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Investigating the Use of AI-Generated Exercises for Beginner and Intermediate Programming Courses: A ChatGPT Case Study
<p>In recent years, artificial intelligence (AI) has been increasingly used in education and supports teachers in creating educational material and students in their learning progress. AI- driven learning support has recently been further strengthened by the release of ChatGPT, in which users can retrieve expla- nations for various concepts in a few minutes through chat. However, to what extent the use of AI models, such as ChatGPT, is suitable for the creation of didactically and content-wise good exercises for programming courses is not yet known. Therefore, in this paper, we investigate the use of AI-generated exercises for beginner and intermediate programming courses in higher education using ChatGPT. We created 12 exercise sheets with ChatGPT for a beginner to intermediate programming course focusing on the objects-first approach. We report our process, prompts, and experience using ChatGPT for this task and outline good practices we identified. The generated exercises are assessed and revised, primarily using ChatGPT, until they met the requirements of the programming course. We assessed the quality of these exercises by using them in our course as external teaching assignment at the University of Education Ludwigsburg and let the students evaluate them. Results indicate the quality of the generated exercises and the time-saving for creating them using ChatGPT. However, our experience showed that while it is fast to generate a good version of an exercise, almost every exercise requires minor manual changes to improve its quality.</p>
APPENDIX 12 in Detangling the effects of patch attributes on bryophyte diversity in fragmented subtropical secondary forests - a case study of land-bridge islands
APPENDIX 12. — Relationships of accumulative species number with accumulative sampling efforts for eight largest islands.
FIG. 2 in Detangling the effects of patch attributes on bryophyte diversity in fragmented subtropical secondary forests - a case study of land-bridge islands
FIG. 2. — Relationships of species richness with number of habitat types, area, elevation, shape irregularity, vegetative cover, and ISW for five bryophyte categories in 168 forest fragments of the Thousand Island Lake, China. The regression equations are derived from GLMMs. Note: ISW, the relative proportion of water within a circle of a diameter of 1000 m centered on a given island.
openENTRANCE - Case Study 7 - Power-to-Heat Demand Flexibility: Results
<p>In case study 7 of the openENTRANCE project, Plan4EU, an electricity dispatch model for Europe, is soft-linked to the Flexibility Function, an indirect demand response model, via Frigg, a novel framework for integrating realistic demand response in energy system analysis. This modelling setup is applied to analyse the role of power-to-heat demand flexibility (end-consumer demand response and heat storage) in the Danish electricity system of 2050. This dataset contains results as presented in the related project report.</p>
Accounting for behaviour in fine-scale habitat selection: a case study highlighting methodological intricacies
<p>Data for the article “Accounting for behaviour in fine-scale habitat selection: a case study highlighting methodological intricacies”</p> <p>By LT Beumer, NMS Schmidt, J Pohle, J Signer, M Chimienti, JP Desforges, LH Hansen, SH Pedersen, DA Rudd, M Stelvig, FM van Beest</p> <p>The data set includes five files: A readme file describing the data files, and four data files accompanying the above publication.</p> <p>For further queries please contact Larissa T. Beumer: ltbeumer@gmail.com</p> <p> </p>
Results related to the case study 4 of the openENTRANCE project - SCOPE SD version 2023
<p>This dataset contains scenarios results for Case Study 4 of the openENTRANCE project.</p> <p>You can find additional information, including model results and case study setup, at Deliverable D6.2 of the openENTRANCE project at <a href="https://openentrance.eu/">openENTRANCE – open ENergy TRanstion ANalyses for a low-Carbon Economy</a>. </p> <p>Further information on the SCOPE SD model is given in: Frischmuth, F., Härtel, P.: Hydrogen sourcing strategies and cross-sectoral flexibility trade-offs in net-neutral energy scenarios for europe. Energy (2022). https://doi.org/10.1016/j.energy.2021.121598</p> <p>The data file follows the IAMC data format and the conventions established by the openENTRANCE project. See <a href="https://github.com/openENTRANCE/openentrance">https://github.com/openENTRANCE/openentrance</a> for details.</p> <p>Visit the openENTRANCE Scenario Explorer at <a href="https://data.ene.iiasa.ac.at/openentrance">https://data.ece.iiasa.ac.at/openentrance</a> for more information.</p> <p> </p>
Fig. 3 in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal
Fig. 3. Motor stereotypic behavior performed by the captive rhesus monkeys; A — under different time of the day; B — under different begging intensities (ns = statistically not significant difference).
Fig. 4. Probable relationship between the MSB and begging. A in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal
Fig. 4. Probable relationship between the MSB and begging. A — by controlling for sex of the captive monkeys; and, B — by controlling for the different probability of the visitor-monkey interaction (Min. — minutes).
Fig. 2 in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal
Fig. 2. Motor stereotypic behavior shown by the captive rhesus monkeys: A — difference between males and females; and B — on the basis of the different rearing histories (*** statistically significant difference).
Fig. 1 in Motor Stereotypic Behaviors In Zoo Rhesus Monkeys: A Case Study Of The Central Zoo, Kathmandu, Nepal
Fig. 1. Mean time invested on motor stereotypic behavior per focal sampling bout of 30 minutes by adult males and females (*** statistically significant difference).
Does social information affect the settlement decisions of resident birds in their second breeding attempt? A case study of the Japanese tit (Parus minor)
<p>Individuals may gather information about environmental conditions when deciding where to breed in order to maximize their lifetime fitness. Many studies have shown that birds can rely on social information to select their nest site. The location of active nests and the reproductive success of conspecifics and heterospecifics can provide accurate predictions about the quality of the breeding habitat. Some short-lived species can facultatively reproduce two and/or more times within a breeding season. However, few studies have focused on how multiple-brooding individuals select nest sites for their second breeding attempts. In this study, we use long-term data to test whether the Japanese tit (<em>Parus</em> <em>minor</em>) can use social information from conspecifics and/or heterospecifics to select a nest site for the second breeding attempt. Our results showed that the nest boxes occupied by tits on their second breeding attempt tended to be surrounded by more breeding conspecific nests, first-breeding successful conspecific nests, and fewer first-breeding failed conspecific nests than the nest boxes that remained unoccupied (the control group). However, the numbers of breeding heterospecific nests, successful heterospecific nests, and failed heterospecific nests did not differ between the nest boxes occupied by tits on their second breeding attempt and the unoccupied nest boxes. Furthermore, the tits with local successful breeding experience tended to choose areas with more first-breeding successful conspecific nests than those without successful breeding experience. Thus, we suggest that conspecifics' but not heterospecifics' social information within the same breeding season is the major factor influencing the nest site selection of Japanese tits during second breeding attempts.</p>
Dataset for the assessment of presence and performance in an augmented reality environment for motor imitation learning: a case-study on violinists.
<p><strong>Data description</strong></p> <ol> <li>Repository structure</li> </ol> <p>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.</p> <p> </p> <table> <tbody> <tr> <td> <p>Zip-files in repository</p> </td> <td> <p>description</p> </td> </tr> <tr> <td> <p>Labeled_MoCap_Data.zip</p> </td> <td> <p>Labeled motion capture data</p> </td> </tr> <tr> <td> <p>Joint_Angle_Data.zip</p> </td> <td> <p>Joint angles extracted from mocap data</p> </td> </tr> <tr> <td> <p>Analyzed_Data.zip</p> </td> <td> <p>Filtered and analyzed mocap data</p> </td> </tr> <tr> <td> <p>Audio_Data.zip</p> </td> <td> <p>Audio data participants</p> </td> </tr> <tr> <td> <p>Questionnaire_Data.zip</p> </td> <td> <p>Questionnaire data</p> </td> </tr> <tr> <td> <p>Scores.zip</p> </td> <td> <p>Scores played by participants</p> </td> </tr> <tr> <td> <p>Avatar_Data.zip</p> </td> <td> <p>All data collected for the avatars</p> </td> </tr> </tbody> </table> <p> Table 1: overview of different zip-files in repository.</p> <p> </p> <ol> <li> </li> </ol> <p>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).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Labeled_MoCap_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Labeled MoCap Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_MoCap.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_MoCap.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_MoCap.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_MoCap.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_MoCap.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_MoCap.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_MoCap.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_MoCap.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_MoCap.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_MoCap.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_MoCap.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 2: content and file structure of Labeled_MoCap_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>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).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Joint_Angle_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Joint Angle Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_JointAngles.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_JointAngles.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_JointAngles.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_JointAngles.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_JointAngles.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_JointAngles.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_JointAngles.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_JointAngles.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 3: content and file structure of Joint_Angle_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>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).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Analyzed_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Analyzed Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_AnalyzedData.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_AnalyzedData.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_AnalyzedData.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_AnalyzedData.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_AnalyzedData.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_AnalyzedData.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_AnalyzedData.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_AnalyzedData.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 4: content and file structure of Analyzed_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>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).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Audio_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> <td> <p>Participant</p> </td> <td> <p>Trial</p> </td> <td> <p>Condition</p> </td> <td> <p>Piece</p> </td> <td> <p>Data Type</p> </td> </tr> <tr> <td> <p>P001_T1_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>Audio Data</p> </td> </tr> <tr> <td> <p>P001_T2_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T3_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T4_2D_F2_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P001_T1_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T2_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T3_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P001_T4_3D_F1_Audio.csv</p> </td> <td> <p>1</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T2_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T3_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T4_2D_F1_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P002_T1_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T2_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T3_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P002_T4_3D_F2_Audio.csv</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P003_T1_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T2_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T3_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T4_2D_F3_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P003_T1_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T2_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T3_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P003_T4_3D_F4_Audio.csv</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P004_T1_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T2_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T3_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T4_2D_F1_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P004_T1_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T2_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T3_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P004_T4_3D_F2_Audio.csv</p> </td> <td> <p>4</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P005_T1_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T2_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T3_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T4_2D_F3_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P005_T1_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T2_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T3_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P005_T4_3D_F4_Audio.csv</p> </td> <td> <p>5</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P006_T1_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T2_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T3_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T4_2D_F1_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P006_T1_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T2_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T3_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P006_T4_3D_F2_Audio.csv</p> </td> <td> <p>6</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P007_T1_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T2_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T3_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T4_2D_F4_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P007_T1_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T2_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T3_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P007_T4_3D_F3_Audio.csv</p> </td> <td> <p>7</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T1_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T2_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T3_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T4_2D_F4_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P008_T1_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T2_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T3_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P008_T4_3D_F3_Audio.csv</p> </td> <td> <p>8</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P009_T1_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T2_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T3_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T4_2D_F1_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P009_T1_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T2_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T3_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P009_T4_3D_F2_Audio.csv</p> </td> <td> <p>9</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T2_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T3_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T4_2D_F2_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> </tr> <tr> <td> <p>P010_T1_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T2_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T3_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P010_T4_3D_F1_Audio.csv</p> </td> <td> <p>10</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>1</p> </td> </tr> <tr> <td> <p>P011_T1_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T2_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T3_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T4_2D_F4_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>2</p> </td> <td> <p>4</p> </td> </tr> <tr> <td> <p>P011_T1_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>1</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T2_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>2</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T3_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> <tr> <td> <p>P011_T4_3D_F3_Audio.csv</p> </td> <td> <p>11</p> </td> <td> <p>4</p> </td> <td> <p>3</p> </td> <td> <p>3</p> </td> </tr> </tbody> </table> <p>Table 5: content and file structure of Audio_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>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.</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Questionnaire_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> </tr> <tr> <td> <p>C1.csv</p> </td> <td> <p>questionnaires and answeres of condition 1</p> </td> </tr> <tr> <td> <p>C2.csv</p> </td> <td> <p>questionnaires and answeres of condition 2</p> </td> </tr> <tr> <td> <p>MB.csv</p> </td> <td> <p>questionnaires and answers related to musical background</p> </td> </tr> <tr> <td> <p>Legend.csv</p> </td> <td> <p>questions and question codes</p> </td> </tr> </tbody> </table> <p>Table 6: content and file structure of Questionnaire_Data.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>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.</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Scores.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> </tr> <tr> <td> <p>First_Violin_F1.pdf</p> </td> <td> <p>Fragment F1 as played by the first violin section</p> </td> </tr> <tr> <td> <p>First_Violin_F2.pdf</p> </td> <td> <p>Fragment F2 as played by the first violin section</p> </td> </tr> <tr> <td> <p>Second_Violin_F3.pdf</p> </td> <td> <p>Fragment F3 as played by the second violin section</p> </td> </tr> <tr> <td> <p>Second_Violin_F4.pdf</p> </td> <td> <p>Fragment F4 as played by the second violin section</p> </td> </tr> </tbody> </table> <p>Table 7: content and file structure of Scores.zip.</p> <p> </p> <ol> <li> </li> </ol> <p>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).</p> <p>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).</p> <p>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).</p> <p> </p> <table> <tbody> <tr> <td> <p>File Name</p> </td> <td> <p>Avatar_Data.zip</p> </td> </tr> <tr> <td> <p>Content</p> </td> </tr> <tr> <td> <p>First_Violin_F1_MoCap.csv</p> </td> <td> <p>MoCap data of the first violin avatar, playing fragment F1</p> </td> </tr> <tr> <td> <p>First_Violin_F1_JointAngles.csv</p> </td> <td> <p>Joint angle data of the first violin avatar, playing fragment F1</p> </td> </tr> <tr> <td> <p>First_Violin_F1_Audio.wav</p> </td> <td> <p>Audio data of the first violin avatar, playing fragment F1</p> </td> </tr> <tr> <td> <p>First_Violin_F2_MoCap.csv</p> </td> <td> <p>MoCap data of the first violin avatar, playing fragment F2</p> </td> </tr> <tr> <td> <p>First_Violin_F2_JointAngles.csv</p> </td> <td> <p>Joint angle data of the first violin avatar, playing fragment F2</p> </td> </tr> <tr> <td> <p>First_Violin_F2_Audio.wav</p> </td> <td> <p>Audio data of the first violin avatar, playing fragment F2</p> </td> </tr> <tr> <td> <p>Second_Violin_F3_MoCap.csv</p> </td> <td> <p>MoCap data of the second violin avatar, playing fragment F3</p> </td> </tr> <tr> <td> <p>Second_Violin_F3_JointAngles.csv</p> </td> <td> <p>Joint angle data of the second violin avatar, playing fragment F3</p> </td> </tr> <tr> <td> <p>Second_Violin_F3_Audio.wav</p> </td> <td> <p>Audio data of the second violin avatar, playing fragment F3</p> </td> </tr> <tr> <td> <p>Second_Violin_F4_MoCap.csv</p> </td> <td> <p>MoCap data of the second violin avatar, playing fragment F4</p> </td> </tr> <tr> <td> <p>Second_Violin_F4_JointAngles.csv</p> </td> <td> <p>Joint angle data of the second violin avatar, playing fragment F4</p> </td> </tr> <tr> <td> <p>Second_Violin_F4_Audio.wav</p> </td> <td> <p>Audio data of the second violin avatar, playing fragment F4</p> </td> </tr> </tbody> </table> <p>Table 8: content and file structure of Avatar_Data.zip.</p> <p> </p>
scenoRITA - Case Study Recording and Record File
<p>Recording and record file for a case study scenario described in the paper titled "scenoRITA: Generating Diverse, Fully-Mutable,<br> Test Scenarios for Autonomous Vehicle Planning".</p>
Geodetic displacement data from Airborne-LiDAR data and Time Series InSAR: Baton Rouge Case Study.
<p>This repository the results produced by Hurtado-Pulido, Amer, Ebinger, and Holcomb “Variations in subsidence patterns in the Gulf of Mexico passive margin from Airborne-LiDAR data and Time Series InSAR: Baton Rouge Case Study”.</p> <p>This repository presents data sets for figures 4, 5, 6, 7 and 8. Processing methods are described in the paper. The READme file contains details about each file. Please address any questions about this dataset to Hurtado-Pulido.</p> <ul> <li>LiDAR data from 1999 is stored and distributed by the Atlas: The Louisiana Statewide GIS (<a href="https://maps.ga.lsu.edu/lidar2000/">https://maps.ga.lsu.edu/lidar2000/</a>). LiDAR data from 2018 is stored and distributed by the USGS Server through The National Map Download Manager (<a href="https://apps.nationalmap.gov/downloader/">https://apps.nationalmap.gov/downloader/</a>).</li> <li>EnviSAT SAR images were retrieved from the Earth Observation Catalogue (<a href="https://eocat.esa.int/sec/#data-services-area">https://eocat.esa.int/sec/#data-services-area</a>). Sentinel-1 SAR images from the Copernicus Open Access Hub (<a href="https://scihub.copernicus.eu/dhus/#/home">https://scihub.copernicus.eu/dhus/#/home</a>). Both property of the European Space Agency.</li> <li>GNSS information was processed by the Nevada Geodetic Laboratory (Blewitt et al., 2018; <a href="http://geodesy.unr.edu/NGLStationPages/gpsnetmap/GPSNetMap.html">http://geodesy.unr.edu/NGLStationPages/gpsnetmap/GPSNetMap.html</a>).</li> <li>Data from water, injection, and extraction wells is stored in the Strategic Online Natural Resources Information System property of the Louisiana Department of Natural Resources (<a href="http://sonris-www.dnr.state.la.us/gis/agsweb/IE/JSViewer/index.html?TemplateID=181">http://sonris-www.dnr.state.la.us/gis/agsweb/IE/JSViewer/index.html?TemplateID=181</a>).</li> </ul>
The Awareness Assessment Model (Case Study Validation)
<p>Dataset of the case study validation of the paper "The Awareness Assessment Model: Measuring Awareness and Collaboration Support Over Participant's Perspective"</p>
T-Factor. WP2 Dataset: Advanced Case Study Interviews for Dortmunder U and Union Quarter
<p>This dataset presents five anonymized interviews performed in the city of Dortmund, Germany as part of the activities in Work Package 2 of the T-Factor project. The content of the interviews is relevant to the analysis of the Dortmunder U and Union Quarter urban redevelopment case study, in which the objective was to consult with experts and practitioners who had important roles in the implementation of temporary uses within the regeneration masterplan of the case study in question.</p>
Fig.2 in On the daily activity of the Red Fox (Vulpes vulpes) in two village areas of Bulgaria: a case study
Fig.2. Number of all pictures of the red fox (Vulpes vulpes) made in 24 hours interval (number of images per hour) for NP "Sinite Kamani" (Georgiev et al., 2015).
Fig. 3 in On the daily activity of the Red Fox (Vulpes vulpes) in two village areas of Bulgaria: a case study
Fig. 3. Number of all pictures of the fox (Vulpes vulpes) made in 24 hours interval (number of images per hour) for the villages of Byaga and Isperihovo.
F I G U R E 2 in Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru
F I G U R E 2 The effect of including data from Peruvian herbaria upon estimated International Union for Conservation of Nature (IUCN) threat assessments. The percentage of species assessed as DD (Data Deficient, grey), LC (Least Concern, green), VU (Vulnerable, yellow), EN (Endangered, orange), and CR (Critically Endangered, red) based upon data from: Top, international herbaria, and bottom, Peruvian and international herbaria.
F I G U R E 3 in Small and in-country herbaria are vital for accurate plant threat assessments: A case study from Peru
F I G U R E 3 The effect of including data from different small and large herbaria upon estimated International Union for Conservation of Nature (IUCN) threat assessments. The percentage of species assessed as DD (Data Deficient, grey), LC (Least Concern, green), VU (Vulnerable, yellow), EN (Endangered, orange), and CR (Critically Endangered, red) based upon data from: top, large herbaria only (>1,000,000 sheets); middle, large and medium herbaria (>500,000 sheets); and bottom, large, medium, and small herbaria (all herbaria).
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.