatar, playing fragment F2

Second_Violin_F3_MoCap.csv

MoCap data of the second violin avatar, playing fragment F3

Second_Violin_F3_JointAngles.csv

Joint angle data of the second violin avatar, playing fragment F3

Second_Violin_F3_Audio.wav

Audio data of the second violin avatar, playing fragment F3

Second_Violin_F4_MoCap.csv

MoCap data of the second violin avatar, playing fragment F4

Second_Violin_F4_JointAngles.csv

Joint angle data of the second violin avatar, playing fragment F4

Second_Violin_F4_Audio.wav

Audio data of the second violin avatar, playing fragment F4

Table 8: content and file structure of Avatar_Data.zip.